Root endodermal suberization induced by nitrate stress regulate apoplastic pathway rather than nitrate uptake in tobacco (Nicotiana tabacum L.).

Nitrogen levels and distribution in the rhizosphere strongly regulate the root architecture. Nitrate is an essential nutrient and an important signaling molecule for plant growth and development. Hydroponic experiments were conducted to investigate the differences in endodermal suberization in tobacco (Nicotiana tabacum L.) roots at three nitrate levels. Nitrogen accumulation was detected in the roots, shoots, and xylem sap. Nitrate influx on the root surface was also measured using the non-invasive self-referencing microsensor technique (SRMT). RNA-Seq analysis was performed to identify the genes related to endodermal suberization, nitrate transport, and endogenous abscisic acid (ABA) biosynthesis. The results showed that root length, root-shoot ratio, nitrate influx on the root surface, and NiA and NRT2.4 genes were regulated to maintain the nitrogen nutrient supply in tobacco under low nitrate conditions. Low nitrate levels enhanced root endodermal suberization and hence reduced the apoplastic transport pathway, and genes from the KCS, FAR, PAS2, and CYP86 families were upregulated. The results of exogenous fluridone, an ABA biosynthesis inhibitor, indicated that suberization of the tobacco root endodermis had no relevance to radial nitrate transport and accumulation. However, ABA enhances suberization, relating to ABA biosynthesis genes in the CCD family and degradation gene ABA8ox1.

2-Mercaptobenzothiazole-derived vulcanization accelerators in urine samples from Chinese adults.

Studies have discovered wide presence of 2-mercaptobenzothiazole (2-MBT) and 2-MBT-derived vulcanization accelerators (MVAs) in household dust samples, suggesting that these chemicals may have been pervasive in the environment. However, despite the potential for human exposure, the presence of MVAs in human urine, a common matrix used for assessing exposure to environmental chemicals, has not been thoroughly investigated. The current study comprehensively analyzed 11 kinds of MVAs in urine samples from the recruited general population (n = 197) living in Taizhou city, China. Five kinds of MVAs were detectable in >50 % of human urine samples. This indicates the widespread exposure to these vulcanization accelerators among the general population. The predominant target analytes in human urine were 2-MBT and 2,2'-dithiobisbenzothiazole (MBTS), with the mean urinary concentrations of 2.7 ng/mL (range

A Copula-based spatiotemporal probabilistic model for heavy metal pollution incidents in drinking water sources.

Water pollution incidents pose a significant threat to the safety of drinking water supplies and directly impact the quality of life of the residents when multiple pollutants contaminate drinking water sources. The majority of drinking water sources in China are derived from rivers and lakes that are often significantly impacted by water pollution incidents. To tackle the internal mechanisms between water quality and quantity, in this study, a Copula-based spatiotemporal probabilistic model for drinking water sources at the watershed scale is proposed. A spatiotemporal distribution simulation model was constructed to predict the spatiotemporal variations for water discharge and pollution to each drinking water source. This method was then applied to the joint probabilistic assessment for the entire Yangtze River downstream watershed in Nanjing City. The results demonstrated a significant negative correlation between water discharge and pollutant concentration following a water emergency. The water quantity-quality joint probability distribution reached the highest value (0.8523) after 14 hours of exposure during the flood season, much higher than it was (0.4460) during the dry season. As for the Yangtze River downstream watershed, five key risk sources (N1-N5) and two high-exposure drinking water sources (W3-W4; AEI=1) should be paid more attention. Overall, this research highlights a comprehensive mode between water quantity and quality for drinking water sources to cope with accidental water pollution.

Recent advances in engineering synthetic biomolecular condensates.

