Oral cancer detection and progression prediction using noninvasive cytology-based DNA ploidy approach.

BACKGROUND: Despite the oral cavity being readily accessible, oral cancer (OC) remains a significant burden. The objective of this study is to develop a DNA ploidy-based cytology test for early detection of high-risk oral lesions. METHODS: This retrospective study was conducted using 569 oral brushing samples collected from 95 normal and 474 clinically abnormal mucosa with biopsy diagnosis of reactive, low-grade or high-grade precancer or cancers. Brushing cells were processed to characterize DNA ploidy. A two-step DNA ploidy-based algorithm, the DNA ploidy oral cytology (DOC) test, was developed using a training set, and verified in test and validation sets to differentiate high-grade lesions (HGLs) from normal. The prognostic value of the test was evaluated by an independent outcome cohort, including progressed and non-progressing normal, reactive and low-grade lesions. Classification performance was assessed by accuracy, sensitivity, and specificity, while the prognostic value was evaluated by using the Cox proportional hazards analysis on 3-year progression-free survival (PFS). RESULTS: The developed DOC test exhibited high accuracy for detecting HGLs in the test and validation sets, with a sensitivity of 0.97 and 0.96, respectively. Its application to the Outcome cohort demonstrated significant prognostic value for 3-year PFS (log rank, p < 0.001). Multivariate analysis showed that high-grade pathology was the only variable explaining positive DOC test, not age, smoking, or lesional site. CONCLUSION: Clinical implementation of the DOC test could provide an effective screening method for detecting HGLs for biopsy and lesions at risk of progression.

Revealing the Roles of Guanidine Hydrochloride Ionic Liquid in Ion Inhibition and Defects Passivation for Efficient and Stable Perovskite Solar Cells.

As a result of full-scale ongoing global efforts, the power conversion efficiency (PCE) of the organic-inorganic metal halide perovskite has skyrocketed. Unfortunately, the long-term operational stability for commercialization standards is still lagging owing to intrinsic defects such as ion migration-induced degradation, undercoordinated Pb2+, and shallow defects initiated by disordered crystal growth. Herein, we employed multifunctional, non-volatile tetra-methyl guanidine hydrochloride [TMGHCL] ionic liquid (IL) as an additive to elucidate defects' passivation effects on organic-inorganic metal halide perovskite. More specifically, the formation of hydrogen bonds between H+ in GA+ and I- and coordinate bonding between Cl- and undercoordinated Pb2+ could significantly passivate these defects. The hypothesis was confirmed by both experimental and DFT simulations displaying that the optimized ratio of IL integration restrains ion migration, improving grains' size, and significantly elongating the carrier lifetime. Remarkably, the modified cell achieved a peak efficiency of 22.00 % with negligible hysteresis, compared to the control device's PCE of 20.12 %. In addition, the TMGHCL-based device retains its 93.29 % efficiency after 16 days of continuous exposure to air with a relative humidity of 35±5% and temperature of 25±5 °C. This efficient approach of adding IL to perovskites absorber can produce high PCE and has strong commercialization potential.

CardioDPi: An explainable deep-learning model for identifying cardiotoxic chemicals targeting hERG, Cav1.2, and Nav1.5 channels.

The cardiotoxic effects of various pollutants have been a growing concern in environmental and material science. These effects encompass arrhythmias, myocardial injury, cardiac insufficiency, and pericardial inflammation. Compounds such as organic solvents and air pollutants disrupt the potassium, sodium, and calcium ion channels cardiac cell membranes, leading to the dysregulation of cardiac function. However, current cardiotoxicity models have disadvantages of incomplete data, ion channels, interpretability issues, and inability of toxic structure visualization. Herein, an interpretable deep-learning model known as CardioDPi was developed, which is capable of discriminating cardiotoxicity induced by the human Ether-à-go-go-related gene (hERG) channel, sodium channel (Na_v1.5), and calcium channel (Ca_v1.5) blockade. External validation yielded promising area under the ROC curve (AUC) values of 0.89, 0.89, and 0.94 for the hERG, Na_v1.5, and Ca_v1.5 channels, respectively. The CardioDPi can be freely accessed on the web server CardioDPipredictor (http://cardiodpi.sapredictor.cn/). Furthermore, the structural characteristics of cardiotoxic compounds were analyzed and structural alerts (SAs) can be extracted using the user-friendly CardioDPi-SAdetector web service (http://cardiosa.sapredictor.cn/). CardioDPi is a valuable tool for identifying cardiotoxic chemicals that are environmental and health risks. Moreover, the SA system provides essential insights for mode-of-action studies concerning cardiotoxic compounds.

