A smartphone-enabled visual platform for detecting aflatoxins in peanut oil using colorimetric analysis coupled with magnetic imprinted solid-phase extraction.

The study aimed to develop a rapid and sensitive colorimetric platform based on the Emerson reaction to visualize and determine total aflatoxins (AFs) in peanut oil. This method offers the advantage of fast screening for AFs (AFB1, AFB2, AFG1, and AFG2), eliminating the need for specific antibodies. The proposed approach combined colorimetric detection with magnetic dummy imprinted solid-phase extraction and purification, enhancing sensitivity and selectivity. The oxidizer aided the colorless AFs in reacting with 4-aminoantipyrine, producing green condensates. Thus, a dual-mode approach was developed for AFs detection, employing both UV-vis colorimetric and smartphone-based colorimetry. Both methods showed a good linear relationship with the concentration of AFs. Notably, the smartphone-based method demonstrated a detection range of 0.5-57 µg/kg, with a detection limit as low as 0.21 µg/kg. The suggested colorimetric methods present a promising potential for onsite detection and fast screening of AFs in actual samples.

Molecular Contrastive Pretraining with Collaborative Featurizations.

Molecular pretraining, which learns molecular representations over massive unlabeled data, has become a prominent paradigm to solve a variety of tasks in computational chemistry and drug discovery. Recently, prosperous progress has been made in molecular pretraining with different molecular featurizations, including 1D SMILES strings, 2D graphs, and 3D geometries. However, the role of molecular featurizations with their corresponding neural architectures in molecular pretraining remains largely unexamined. In this paper, through two case studies─chirality classification and aromatic ring counting─we first demonstrate that different featurization techniques convey chemical information differently. In light of this observation, we propose a simple and effective MOlecular pretraining framework with COllaborative featurizations (MOCO). MOCO comprehensively leverages multiple featurizations that complement each other and outperforms existing state-of-the-art models that solely rely on one or two featurizations on a wide range of molecular property prediction tasks.

Association of Dietary Live Microbes and Nondietary Prebiotic/Probiotic Intake With Cognitive Function in Older Adults: Evidence From NHANES.

BACKGROUND: The current study aims to examine association of dietary live microbes and nondietary prebiotic/probiotic intake with cognitive function among older U.S. adults, examining heterogeneity across demographic characteristics and diseases. METHODS: Participants from the National Health and Nutrition Examination Survey 2011-2014 cycles were selected and administered 3 cognitive function tests: the Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest (CERAD W-L, including immediate [CERAD-IRT] and delayed [CERAD-DRT] memory), the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST). Test-specific and global cognition z-score was created. Based on their estimated dietary live microbes intake, participants were categorized into three groups: low, medium, and high. Text mining was employed to identify nondietary prebiotic/probiotic usage by examining the names and ingredients of dietary supplements or drugs. RESULTS: Participants in the medium (including AFT) and high (including global cognition, AFT, DSST, and CERAD-IRT) dietary live microbes intake group had significantly higher z-score of cognitive function compared to those in the low intake group. Among participants with cardiovascular disease history, nondietary prebiotic intake was associated with higher z-score in global cognition and CERAD-DRT compared to those who did not consume prebiotic. Additionally, probiotic intake was linked to higher z-score in global cognition, AFT, and DSST, particularly in participants with diabetes mellitus or hypertension. CONCLUSIONS: Our study suggests that the intake of dietary live microbes and nondietary probiotic/prebiotic was associated with better cognitive function in older adults, particularly in specific disease states.

Coordinated regulation of the mitochondrial retrograde response by circadian clock regulators and ANAC017.