Biomolecular condensates are intriguing entities found within living cells. These structures possess the ability to selectively concentrate specific components through phase separation, thereby playing a crucial role in the spatiotemporal regulation of a wide range of cellular processes and metabolic activities. To date, extensive studies have been dedicated to unraveling the intricate connections between molecular features, physical properties, and cellular functions of condensates. This collective effort has paved the way for deliberate engineering of tailor-made condensates with specific applications. In this review, we comprehensively examine the underpinnings governing condensate formation. Next, we summarize the material states of condensates and delve into the design of synthetic intrinsically disordered proteins with tunable phase behaviors and physical properties. Subsequently, we review the diverse biological functions demonstrated by synthetic biomolecular condensates, encompassing gene regulation, cellular behaviors, modulation of biochemical reactions, and manipulation of endogenous protein activities. Lastly, we discuss future challenges and opportunities in constructing synthetic condensates with tunable physical properties and customized cellular functions, which may shed light on the development of new types of sophisticated condensate systems with distinct functions applicable to various scenarios.

Rational modification of Neisseria meningitidis ß1,3-N-acetylglucosaminyltransferase for lacto-N-neotetraose synthesis with reduced long-chain derivatives.

Lacto-N-neotetraose (LNnT), as a neutral core structure within human milk oligosaccharides (HMOs), has garnered widespread attention due to its exceptional physiological functions. In the process of LNnT synthesis using cellular factory approaches, substrate promiscuity of glycosyltransferases leads to the production of longer oligosaccharide derivatives. Here, rational modification of ß1,3-N-acetylglucosaminyltransferase from Neisseria meningitidis (LgtA) effectively decreased the concentration of long-chain LNnT derivatives. Specifically, the optimal ß1,4-galactosyltransferase (ß1,4-GalT) was selected from seven known candidates, enabling the efficient synthesis of LNnT in Escherichia coli BL21(DE3). Furthermore, the influence of lactose concentration on the distribution patterns of LNnT and its longer derivatives was investigated. The modification of LgtA was conducted with computational assistance, involving alanine scanning based on molecular docking to identify the substrate binding pocket and implementing large steric hindrance on crucial amino acids to obstruct LNnT entry. The implementation of saturation mutagenesis at positions 223 and 228 of LgtA yielded advantageous mutant variants that did not affect LNnT synthesis while significantly reducing the production of longer oligosaccharide derivatives. The most effective mutant, N223I, reduced the molar ratio of long derivatives by nearly 70 %, showcasing promising prospects for LNnT production with diminished byproducts.

Intracellular Construction of Organelle-like Compartments Facilitates Metabolic Flux in Escherichia coli.

The formation of well-designed synthetic compartments or membraneless organelles for applications in synthetic biology and cellular engineering has aroused enormous interest. However, establishing stable and robust intracellular compartments in bacteria remains a challenge. Here, we use the structured DIX domains derived from Wnt signaling pathway components, more specifically, Dvl2 and Axin1, as building blocks to generate intracellular synthetic compartments in Escherichia coli. Moreover, the aggregation behaviors and physical properties of the DIX-based compartments can be tailored by genetically embedding a specific dimeric domain into the DIX domains. Then, a pair of interacting motifs, consisting of the aforementioned dimeric domain and its corresponding binding ligand, was incorporated to modify the client recruitment pattern of the synthetic compartments. As a proof of concept, the human milk oligosaccharide lacto-N-tetraose (LNT) biosynthesis pathway was selected as a model metabolic pathway. The fermentation results demonstrated that the co-compartmentalization of sequential pathway enzymes into intracellular compartments created by DIX domain, or by the DIX domain in conjunction with interacting motifs, prominently enhanced the metabolic flux and increased LNT production. These synthetic protein compartments may provide a feasible and effective tool to develop versatile organelle-like compartments in bacteria for applications in cellular engineering and synthetic biology.

Crystal structure and structure-guided tunnel engineering in a bacterial ß-1,4-galactosyltransferase.