A Multi-Interface Structure of Graphdiyne/Cobalt Oxides for Chlorine Production.

A challenge facing the chlor-alkali process is the lack of electrocatalyst with high activity and selectivity for the efficient industrial production of chlorine. Herein the authors report a new electrocatalyst that can generate multi-interface structure by in situ growth of graphdiyne on the surface of cobalt oxides (GDY/Co3O4), which shows great potential in highly selective and efficient chlorine production. This result is due to the strong electron transfer and high density charge transport between GDY and Co3O4 and the interconversion of the mixed valence states of the Co atoms itself. These intrinsic characteristics efficiently enhance the conductivity of the catalyst, facilitate the reaction kinetics, and improve the overall catalytic selectivity and activity. Besides, the protective effect of the formed GDY layer is remarkable endowing the catalyst with excellent stability. The catalyst can selectively produce chlorine in low-concentration of NaCl aqueous solution at room temperature and pressure with the highest Faraday efficiency of 80.67% and an active chlorine yield rate of 184.40 mg h-1 cm-2, as well as superior long-term stability.

Plant-LncPipe: a computational pipeline providing significant improvement in plant lncRNA identification.

Long non-coding RNAs (lncRNAs) play essential roles in various biological processes, such as chromatin remodeling, post-transcriptional regulation, and epigenetic modifications. Despite their critical functions in regulating plant growth, root development, and seed dormancy, the identification of plant lncRNAs remains a challenge due to the scarcity of specific and extensively tested identification methods. Most mainstream machine learning-based methods used for plant lncRNA identification were initially developed using human or other animal datasets, and their accuracy and effectiveness in predicting plant lncRNAs have not been fully evaluated or exploited. To overcome this limitation, we retrained several models, including CPAT, PLEK, and LncFinder, using plant datasets and compared their performance with mainstream lncRNA prediction tools such as CPC2, CNCI, RNAplonc, and LncADeep. Retraining these models significantly improved their performance, and two of the retrained models, LncFinder-plant and CPAT-plant, alongside their ensemble, emerged as the most suitable tools for plant lncRNA identification. This underscores the importance of model retraining in tackling the challenges associated with plant lncRNA identification. Finally, we developed a pipeline (Plant-LncPipe) that incorporates an ensemble of the two best-performing models and covers the entire data analysis process, including reads mapping, transcript assembly, lncRNA identification, classification, and origin, for the efficient identification of lncRNAs in plants. The pipeline, Plant-LncPipe, is available at: https://github.com/xuechantian/Plant-LncRNA-pipline.

Reliability and Validity of a Theory-Based Determinants of Eating and Physical Activity Behaviors Questionnaire for Chinese Elementary School Children.

OBJECTIVE: The primary objective of this study was to develop and validate a Social Cognitive Theory-based instrument to identify psychosocial factors that influence diet and physical activity among Chinese children aged 10-12 years. DESIGN: This is a cross-sectional study, with data collected from questionnaires. SETTING: Two elementary schools in Beijing, China. PARTICIPANTS: Fourth to sixth-grade students (N = 1,486) aged 10-12 years were recruited. VARIABLES MEASURED: Gender, height, weight, nation, and grade were collected. Energy-balanced eating behaviors and their related sociopsychological factors were surveyed. ANALYSIS: Confirmatory factor analysis, Pearson correlations, Cronbach α index, and mediation analysis were used. RESULTS: (1) Confirmatory factor analysis revealed a 6-factor solution (51 items) and all factor loadings > 0.32, indicating that the model fitness was acceptable. (2) All correlation coefficients are statistically significant. All of the Cronbach α indexes were > 0.65, indicating acceptable reliability. (3) The mediating effect of goal intention and outcome expectations between self-efficacy and habit strength was statistically significant (P < 0.01), verifying the theory structure. CONCLUSIONS AND IMPLICATIONS: This questionnaire exhibits good internal consistency, reliability, and structural validity. It can be effectively employed to investigate energy-balanced eating behaviors related to the Social Cognitive Theory in Chinese children.