Mitochondrial retrograde signaling (MRS) supports photosynthetic function under a variety of conditions. Induction of mitochondrial dysfunction with myxothiazol (a specific inhibitor of the mitochondrial bc1 complex) or antimycin A (an inhibitor of the mitochondrial bc1 complex and cyclic electron transport in the chloroplast under light conditions) in the light and dark revealed diurnal control of MRS. This was evidenced by (1) significantly enhanced binding of ANAC017 to promoters in the light compared with the dark in Arabidopsis plants treated with myxothiazol (but not antimycin A), (2) overlap in the experimentally determined binding sites for ANAC017 and circadian clock regulators in the promoters of ANAC013 and AOX1a, (3) a diurnal expression pattern for ANAC017 and transcription factors it regulates, (4) altered expression of ANAC017-regulated genes in circadian clock mutants with and without myxothiazol treatment, and (5) a decrease in the magnitude of LHY and CCA1 expression in an ANAC017-overexpressing line and protein-protein interaction between ANAC017 and PIF4. This study also shows a large difference in transcriptome responses to antimycin A and myxothiazol in the dark: these responses are ANAC017 independent, observed in shoots and roots, similar to biotic challenge and salicylic acid responses, and involve ERF and ZAT transcription factors. This suggests that antimycin A treatment stimulates a second MRS pathway that is mediated or converges with salicylic acid signaling and provides a merging point with chloroplast retrograde signaling.

BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks.

Mapping the connectome of the human brain using structural or functional connectivity has become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph Neural Networks (GNNs) motivated from geometric deep learning have attracted broad interest due to their established power for modeling complex networked data. Despite their superior performance in many fields, there has not yet been a systematic study of how to design effective GNNs for brain network analysis. To bridge this gap, we present BrainGB, a benchmark for brain network analysis with GNNs. BrainGB standardizes the process by (1) summarizing brain network construction pipelines for both functional and structural neuroimaging modalities and (2) modularizing the implementation of GNN designs. We conduct extensive experiments on datasets across cohorts and modalities and recommend a set of general recipes for effective GNN designs on brain networks. To support open and reproducible research on GNN-based brain network analysis, we host the BrainGB website at https://braingb.us with models, tutorials, examples, as well as an out-of-box Python package. We hope that this work will provide useful empirical evidence and offer insights for future research in this novel and promising direction.

DEEP DAG LEARNING OF EFFECTIVE BRAIN CONNECTIVITY FOR FMRI ANALYSIS.

Functional magnetic resonance imaging (fMRI) has become one of the most common imaging modalities for brain function analysis. Recently, graph neural networks (GNN) have been adopted for fMRI analysis with superior performance. Unfortunately, traditional functional brain networks are mainly constructed based on similarities among region of interests (ROIs), which are noisy and can lead to inferior results for GNN models. To better adapt GNNs for fMRI analysis, we propose DABNet, a Deep DAG learning framework based on Brain Networks for fMRI analysis. DABNet adopts a brain network generator module, which harnesses the DAG learning approach to transform the raw time-series into effective brain connectivities. Experiments on two fMRI datasets demonstrate the efficacy of DABNet. The generated brain networks also highlight the prediction-related brain regions and thus provide interpretations for predictions.

Neighborhood-Regularized Self-Training for Learning with Few Labels.

Training deep neural networks (DNNs) with limited supervision has been a popular research topic as it can significantly alleviate the annotation burden. Self-training has been successfully applied in semi-supervised learning tasks, but one drawback of self-training is that it is vulnerable to the label noise from incorrect pseudo labels. Inspired by the fact that samples with similar labels tend to share similar representations, we develop a neighborhood-based sample selection approach to tackle the issue of noisy pseudo labels. We further stabilize self-training via aggregating the predictions from different rounds during sample selection. Experiments on eight tasks show that our proposed method outperforms the strongest self-training baseline with 1.83% and 2.51% performance gain for text and graph datasets on average. Our further analysis demonstrates that our proposed data selection strategy reduces the noise of pseudo labels by 36.8% and saves 57.3% of the time when compared with the best baseline. Our code and appendices will be uploaded to https://github.com/ritaranx/NeST.

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis.

