A novel AP2/ERF transcription factor, NtERF10, positively regulates plant height in tobacco.

Ethylene response factors have been shown to be involved in the effects of plant developmental processes and to regulate stress tolerance. The aim of this study was to recognize the regulatory mechanisms of ethylene response factors on tobacco plant height. In this study, a gene-edited mutant (ERF10-KO) and wild type (WT) were utilized as experimental materials. Transcriptome and metabolome analyses were used to investigate the regulatory mechanism of NtERF10 gene editing on plant height in tobacco. Here, through the analysis of differentially expressed genes (DEGs), 2051 genes were upregulated and 1965 genes were downregulated. We characterized the different ERF10-KO and WT plant heights and identified key genes for photosynthesis, the plant hormone signal transduction pathway and the terpene biosynthesis pathway. NtERF10 was found to affect the growth and development of tobacco by regulating the expression levels of the PSAA, PSBA, GLY17 and GGP3 genes. Amino acid metabolism was analyzed by combining analyses of differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs). In addition, we found that members of the bHLH, NAC, MYB, and WRKY transcription factor families have vital roles in regulating plant height. This study not only provides important insights into the positive regulation of the ethylene response factor NtERF10 on plant height during plant growth and development but also provides new research ideas for tobacco molecular breeding.

A Review of the Risk Factors and Approaches to Prevention of Post-Reperfusion Syndrome During Liver Transplantation.

Post-reperfusion syndrome (PRS) is a severe and highly lethal syndrome that occurs after declamping the portal vein forceps during liver transplantation. It is marked by severe hemodynamic disturbances manifested by decreased mean arterial pressure, increased heart rate and elevated pulmonary artery pressure. The complex pathogenesis of PRS remains understudied. It is generally believed to be related to the large amount of acidic, cold blood that enters the circulation after release of the portal clamp. This blood is rich in oxygen-free radicals and metabolic toxins, which not only aggravate the ischemia-reperfusion injury of the liver but also further attack the systemic organs indiscriminately. Considering the range of possible adverse prognoses including acute kidney injury, delirium and graft nonfunction, it is imperative that clinicians increase their awareness and prevention of PRS. The aim of this article is to review the current risk factors, pathophysiological mechanisms and prevention strategies for PRS.

Regio- and enantioselective nickel-alkyl catalyzed hydroalkylation of alkynes.

The migratory insertion of metal-hydride into alkene has allowed regioselective access to organometallics, readily participating in subsequent functionalization as one conventional pathway of hydroalkylation, whereas analogous process with feedstock alkyne is drastically less explored. Among few examples, the regioselectivity of metal-hydride insertion is mostly governed by electronic bias of alkynes. To alter the regioselectivity and drastically expand the intermediate pools that we can access, one aspirational design is through alternative nickel-alkyl insertion, providing opposite regioselectivity induced by steric demand. Leveraging in situ formed nickel-alkyl species, we herein report the regio- and enantioselective hydroalkylation of alkynes with broad functional group tolerance, excellent regio- and enantioselectivity, enabling efficient route to diverse valuable chiral allylic amines motifs. Preliminary mechanistic studies indicate the aminoalkyl radical species can participate in metal-capture and lead to formation of nickel-alkyl, of which the migratory insertion is key to reverse regioselectivity observed in metal-hydride insertion.

Protein-Protein Interaction Prediction Model Based on ProtBert-BiGRU-Attention.

The physiological activities within cells are mainly regulated through protein-protein interactions (PPI). Therefore, studying protein interactions has become an essential part of researching protein function and mechanisms. Traditional biological experiments required for PPI prediction are expensive and time consuming. For this reason, many methods based on predicting PPI from protein sequences have been proposed in recent years. However, existing computational methods usually require the combination of evolutionary feature information of proteins to predict PPI docking situations. Because different relevant features of selected proteins are chosen, there may be differences in the predicted results for PPI. This article proposes a PPI prediction method based on the pretrained protein sequence model ProtBert, combined with the Bidirectional Gated Recurrent Unit (BiGRU) and attention mechanism. Only using protein sequence information and leveraging ProtBert's powerful ability to capture amino acid feature information, BiGRU is used for further feature extraction of the amino acid vectors output by ProtBert. The attention mechanism is then applied to enhance the focus on different amino acid features and improve the expression ability of protein sequence features, ultimately obtaining binary classification results for protein interactions. Experimental results show that our proposed ProtBert-BiGRU-Attention model has good predictive performance for PPI. Through relevant comparative experiments, it has been proven that our model performs well in protein binary prediction. Furthermore, through the ablation experiment of the model, different deep learning modules' contributions to the prediction have been demonstrated.