Sulfonic Acid Functionalized Ionic Liquids for Defect Passivation via Molecular Interactions for High-Quality Perovskite Films and Stable Solar Cells.

The high photoelectric conversion efficiency and low cost of perovskite solar cells (PSCs) have further inspired people's determination to push this technology toward industrialization. The high-quality perovskite films and high-efficiency and stable PSCs are the crucial factors. Ionic liquids have been proven to be an effective strategy for regulating high-quality perovskite films and high-performance PSCs. However, the regulation mechanism between ionic liquids and perovskites still needs further clarification. In this study, a novel sulfonic acid-functionalized ionic liquid, 1-butyl-3-methylimidazolium trifluoromethanesulfonate (BSO3HMImOTf), was used as an effective additive to regulate high-quality perovskite films and high-performance devices. Microscopic mechanism studies revealed strong interactions between BSO3HMImOTf and Pb2+ ions as well as halogens in the perovskite. The perovskite film is effectively passivated with the controlled crystal growth, suppressed ion migration, facilitating to the greatly improved photovoltaic performance, and superior long-term stability. This article reveals the regulatory mechanism of sulfonic acid type ionic liquids through testing characterization and mechanism analysis, providing a new approach for the preparation of high-quality perovskite devices.

UV-Triggered Hydrogel Coating of the Double Network Polyelectrolytes for Enhanced Endothelialization.

The left atrial appendage (LAA) occluder is an important medical device for closing the LAA and preventing stroke. The device-related thrombus (DRT) prevents the implantation of the occluder in exerting the desired therapeutic effect, which is primarily caused by the delayed endothelialization of the occluder. Functional coatings are an effective strategy for accelerating the endothelialization of occluders. However, the occluder surface area is particularly large and structurally complex, and the device is subjected to a large shear friction in the sheath during implantation, which poses a significant challenge to the coating. Herein, a hydrogel coating by the in situ UV-triggered polymerization of double-network polyelectrolytes is reported. The findings reveal that the double network and electrostatic interactions between the networks resulted in excellent mechanical properties of the hydrogel coating. The sulfonate and Arg-Gly-Asp (RGD) groups in the coating promoted hemocompatibility and endothelial growth of the occluder, respectively. The coating significantly accelerated the endothelialization of the LAA occluder in a canine model is further demonstrated. This study has potential clinical benefits in reducing both the incidence of DRT and the postoperative anticoagulant course for LAA closure.

Controlled Growth of Metal Atom Arrays on Graphdiyne for Seawater Oxidation.

Advanced atomic-level heterointerface engineering provides a promising method for the preparation of next-generation catalysts. Traditional carbon-based heterointerface catalytic performance rely heavily on the undetermined defects in complex and demanding preparation processes, rendering it impossible to control the catalytic performance. Here, we present a general method for the controlled growth of metal atom arrays on graphdiyne (GDY/IrCuOx), and we are surprised to find strong heterointerface strains during the growth. We successfully controlled the thickness of GDY to regulate the heterointerface metal atoms and achieved compressive strain at the interface. Experimental and density functional theory calculation results show that the unique incomplete charge transfer between GDY and metal atoms leads to the formation of strong interactions and significant heterointerface compressive strain between GDY and IrCuOx, which results in high oxidation performances with 1000 mA cm-2 at a low overpotential of 283 mV and long-term stability at large current densities in alkaline simulated seawater. We anticipate that this finding will contribute to construction of high-performance heterogeneous interface structures, leading to the development of new generation of GDY-based heterojunction catalysts in the field of catalysis for future promising performance.

Nuclear Binding Protein 2/Nesfatin-1 Affects Trophoblast Cell Fusion during Placental Development via the EGFR-PLCG1-CAMK4 Pathway.