Lacto-N-neotetraose (LNnT), a representative oligosaccharide found in human milk, has been previously examined for its beneficial traits. However, the LNnT titer is limited by the efficient glycosyltransferase pathway, particularly with respect to the catalysis of rate-limiting steps. As data on the crystal structure of the key enzyme required for synthesizing LNnT are lacking, the synthesis of LNnT remains an uncertainty. Here, for the first time we report the three-dimensional structure of a bacterial ß-1,4-galactosyltransferase, Aaß4GalT, and analyze the critical role played by residues in its catalytic efficacy. Guided by structural insights, we engineered this enzyme to enhance its catalytic efficiency using structure-guided tunnel engineering. The mutant enzyme L5 (K155M/H156D/F157W/K185M/Q216V) so produced, showed a 50-fold enhancement in catalytic activity. Crystal structure analysis revealed that the mechanism underlying the improvement in activity was of the swing door type. The closed conformation formed by dense hydrophobic packing with Q216V-K155M widened and permitted substrate entry. Our results show that altering the tunnel conformation helped appropriately accommodate the substrate for catalysis and provide a structural basis for the modification of other glycosyltransferases.

Microstructural and functional substrates underlying dispositional greed and its link with trait but not state impulsivity.

The interplay between personality traits and impulsivity has long been a central theme in psychology and psychiatry. However, the potential association between Greed Personality Traits (GPT) and impulsivity, encompassing both trait and state impulsivity and future time perspective, remains largely unexplored. To address these issues, we employed questionnaires and an inter-temporal choice task to estimate corresponding trait/state impulsivity and collected multi-modal neuroimaging data (resting-state functional imaging: n = 430; diffusion-weighted imaging: n = 426; task-related functional imaging: n = 53) to investigate the underlying microstructural and functional substrates. Behavioral analyses revealed that GPT mediated the association between time perspective (e.g., present fatalism) and trait impulsivity (e.g., motor impulsivity). Functional imaging analyses further identified that brain activation strengths and patterns related to delay length, particularly in the dorsomedial prefrontal cortex, superior parietal lobule, and cerebellum, were associated with GPT. Moreover, individuals with similar levels of greed exhibited analogous spontaneous brain activity patterns, predominantly in the Default Mode Network (DMN), Fronto-Parietal Network (FPN), and Visual Network (VIS). Diffusion imaging analysis observed specific microstructural characteristics in the spinocerebellar/pontocerebellar fasciculus, internal/external capsule, and corona radiata that support the formation of GPT. Furthermore, the corresponding neural activation pattern, spontaneous neural activity pattern, and analogous functional couplings among the aforementioned brain regions mediated the relationships between time perspective and GPT and between GPT and motor impulsivity. These findings provide novel insights into the possible pathway such as time perspective → dispositional greed → impulsivity and uncover their underlying microstructural and functional substrates.

Stability of gross primary productivity and its sensitivity to climate variability in China.

Identifying the stability and sensitivity of land ecosystems to climate change is vital for exploring nature-based solutions. However, the underlying mechanisms governing ecosystem stability and sensitivity, especially in regions with overlapping ecological projects, remain unclear. based on Mann-Kendall, stability analysis method, and multiple regression method, this study quantified the stability and sensitivity of gross primary productivity (GPP) to climate variables [temperature, vapor pressure deficit (VPD), soil moisture, and radiation] in China from 1982 to 2019. Our findings revealed the following: (1) GPP demonstrated an increased trend with lower stability in Eastern regions, whereas a decreasing trend with higher stability was observed in Western and Southwest China. Notably, the stability of GPP was highest (74.58%) in areas with five overlapping ecological projects: Grain to Green, Natural Forest Resource Protection Project, Three-River Ecological Conservation and Restoration Project, Return Grazing to Grassland Project, and Three-North Shelter Forestation Project. (2) In regions with minimal or no overlapping ecological projects, temperature and radiation jointly dominated GPP variations. In contrast, water-related factors (VPD and soil moisture) significantly affected GPP in areas with multiple overlapping ecological projects. (3) In the southwestern and northeastern regions, GPP exhibited the highest sensitivity to climate change, whereas, in the eastern coastal areas and Tibet, GPP showed low sensitivity to climate change. In the Loess Plateau, where five ecological projects overlap extensively, carbon sinks primarily demonstrate a monotonic increasing trend, high stability, and low sensitivity to climate change. This study aimed to assess the stability of the land ecosystems and delineate their sensitivity to climate changes, thereby laying the groundwork for understanding ecosystem resilience.