Multimodal brain networks characterize complex connectivities among different brain regions from both structural and functional aspects and provide a new means for mental disease analysis. Recently, Graph Neural Networks (GNNs) have become a de facto model for analyzing graph-structured data. However, how to employ GNNs to extract effective representations from brain networks in multiple modalities remains rarely explored. Moreover, as brain networks provide no initial node features, how to design informative node attributes and leverage edge weights for GNNs to learn is left unsolved. To this end, we develop a novel multiview GNN for multimodal brain networks. In particular, we treat each modality as a view for brain networks and employ contrastive learning for multimodal fusion. Then, we propose a GNN model which takes advantage of the message passing scheme by propagating messages based on degree statistics and brain region connectivities. Extensive experiments on two real-world disease datasets (HIV and Bipolar) demonstrate the effectiveness of our proposed method over state-of-the-art baselines.

Exogenous proanthocyanidins improve tolerance of Cu-toxicity by amelioration of oxidative damage and re-programming of gene expression in Medicago sativa.

Excess copper (Cu) in soil due to industrial and agricultural practices can result in reduced plant growth. Excess Cu resulted in severely retarded root growth with severe discoloration of Alfalfa (Medicago sativa) and Medicago truncatula. Growth in the presence of hydrogen peroxide resulted in similar symptoms that could be partially recovered by the addition of the reductant ascorbic acid revealing damage was likely due to oxidative stress. The addition of proanthocyanidins (PAs) in the presence of Cu prevented much of the damage, including plant growth and restoration of lignin synthesis which was inhibited in the presence of excess Cu. Transcriptome analyses of the impact of excess Cu and the amelioration after PAs treatment revealed that changes were enriched in functions associated with the cell wall and extracellular processes, indicating that inhibition of cell wall synthesis was likely the reason for retarded growth. Excess Cu appeared to induce a strong defense response, along with alterations in the expression of a number of genes encoding transcription factors, notably related to ethylene signaling. The addition of PAs greatly reduced this response, and also induced novel genes that likely help ameliorate the effects of excess Cu. These included induction of genes involved in the last step of ascorbic acid biosynthesis and of enzymes involved in cell wall synthesis. Combined, these results show that excess Cu causes severe oxidative stress damage and inhibition of cell wall synthesis, which can be relieved by the addition of PAs.

RNA-seq analysis of laser microdissected Arabidopsis thaliana leaf epidermis, mesophyll and vasculature defines tissue-specific transcriptional responses to multiple stress treatments.

Acclimation of plants to adverse conditions requires the coordination of gene expression and signalling pathways between tissues and cell types. As the energy and carbon capturing organs, leaves are significantly affected by abiotic and biotic stresses. However, tissue- or cell type-specific analyses of stress responses have focussed on the Arabidopsis root. Here, we comparatively explore the transcriptomes of three leaf tissues (epidermis, mesophyll, vasculature) after induction of diverse stress pathways by chemical stimuli (antimycin A, 3-amino-1,2,4-triazole, methyl viologen, salicylic acid) and ultraviolet light in Arabidopsis using laser capture microdissection followed by RNA sequencing. Stimulation of stress pathways caused an overall reduction in the number of genes expressed in a tissue-specific manner, though a small subset gained or changed their tissue specificity. We find no evidence of a common stress response, with only a few genes consistently responsive to two or more treatments in the analysed tissues. However, differentially expressed genes overlap between tissues for individual treatments. A focussed analysis provided evidence for an interaction of auxin and ethylene that mediates retrograde signalling during mitochondrial dysfunction specifically in the epidermis, and a gene regulatory network defined the hierarchy of interactions. Taken together, we have generated an extensive reference dataset that will be valuable for future experiments analysing transcriptional responses on a tissue or single-cell level. Our results will enable the tailoring of the tissue-specific engineering of stress-tolerant plants.

Conserved and Opposite Transcriptome Patterns during Germination in Hordeum vulgare and Arabidopsis thaliana.