Previous studies have shown that nuclear binding protein 2 (NUCB2) is expressed in the human placenta and increases with an increase in the syncytialization of trophoblast cells. This study aimed to investigate the role of NUCB2 in the differentiation and fusion of trophectoderm cells. In this study, the expression levels of NUCB2 and E-cadherin in the placentas of rats at different gestation stages were investigated. The results showed that there was an opposite trend between the expression of placental NUCB2 and E-cadherin in rat placentas in different trimesters. When primary human trophoblast (PHT) and BeWo cells were treated with high concentrations of Nesfatin-1, the trophoblast cell syncytialization was significantly inhibited. The effects of NUCB2 knockdown in BeWo cells and Forskolin-induced syncytialization were investigated. These cells showed a significantly decreased cell fusion rate. The mechanism underlying NUCB2-regulated trophoblast cell syncytialization was explored using RNA-Seq and the results indicated that the epidermal growth factor receptor (EGFR)-phospholipase C gamma 1 (PLCG1)-calmodulin-dependent protein kinase IV (CAMK4) pathway might be involved. The results suggested that the placental expression of NUCB2 plays an important role in the fusion of trophoblasts during differentiation via the EGFR-PLCG1-CAMK4 pathway.

Interfacial Heat and Mass Transfer Effects on Secondary Hydrate Formation under Different Dissociation Conditions.

Secondary hydrate formation or hydrate reformation poses a serious threat to the oil and gas transportation safety and natural gas hydrate exploitation efficiency. The hydrate reformation behaviors in porous media have been widely studied in large simulators due to their importance in traditional industries and new energy resources. However, it is difficult to understand the interfacial effects of hydrate reformation on the surface and in micropores of the porous media via a basic experimental apparatus. In this work, in situ X-ray computed tomography (X-CT) technology is used to detect the period, distribution, volume, and morphology characteristics of secondary hydrate formation during hydrate dissociation under depressurization, thermal stimulation, and the combined conditions. It is found that the secondary hydrate formation is inevitable under any conditions of hydrate dissociation. The secondary hydrate morphology varies among porous, grain-enveloping, grain-cementing, granular, and patchy structures, which are closely correlated to the hydrate reformation region and gas/water saturated conditions during hydrate dissociation. Accordingly, we revealed that the interfacial superheating phenomenon before hydrate dissociation could provide a supercooling condition for hydrate reformation. The gas flow along the interface of pores and inside the liquid water, as well as gas accumulation in noninterconnected pores, would exaggerate the hydrate reformation by increasing the local pore pressure. Meanwhile, the hydrate reformation aggravates the nonuniform distribution of gas hydrates in pores. In order to avoid hydrate reformation during dissociation, we further compared hydrate reformation and dissociation behaviors under three hydrate dissociation conditions. It is revealed that the combination of thermal stimulation and depressurization is an effective method for hydrate dissociation by retarding secondary hydrate formation. This study provides visual evidence and an interaction mechanism between interfacial heat and mass transfer, as well as secondary hydrate formation behaviors, which can be favorable for future quantitative research on secondary hydrate formation in different scales under various dissociation conditions.

GTF2H4 regulates partial EndMT via NF-κB activation through NCOA3 phosphorylation in ischemic diseases.

Partial endothelial-to-mesenchymal transition (EndMT) is an intermediate phenotype observed in endothelial cells (ECs) undergoing a transition toward a mesenchymal state to support neovascularization during (patho)physiological angiogenesis. Here, we investigated the occurrence of partial EndMT in ECs under hypoxic/ischemic conditions and identified general transcription factor IIH subunit 4 (GTF2H4) as a positive regulator of this process. In addition, we discovered that GTF2H4 collaborates with its target protein excision repair cross-complementation group 3 (ERCC3) to co-regulate partial EndMT. Furthermore, by using phosphorylation proteomics and site-directed mutagenesis, we demonstrated that GTF2H4 was involved in the phosphorylation of receptor coactivator 3 (NCOA3) at serine 1330, which promoted the interaction between NCOA3 and p65, resulting in the transcriptional activation of NF-κB and the NF-κB/Snail signaling axis during partial EndMT. In vivo experiments confirmed that GTF2H4 significantly promoted partial EndMT and angiogenesis after ischemic injury. Collectively, our findings reveal that targeting GTF2H4 is promising for tissue repair and offers potential opportunities for treating hypoxic/ischemic diseases.

High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar.

Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid "84K" (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

Incorporation of Decidual Stromal Cells Derived Exosomes in Sodium Alginate Hydrogel as an Innovative Therapeutic Strategy for Advancing Endometrial Regeneration and Reinstating Fertility.