Recent Progress in Physiological Significance and Biosynthesis of Lacto-N-triose II: Insights into a Crucial Biomolecule.

Lacto-N-triose II (LNTri II), an important precursor for human milk oligosaccharide (HMOs) synthesis, has garnered significant attention due to its structural features and physiological properties. Composed of galactose (Gal), N-acetylglucosamine (GlcNAc), and glucose (Glc), with the chemical structure GlcNAcß1,3Galß1,4Glc, the distinctive structure of LNTri II confers various physiological functions such as promoting the growth of beneficial bacteria, regulating the infant immune system, and preventing certain gastrointestinal diseases. Extensive research efforts have been dedicated to elucidating efficient enzymatic synthesis pathways for LNTri II production, with particular emphasis on the transglycosylation activity of ß-N-acetylhexosaminidases and the action of ß-1,3-N-acetylglucosaminyltransferases. Additionally, metabolic engineering and cell factory approaches have been explored, harnessing the potential of engineered microbial hosts for the large-scale biosynthesis of LNTri II. This review summarizes the structure, derivatives, physiological effects, and biosynthesis of LNTri II.

Recent advances of 3-fucosyllactose in health effects and production.

Human milk oligosaccharides (HMOs) have been recognized as gold standard for infant development. 3-Fucosyllactose (3-FL), being one of the Generally Recognized as Safe HMOs, represents a core trisaccharide within the realm of HMOs; however, it has received comparatively less attention in contrast to extensively studied 2'-fucosyllactose. The objective of this review is to comprehensively summarize the health effects of 3-FL, including its impact on gut microbiota proliferation, antimicrobial effects, immune regulation, antiviral protection, and brain maturation. Additionally, the discussion also covers the commercial application and regulatory approval status of 3-FL. Lastly, an organized presentation of large-scale production methods for 3-FL aims to provide a comprehensive guide that highlights current strategies and challenges in optimization.

Human milk oligosaccharides in preventing food allergy: A review through gut microbiota and immune regulation.

Food allergy (FA) has increasingly attracted global attention in past decades. However, the mechanism and effect of FA are complex and varied, rendering it hard to prevention and management. Most of the allergens identified so far are macromolecular proteins in food and may have potential cross-reactions. Human milk oligosaccharides (HMOs) have been regarded as an ideal nutrient component for infants, as they can enhance the immunomodulatory capacity to inhibit the progress of FA. HMOs may intervene in the development of allergies by modifying gut microbiota and increasing specific short-chain fatty acids levels. Additionally, HMOs could improve the intestinal permeability and directly or indirectly regulate the balance of T helper cells and regulatory T cells by enhancing the inflammatory signaling pathways to combat FA. This review will discuss the influence factors of FA, key species of gut microbiota involved in FA, types of FA, and profiles of HMOs and provide evidence for future research trends to advance HMOs as potential therapeutic aids in preventing the progress of FA.

Compartmentalization of pathway sequential enzymes into synthetic protein compartments for metabolic flux optimization in Escherichia coli.