Seed germination is a critical process for completion of the plant life cycle and for global food production. Comparing the germination transcriptomes of barley (Hordeum vulgare) to Arabidopsis thaliana revealed the overall pattern was conserved in terms of functional gene ontology; however, many oppositely responsive orthologous genes were identified. Conserved processes included a set of approximately 6000 genes that peaked early in germination and were enriched in processes associated with RNA metabolism, e.g., pentatricopeptide repeat (PPR)-containing proteins. Comparison of orthologous genes revealed more than 3000 orthogroups containing almost 4000 genes that displayed similar expression patterns including functions associated with mitochondrial tricarboxylic acid (TCA) cycle, carbohydrate and RNA/DNA metabolism, autophagy, protein modifications, and organellar function. Biochemical and proteomic analyses indicated mitochondrial biogenesis occurred early in germination, but detailed analyses revealed the timing involved in mitochondrial biogenesis may vary between species. More than 1800 orthogroups representing 2000 genes displayed opposite patterns in transcript abundance, representing functions of energy (carbohydrate) metabolism, photosynthesis, protein synthesis and degradation, and gene regulation. Differences in expression of basic-leucine zippers (bZIPs) and Apetala 2 (AP2)/ethylene-responsive element binding proteins (EREBPs) point to differences in regulatory processes at a high level, which provide opportunities to modify processes in order to enhance grain quality, germination, and storage as needed for different uses.

Linking mitochondrial and chloroplast retrograde signalling in plants.

Retrograde signalling refers to the regulation of nuclear gene expression in response to functional changes in organelles. In plants, the two energy-converting organelles, mitochondria and chloroplasts, are tightly coordinated to balance their activities. Although our understanding of components involved in retrograde signalling has greatly increased in the last decade, studies on the regulation of the two organelle signalling pathways have been largely independent. Thus, the mechanism of how mitochondrial and chloroplastic retrograde signals are integrated is largely unknown. Here, we summarize recent findings on the function of mitochondrial signalling components and their links to chloroplast retrograde responses. From this, a picture emerges showing that the major regulators are integrators of both organellar retrograde signalling pathways. This article is part of the theme issue 'Retrograde signalling from endosymbiotic organelles'.

Induction of N-Ras degradation by flunarizine-mediated autophagy.

Ras GTPases are powerful drivers for tumorigenesis, but directly targeting Ras for treating cancer remains challenging. The growth and transforming activity of the aggressive basal-like breast cancer (BLBC) are driven by N-Ras. To target N-Ras in BLBC, this study screened existing pharmacologically active compounds for the new ability to induce N-Ras degradation, which led to the identification of flunarizine (FLN), previously approved for treating migraine and epilepsy. The FLN-induced N-Ras degradation was not affected by a 26S-proteasome inhibitor. Rather, it was blocked by autophagy inhibitors. Furthermore, N-Ras can be seen co-localized with active autophagosomes upon FLN treatment, suggesting that FLN alters the autophagy pathway to degrade N-Ras. Importantly, FLN treatment recapitulated the effect of N-RAS silencing in vitro by selectively inhibiting the growth of BLBC cells, but not that of breast cancer cells of other subtypes. In addition, in vivo FLN inhibited tumor growth of a BLBC xenograft model. In conclusion, this proof-of-principle study presents evidence that the autophagy pathway can be coerced by small molecule inhibitors, such as FLN, to degrade Ras as a strategy to treat cancer. FLN has low toxicity and should be further investigated to enrich the toolbox of cancer therapeutics.

Nitric Oxide Regulates Seedling Growth and Mitochondrial Responses in Aged Oat Seeds.