Intrauterine adhesion (IUA) stands as a prevalent medical condition characterized by endometrial fibrosis and scar tissue formation within the uterine cavity, resulting in infertility and, in severe cases, recurrent miscarriages. Cell therapy, especially with stem cells, offers an alternative to surgery, but concerns about uncontrolled differentiation and tumorigenicity limit its use. Exosomes, more stable and immunogenicity-reduced than parent cells, have emerged as a promising avenue for IUA treatment. In this study, a novel approach has been proposed wherein exosomes originating from decidual stromal cells (DSCs) are encapsulated within sodium alginate hydrogel (SAH) scaffolds to repair endometrial damage and restore fertility in a mouse IUA model. Current results demonstrate that in situ injection of DSC-derived exosomes (DSC-exos)/SAH into the uterine cavity has the capability to induce uterine angiogenesis, initiate mesenchymal-to-epithelial transformation (MET), facilitate collagen fiber remodeling and dissolution, promote endometrial regeneration, enhance endometrial receptivity, and contribute to the recovery of fertility. RNA sequencing and advanced bioinformatics analysis reveal miRNA enrichment in exosomes, potentially supporting endometrial repair. This finding elucidates how DSC-exos/SAH mechanistically fosters collagen ablation, endometrium regeneration, and fertility recovery, holding the potential to introduce a novel IUA treatment and offering invaluable insights into the realm of regenerative medicine.

Bio-Inspired Superhydrophilic Self-Assembled Coronavirus-Like Pt-WC/CNT for Hydrogen Evolution Reaction.

This study presents a novel approach to enhance the catalytic activity of composite materials by promoting active surface exposure and improving hydrogen transfer performance. Through a self-assembly route involving tailored gas-solid and galvanic replacement reactions, Pt-WC/CNT catalysts with superhydrophilicity and coronavirus-like structure are synthesized. These unique structural features contribute to a remarkable enhancement in the electrocatalytic performance of the hydrogen evolution reaction (HER). Notably, the Pt-WC/CNT catalyst exhibits an outstanding intrinsic activity and efficient bubble transfer properties, leading to a high turnover frequency of 34.97 H2 ·s-1 at an overpotential of 100 mV. This value is 4.8 times higher than that achieved by commercial Pt/C catalysts (7.30 H2 ·s-1 ), establishing Pt-WC/CNT as one of the most active catalysts reported to date. Moreover, the combination of gas-solid and galvanic replacement reactions in the synthesis process offers a scalable route for the production of Pt-loading controllable composite catalysts, thus challenging the dominance of commercial Pt/C catalysts.

A novel dual-pooling attention module for UAV vehicle re-identification.

Vehicle re-identification (Re-ID) involves identifying the same vehicle captured by other cameras, given a vehicle image. It plays a crucial role in the development of safe cities and smart cities. With the rapid growth and implementation of unmanned aerial vehicles (UAVs) technology, vehicle Re-ID in UAV aerial photography scenes has garnered significant attention from researchers. However, due to the high altitude of UAVs, the shooting angle of vehicle images sometimes approximates vertical, resulting in fewer local features for Re-ID. Therefore, this paper proposes a novel dual-pooling attention (DpA) module, which achieves the extraction and enhancement of locally important information about vehicles from both channel and spatial dimensions by constructing two branches of channel-pooling attention (CpA) and spatial-pooling attention (SpA), and employing multiple pooling operations to enhance the attention to fine-grained information of vehicles. Specifically, the CpA module operates between the channels of the feature map and splices features by combining four pooling operations so that vehicle regions containing discriminative information are given greater attention. The SpA module uses the same pooling operations strategy to identify discriminative representations and merge vehicle features in image regions in a weighted manner. The feature information of both dimensions is finally fused and trained jointly using label smoothing cross-entropy loss and hard mining triplet loss, thus solving the problem of missing detail information due to the high height of UAV shots. The proposed method's effectiveness is demonstrated through extensive experiments on the UAV-based vehicle datasets VeRi-UAV and VRU.

Recent discoveries of the role of histone modifications and related inhibitors in pathological cardiac hypertrophy.

Pathological cardiac hypertrophy is a common response of the heart to various pathological stimuli. In recent years, various histone modifications, including acetylation, methylation, phosphorylation and ubiquitination, have been identified to have crucial roles in regulating chromatin remodeling and cardiac hypertrophy. Novel drugs targeting these epigenetic changes have emerged as potential treatments for pathological cardiac hypertrophy. In this review, we provide a comprehensive summary of the roles of histone modifications in regulating the development of pathological cardiac hypertrophy, and discuss potential therapeutic targets that could be utilized for its treatment.