Advancing the formation of artificial membraneless compartments with organizational complexity and diverse functionality remains a challenge. Typically, synthetic compartments or membraneless organelles are made up of intrinsically disordered proteins featuring low-complexity sequences or polypeptides with repeated distinctive short linear motifs. In order to expand the repertoire of tools available for the formation of synthetic membraneless compartments, here, a range of DIshevelled and aXin (DIX) or DIX-like domains undergoing head-to-tail polymerization were demonstrated to self-assemble into aggregates and generate synthetic compartments within E. coli cells. Then, synthetic complex compartments with diverse intracellular morphologies were generated by coexpressing different DIX domains. Further, we genetically incorporated a pair of interacting motifs, comprising a homo-dimeric domain and its anchoring peptide, into the DIX domain and cargo proteins, respectively, resulting in the alteration of both material properties and client recruitment of synthetic compartments. As a proof-of-concept, several human milk oligosaccharide biosynthesis pathways were chosen as model systems. The findings indicated that the recruitment of pathway sequential enzymes into synthetic compartments formed by DIX-DIX heterotypic interactions or by DIX domains embedded with specific interacting motifs efficiently boosted metabolic pathway flux and improved the production of desired chemicals. We propose that these synthetic compartment systems present a potent and adaptable toolkit for controlling metabolic flux and facilitating cellular engineering.

A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images with Multi-Relationship Graph Learning.

Chest radiography, commonly known as CXR, is frequently utilized in clinical settings to detect cardiopulmonary conditions. However, even seasoned radiologists might offer different evaluations regarding the seriousness and uncertainty associated with observed abnormalities. Previous research has attempted to utilize clinical notes to extract abnormal labels for training deep-learning models in CXR image diagnosis. However, these methods often neglected the varying degrees of severity and uncertainty linked to different labels. In our study, we initially assembled a comprehensive new dataset of CXR images based on clinical textual data, which incorporated radiologists' assessments of uncertainty and severity. Using this dataset, we introduced a multi-relationship graph learning framework that leverages spatial and semantic relationships while addressing expert uncertainty through a dedicated loss function. Our research showcases a notable enhancement in CXR image diagnosis and the interpretability of the diagnostic model, surpassing existing state-of-the-art methodologies. The dataset address of disease severity and uncertainty we extracted is: https://physionet.org/content/cad-chest/1.0/.

Discovery of a Thermostable Tagatose 4-Epimerase Powered by Structure- and Sequence-Based Protein Clustering.

d-Tagatose is a highly promising functional sweetener known for its various physiological functions. In this study, a novel tagatose 4-epimerase from Thermoprotei archaeon (Thar-T4Ease), with the ability to convert d-fructose to d-tagatose, was discovered through a combination of structure similarity search and sequence-based protein clustering. The recombinant Thar-T4Ease exhibited optimal activity at pH 8.5 and 85 °C, in the presence of 1 mM Ni2+. Its kcat and kcat/Km values toward d-fructose were measured to be 248.5 min-1 and 2.117 mM-1·min-1, respectively. Notably, Thar-T4Ease exhibited remarkable thermostability, with a t1/2 value of 198 h at 80 °C. Moreover, it achieved a conversion ratio of 18.9% using 100 g/L d-fructose as the substrate. Finally, based on sequence and structure analysis, crucial residues for the catalytic activity of Thar-T4Ease were identified by molecular docking and site-directed mutagenesis. This research expands the repertoire of enzymes with C4-epimerization activity and opens up new possibilities for the cost-effective production of d-tagatose from d-fructose.

Parental psychological control and depression, anxiety among adolescents: The mediating role of bedtime procrastination and moderating role of neuroticism.

Studies have shown that maladaptive parenting styles, particularly parental psychological control may be an important risk factor for emotional problems in adolescence. However, the potential mechanisms behind this association are still not fully understood. To fill the research gap, this study investigated the relationship between parental psychological control and depression and anxiety among adolescents. It also explored the mediating effect of bedtime procrastination and the moderating effect of neuroticism through a moderated mediation analysis. A sample of 665 adolescents (331 girls) were recruited from two secondary schools in southern China. All participants completed standardized self-report questionnaires measuring the severity of parental psychological control, bedtime procrastination, depression, anxiety, and neuroticism. Data were analyzed using SPSS 25.0 and PROCESS macros. The results indicated that parental psychological control had a positive predictive effect on depression and anxiety among adolescents. Bedtime procrastination partially mediated the relationship between parental psychological control and depression, as well as parental psychological control and anxiety. Neuroticism was found to play a moderating role in the path from bedtime procrastination to depression and from bedtime procrastination to anxiety, with these effects being stronger for adolescents with higher levels of neuroticism. This study advances a deeper understanding of how and when or for whom parental psychological control is related to adolescents' severe depression and anxiety. Our findings suggest that intervention programs or strategies aimed at reducing parental psychological control and assisting adolescents in establishing healthy sleep hygiene practices should be developed to decrease the risk of depression and anxiety in adolescents.