High Young's Modulus Li6.4La3Zr1.4Ta0.6O12-Based Solid Electrolyte Interphase Regulating Lithium Deposition for Dendrite-Free Lithium Metal Anode.

Artificial solid electrolyte interphase (SEI) layers have been widely regarded as an effective protection for lithium (Li) metal anodes. In this work, an artificial SEI film consisting of dense Li6.4La3Zr1.4Ta0.6O12 (LLZTO) nanoparticles and polymerized styrene butadiene rubber is designed, which has good mechanical and chemical stability to effectively prevent Li anode corrosion by the electrolyte. The LLZTO-based SEI film can not only guide Li to uniformly deposit at the interface but also accelerate the electrochemical reaction kinetics due to its high Li+ conductivity. In particular, the high Young's modulus of the LLZTO-based SEI will regulate e- distribution in the continuous Li plating/stripping process and achieve uniform deposition of Li. As a consequence, the Li anode with LLZTO-based SEI (Li@LLZTO) enables symmetric cells to demonstrate a stable overpotential of 25 mV for 600 h at a current density of 1 mA cm-2 for 1 mA h cm-2. The Li@LLZTO||LFP (LiFePO4) full cell exhibits a capacity of 106 mA h g-1 after 800 cycles at 5 C with retention as high as 90%. Our strategy here suggests that the artificial SEI with high Young's modulus effectively inhibits the formation of Li dendrites and provides some guidance for the design of higher performance Li metal batteries.

Development and validation of a COVID-19 vaccination prediction model based on self-reporting results in Chinese older adults from September 2022 to November 2022: A nationwide cross-sectional study.

It was common to see that older adults were reluctant to be vaccinated for coronavirus disease 2019 (COVID-19) in China. There is a lack of practical prediction models to guide COVID-19 vaccination program. A nationwide, self-reported, cross-sectional survey was conducted from September 2022 to November 2022, including people aged 60 years or older. Stratified random sampling was used to divide the dataset into derivation, validation, and test datasets at a ratio of 6:2:2. Least absolute shrinkage and selection operator and multivariable logistic regression were used for variable screening and model construction. Discrimination and calibration were assessed primarily by area under the receiver operating characteristic curve (AUC) and calibration curve. A total of 35057 samples (53.65% males and mean age of 69.64 ± 7.24 years) were finally selected, which constitutes 93.73% of the valid samples. From 33 potential predictors, 19 variables were screened and included in the multivariable logistic regression model. The mean AUC in the validation dataset was 0.802, with sensitivity, specificity, and accuracy of 0.732, 0.718 and 0.729 respectively, which were similar to the parameters in the test dataset of 0.755, 0.715 and 0.720, respectively, and the mean AUC in the test dataset was 0.815. There were no significant differences between the model predicted values and the actual observed values for calibration in these groups. The prediction model based on self-reported characteristics of older adults was developed that could be useful for predicting the willingness for COVID-19 vaccines, as well as providing recommendations in improving vaccine acceptance.

Predictive and therapeutic value of lipoprotein-associated phospholipaseA2 in sarcopenia in chronic obstructive pulmonary disease.

BACKGROUND: Sarcopenia, characterized by progressive muscle dysfunction, is a common complication of chronic obstructive pulmonary disease (COPD). Our previous study revealed serum Lipoprotein-associated phospholipaseA2 (Lp-PLA2) level significantly increased in COPD and associated with exercise tolerance. This study further investigated the functions and target potential of Lp-PLA2 for sarcopenia in COPD. METHODS: The circulating Lp-PLA2 level/enzyme activity in COPD patients and age-matched healthy volunteers were measured. Clinical parameters on skeletal muscle were measured and their correlations with Lp-PLA2 were analyzed. We explored the involvement of Lp-PLA2 in vivo and treatment effectiveness of darapladib (a specific Lp-PLA2 inhibitor) in CS-induced muscle dysfunction models. RESULTS: Circulating Lp-PLA2 level/enzyme activity was elevated in COPD patients compared with healthy controls, negatively associated with skeletal muscle mass and function. In CS-induced muscle dysfunction murine models, up-regulated serum Lp-PLA2 level/enzyme activity was verified again. In CS-exposed mouse models, darapladib treatment reversed muscle mass loss and muscle dysfunction, meanwhile rescued upregulation of MuRF1 and atrogin-1, and activation of inflammatory factors, oxidant enzymes and NF-κB signaling. CONCLUSIONS: Lp-PLA2 could be a potential indicator for sarcopenia in COPD. Darapladib, a Lp-PLA2 inhibitor, can alleviate CS-induced skeletal muscle dysfunction and represents a potential therapeutic for sarcopenia in COPD.