Mitochondria are the source of reactive oxygen species (ROS) in plant cells and play a central role in the mitochondrial electron transport chain (ETC) and tricarboxylic acid cycle (TCA) cycles; however, ROS production and regulation for seed germination, seedling growth, as well as mitochondrial responses to abiotic stress, are not clear. This study was conducted to obtain basic information on seed germination, embryo mitochondrial antioxidant responses, and protein profile changes in artificial aging in oat seeds (Avena sativa L.) exposed to exogenous nitric oxide (NO) treatment. The results showed that the accumulation of H2O2 in mitochondria increased significantly in aged seeds. Artificial aging can lead to a loss of seed vigor, which was shown by a decline in seed germination and the extension of mean germination time (MGT). Seedling growth was also inhibited. Some enzymes, including catalase (CAT), glutathione reductase (GR), dehydroascorbate reductase (DHAR), and monodehydroascorbate reductase (MDHAR), maintained a lower level in the ascorbate-glutathione (AsA-GSH) scavenging system. Proteomic analysis revealed that the expression of some proteins related to the TCA cycle were down-regulated and several enzymes related to mitochondrial ETC were up-regulated. With the application of 0.05 mM NO in aged oat seeds, a protective effect was observed, demonstrated by an improvement in seed vigor and increased H2O2 scavenging ability in mitochondria. There were also higher activities of CAT, GR, MDHAR, and DHAR in the AsA-GSH scavenging system, enhanced TCA cycle-related enzymes (malate dehydrogenase, succinate-CoA ligase, fumarate hydratase), and activated alternative pathways, as the cytochrome pathway was inhibited. Therefore, our results indicated that seedling growth and seed germinability could retain a certain level in aged oat seeds, predominantly depending on the lower NO regulation of the TCA cycle and AsA-GSH. Thus, it could be concluded that the application of 0.05 mM NO in aged oat seeds improved seed vigor by enhancing the mitochondrial TCA cycle and activating alternative pathways for improvement.

Proteomic Identification of Differentially Expressed Proteins during Alfalfa (Medicago sativa L.) Flower Development.

Flower development, pollination, and fertilization are important stages in the sexual reproduction process of plants; they are also critical steps in the control of seed formation and development. During alfalfa (Medicago sativa L.) seed production, some distinct phenomena such as a low seed setting ratio, serious flower falling, and seed abortion commonly occur. However, the causes of these phenomena are complicated and largely unknown. An understanding of the mechanisms that regulate alfalfa flowering is important in order to increase seed yield. Hence, proteomic technology was used to analyze changes in protein expression during the stages of alfalfa flower development. Flower samples were collected at pre-pollination (S1), pollination (S2), and the post-pollination senescence period (S3). Twenty-four differentially expressed proteins were successfully identified, including 17 down-regulated in pollinated flowers, one up-regulated in pollinated and senesced flowers, and six up-regulated in senesced flowers. The largest proportions of the identified proteins were involved in metabolism, signal transduction, defense response, oxidation reduction, cell death, and programmed cell death (PCD). Their expression profiles demonstrated that energy metabolism, carbohydrate metabolism, and amino acid metabolism provided the nutrient foundation for pollination in alfalfa. Furthermore, there were three proteins involved in multiple metabolic pathways: dual specificity kinase splA-like protein (kinase splALs), carbonic anhydrase, and NADPH: quinone oxidoreductase-like protein. Expression patterns of these proteins indicated that MAPK cascades regulated multiple processes, such as signal transduction, stress response, and cell death. PCD also played an important role in the alfalfa flower developmental process, and regulated both pollination and flower senescence. The current study sheds some light on protein expression profiles during alfalfa flower development and contributes to the understanding of the basic molecular mechanisms during the alfalfa flowering process. These results may offer insight into potential strategies for improving seed yield, quality, and stress tolerance in alfalfa.

Proteomic and Physiological Analysis of the Response of Oat (Avena sativa) Seeds to Heat Stress under Different Moisture Conditions.

Seeds lose their viability when they are exposed to high temperature and moisture content (MC) during storage. The expression and metabolism of proteins plays a critical role in seed resistance to heat stress. However, the proteome response to heat stress in oat (Avena sativa) seeds during storage has not been revealed. To understand mechanisms of heat stress acclimation and tolerance in oat seeds, an integrated physiological and comparative proteomic analysis was performed on oat seeds with different MC during heat stress. Oat seeds with 10% and 16% MC were subjected to high temperatures (35, 45, and 50°C) for 24 and 2 days, respectively, and changes in physiological and biochemical characteristics were analyzed. The results showed that seed vigor decreased significantly with temperature increase from 35 to 50°C. Also, the proline content in 10% MC seeds decreased significantly (p < 0.05) whereas that in 16% MC seeds increased significantly (p < 0.05) during heat treatment from 35 to 50°C. There were no significant differences in malondialdehyde content in 10% MC seeds with temperature from 35 to 50°C, but a significant (p < 0.05) decline occurred in 16% MC seeds at 45°C. Proteome analysis revealed 21 significantly different proteins, including 19 down-regulated and two up-regulated proteins. The down-regulated proteins, notably six heat shock proteins and two ATP synthases, have important roles in the mobilization of carbohydrates and energy, and in the balance between synthesis and degradation of other proteins during seed deterioration. The up-regulation of argininosuccinate synthase participated in proline biosynthesis at 16% MC, which is important for maintaining reactive oxygen species homeostasis for the resistance of heat stress. In summary, heat-responsive protein species and mitochondrial respiratory metabolism were sensitive to high temperature and MC treatment. These studies provide a new insight into acclimation and tolerance to heat stress in oat seeds.