Interpretable medical image Visual Question Answering via multi-modal relationship graph learning.

Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficiency of medical professionals while relieving the burden on the public health system, particularly in resource-poor countries. However, existing medical VQA datasets are small and only contain simple questions (equivalent to classification tasks), which lack semantic reasoning and clinical knowledge. Our previous work proposed a clinical knowledge-driven image difference VQA benchmark using a rule-based approach (Hu et al., 2023). However, given the same breadth of information coverage, the rule-based approach shows an 85% error rate on extracted labels. We trained an LLM method to extract labels with 62% increased accuracy. We also comprehensively evaluated our labels with 2 clinical experts on 100 samples to help us fine-tune the LLM. Based on the trained LLM model, we proposed a large-scale medical VQA dataset, Medical-CXR-VQA, using LLMs focused on chest X-ray images. The questions involved detailed information, such as abnormalities, locations, levels, and types. Based on this dataset, we proposed a novel VQA method by constructing three different relationship graphs: spatial relationships, semantic relationships, and implicit relationship graphs on the image regions, questions, and semantic labels. We leveraged graph attention to learn the logical reasoning paths for different questions. These learned graph VQA reasoning paths can be further used for LLM prompt engineering and chain-of-thought, which are crucial for further fine-tuning and training multi-modal large language models. Moreover, we demonstrate that our approach has the qualities of evidence and faithfulness, which are crucial in the clinical field. The code and the dataset is available at https://github.com/Holipori/Medical-CXR-VQA.

Comparing the antireflux effect of laparoscopic proximal gastrectomy with double-flap technique reconstruction versus laparoscopic total gastrectomy with Roux-en-Y reconstruction for proximal early gastric cancer: study protocol for a multicentre, prospective, open-label, randomised controlled trial.

INTRODUCTION: Laparoscopic proximal gastrectomy with double flap technique (LPG-DFT) reconstruction has been used for proximal early gastric cancer in recent years. However, its feasibility and safety remain uncertain, as only a few retrospective studies have contained postoperative complications and long-term survival data. LPG-DFT for proximal early gastric cancer is still in the early stages of research. Large-scale, prospective randomised controlled trials (RCTs) are necessary to assess the value of LPG-DFT for proximal early gastric cancer. METHODS AND ANALYSIS: This study is a multicentre, prospective, open-label, RCT that investigates the antireflux effect of LPG-DFT compared with laparoscopic total gastrectomy with Roux-en-Y (LTG-RY) reconstruction for proximal early gastric cancer. A total of 216 eligible patients will be randomly assigned to the LPG-DFT group or the LTG-RY group at a 1:1 ratio using a central, dynamic and stratified block randomisation method, if inclusion criteria are met. General and clinical data will be collected when the patient is enrolled in the study and keep pace with the patient at each stage of his medical and follow-up pathway. The primary endpoint is the proportion of patients with reflux esophagitis (Los Angeles Grade B or more) within 12 months postoperatively. The secondary endpoints included intraoperative outcomes, postoperative recovery, postoperative pain assessment, pathological outcomes, postoperative quality of life, postoperative nutrition status, morbidity and mortality rate, and oncological outcomes (3-year overall survival (OS), 3-year disease-free survival (DFS), 5-year DFS and 5-year OS). ETHICS AND DISSEMINATION: The protocol is approved by the Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University ethics committee (registration number: SYSKY-2022-276-02) on 28 September 2022.We will report the positive as well as negative findings in international peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT05890339.

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.