Melatonin alleviates valproic acid-induced neural tube defects by modulating Src/PI3K/ERK signaling and oxidative stress.

Neural tube defects (NTDs) represent a developmental disorder of the nervous system that can lead to significant disability in children and impose substantial social burdens. Valproic acid (VPA), a widely prescribed first-line antiepileptic drug for epilepsy and various neurological conditions, has been associated with a 4-fold increase in the risk of NTDs when used during pregnancy. Consequently, urgent efforts are required to identify innovative prevention and treatment approaches for VPA-induced NTDs. Studies have demonstrated that the disruption in the delicate balance between cell proliferation and apoptosis is a crucial factor contributing to NTDs induced by VPA. Encouragingly, our current data reveal that melatonin (MT) significantly inhibits apoptosis while promoting the restoration of neuroepithelial cell proliferation impaired by VPA. Moreover, further investigations demonstrate that MT substantially reduces the incidence of neural tube malformations resulted from VPA exposure, primarily by suppressing apoptosis through the modulation of intracellular reactive oxygen species levels. In addition, the Src/PI3K/ERK signaling pathway appears to play a pivotal role in VPA-induced NTDs, with significant inhibition observed in the affected samples. Notably, MT treatment successfully reinstates Src/PI3K/ERK signaling, thereby offering a potential underlying mechanism for the protective effects of MT against VPA-induced NTDs. In summary, our current study substantiates the considerable protective potential of MT in mitigating VPA-triggered NTDs, thereby offering valuable strategies for the clinical management of VPA-related birth defects.

Prediction of Cytochrome P450 Inhibition Using a Deep Learning Approach and Substructure Pattern Recognition.

Cytochrome P450 (CYP) is a family of enzymes that are responsible for about 75% of all metabolic reactions. Among them, CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 participate in the metabolism of most drugs and mediate many adverse drug reactions. Therefore, it is necessary to estimate the chemical inhibition of Cytochrome P450 enzymes in drug discovery and the food industry. In the past few decades, many computational models have been reported, and some provided good performance. However, there are still several issues that should be resolved for these models, such as single isoform, models with unbalanced performance, lack of structural characteristics analysis, and poor availability. In the present study, the deep learning models based on python using the Keras framework and TensorFlow were developed for the chemical inhibition of each CYP isoform. These models were established based on a large data set containing 85715 compounds extracted from the PubChem bioassay database. On external validation, the models provided good AUC values with 0.97, 0.94, 0.94, 0.96, and 0.94 for CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4, respectively. The models can be freely accessed on the Web server named CYPi-DNNpredictor (cypi.sapredictor.cn), and the codes for the model were made open source in the Supporting Information. In addition, we also analyzed the structural characteristics of chemicals with CYP450 inhibition and detected the structural alerts (SAs), which should be responsible for the inhibition. The SAs were also made available online, named CYPi-SAdetector (cypisa.sapredictor.cn). The models can be used as a powerful tool for the prediction of CYP450 inhibitors, and the SAs should provide useful information for the mechanisms of Cytochrome P450 inhibition.

Comprehensive physiological, transcriptomic, and metabolomic analysis of the key metabolic pathways in millet seedling adaptation to drought stress.

Drought is one of the leading environmental constraints that affect the growth and development of plants and, ultimately, their yield and quality. Foxtail millet (Setaria italica) is a natural stress-resistant plant and an ideal model for studying plant drought resistance. In this study, two varieties of foxtail millet with different levels of drought resistance were used as the experimental material. The soil weighing method was used to simulate drought stress, and the differences in growth, photosynthetic physiology, metabolite metabolism, and gene transcriptional expression under drought stress were compared and analyzed. We aimed to determine the physiological and key metabolic regulation pathways of the drought-tolerant millet in resistance to drought stress. The results showed that drought-tolerant millet exhibited relatively stable growth and photosynthetic parameters under drought stress while maintaining a relatively stable level of photosynthetic pigments. The metabolomic, transcriptomic, and gene co-expression network analysis confirmed that the key to adaptation to drought by millet was to enhance lignin metabolism, promote the metabolism of fatty acids to be transformed into cutin and wax, and improve ascorbic acid circulation. These findings provided new insights into the metabolic regulatory network of millet adaptation to drought stress.