Impact of α-amylase combined with hydrochloric acid hydrolysis on structure and digestion of waxy rice starch.

The structure and in vitro digestibility of native waxy rice starch by the combined hydrolysis of α-amylase and hydrochloric acid were investigated in this study. The combined hydrolysis technique generated higher hydrolysis rate and extent than the enzymatic hydrolysis. The granular appearance and chromatograph profile demonstrated that α-amylase and hydrochloric acid exhibited different patterns of hydrolysis. The rise in the ratio of absorbance 1047/1022cm(-1), the melting temperature range (Tc-To), and the melting enthalpy (ΔH) were observed during the combined hydrolysis. These results suggest that α-amylase simultaneously cleaves the amorphous and crystalline regions, whereas the amorphous regions of starch granules are preferentially hydrolyzed during the acid hydrolysis. Furthermore, the combined hydrolysis increased rapidly digestible starch (RDS) while decreased slowly digestible starch (SDS) and resistant starch (RS), indicating that the hydrolysis mode affected the digestion property of native waxy rice starch.

Identification and releasing characteristics of high-amylose corn starch-cinnamaldehyde inclusion complex prepared using ultrasound treatment.

In this study, the high-amylose corn starch-cinnamaldehyde inclusion complex was prepared by an ultrasound treatment and its releasing characteristic was investigated. The results showed that the ultrasound treatment (35°C, 10min and 250W) generated a higher encapsulation rate of 40.2% than the conventional treatment (encapsulation rate, 5.7%). Data obtained from Fourier-transform infrared (FT-IR) spectroscopy and thermogravimetric analysis (TGA) indicated that cinnamaldehyde was successfully encapsulated by high-amylose corn starch and the encapsulation significantly increased the dissociation temperature of cinnamaldehyde by around 70°C. Compared to the physical mixture of high-amylose corn starch and cinnamaldehyde, the formed inclusion complex had good retention ability and reduced the releasing rate of cinnamaldehyde from 57.5% to 28.4% in the first week. These results suggest that cinnamaldehyde could be encapsulated by high-amylose corn starch with an ultrasound treatment for presenting the releasing behavior in food preservation.

Three-dimensional vasculature reconstruction of tumour microenvironment via local clustering and classification.

The vasculature inside breast cancers is one important component of the tumour microenvironment. The investigation of its spatial morphology, distribution and interactions with cancer cells, including cancer stem cells, is essential for elucidating mechanisms of tumour development and treatment response. Using confocal microscopy and fluorescent markers, we have acquired three-dimensional images of vasculature within mammary tumours and normal mammary gland of mouse models. However, it is difficult to segment and reconstruct complex vasculature accurately from the in vivo three-dimensional images owing to the existence of uneven intensity and regions with low signal-to-noise ratios (SNR). To overcome these challenges, we have developed a novel three-dimensional vasculature segmentation method based on local clustering and classification. First, images of vasculature are clustered into local regions, whose boundaries well delineate vasculature even in low SNR and uneven intensity regions. Then local regions belonging to vasculature are identified by applying a semi-supervised classification method based on three informative features of the local regions. Comparison of results using simulated and real vasculature images, from mouse mammary tumours and normal mammary gland, shows that the new method outperforms existing methods, and can be used for three-dimensional images with uneven background and low SNR to achieve accurate vasculature reconstruction.