Association of exposure to a mixture of phenols, parabens, and phthalates with altered serum thyroid hormone levels and the roles of iodine status and thyroid autoantibody status: A study among American adults.

BACKGROUND: Toxicological and epidemiological studies have shown that environmental endocrine disruptors interfere with hormonal homeostasis. However, there is limited research on the effects of mixed exposure to nonpersistent endocrine disruptors on thyroid hormones and the factors (e.g., presence status of thyroid autoantibodies or nutritional status of organismal iodine) that may influence this association. METHODS: Data were collected from the National Health and Nutrition Examination Survey (NHANES) 2007-2008 and 2011-2012. Relationships between single pollutants and thyroid hormone and thyroid autoantibody levels were assessed using generalized linear (GLM) and restricted cubic spline (RCS) regression models. Weighted quantile sum regression (WQS), group-weighted quantile sum regression (GWQS), quantile-based g-computation (qgcomp), and adaptive elasticity network (AENET) were applied to assess the mixed exposure effect. Next, subgroup analyses were performed on the basis of the urinary iodine concentration or thyroid autoantibody status to assess the modifying role of urinary iodine and thyroid autoantibodies. RESULTS: A total of 2385 study participants were included in this study. Both the single-pollutant model and the multipollutant mixed model revealed that parabens and bis(2-ethylhexyl) phthalate (DEHP) metabolites were significantly and negatively associated with serum thyroxine (T4) levels. However, no associations were found between the target pollutants and thyroid autoantibodies (thyroglobulin antibodies (TgAb) and thyroid peroxidase antibodies (TPOAb)). In addition, this study revealed that urinary iodine or thyroid autoantibody status altered the associations of some of the target pollutants with thyroid hormones. WQS and qgcomp analyses, revealed that the associations of mixed pollutants with hormones differed depending on the urinary iodine or antibody status, especially T4 and thyroid-stimulating hormone (TSH). CONCLUSION: Significant associations were found between phenols, parabens, and phthalates and serum thyroid hormone levels, with parabens and DEHP metabolites playing major roles. Urinary iodine and thyroid autoantibody status act as modifiers between environmental endocrine-disrupting pollutants and thyroid hormones.

Combining binding pocket mutagenesis and substrate tunnel engineering to improve an (R)-selective transaminase for the efficient synthesis of (R)-3-aminobutanol.

(R)-selective transaminases have the potential to act as efficient biocatalysts for the synthesis of important pharmaceutical intermediates. However, their low catalytic efficiency and unfavorable equilibrium limit their industrial application. Seven (R)-selective transaminases were identified using homologous sequence mining. Beginning with the optimal candidate from Mycolicibacterium hippocampi, virtual mutagenesis and substrate tunnel engineering were performed to improve catalytic efficiency. The obtained variant, T282S/Q137E, exhibited 3.68-fold greater catalytic efficiency (kcat/Km) than the wild-type enzyme. Using substrate fed-batch and air sweeping processes, effective conversion of 100 mM 4-hydroxy-2-butanone was achieved with a conversion rate of 93 % and an ee value > 99.9 %. This study provides a basis for mutation of (R)-selective transaminases and offers an efficient biocatalytic process for the asymmetric synthesis of (R)-3-aminobutanol.

Predicting high-risk pre-capillary pulmonary hypertension: an echocardiographic multiparameter scoring index.

BACKGROUND: The risk stratification of pulmonary arterial hypertension proposed by the European Society of Cardiology /European Respiratory Society guidelines in 2015 and 2022 included two to three echocardiographic indicators. However, the specific value of echocardiography in risk stratification of pre-capillary pulmonary hypertension (pcPH) has not been efficiently demonstrated. Given the complex geometry of the right ventricular (RV) and influencing factors of echocardiographic parameter, there is no single echocardiographic parameter that reliably informs about PH status. We hypothesize that a multi-parameter comprehensive index can more accurately evaluate the severity of the pcPH. The purpose of this study was to develop and validate an echocardiographic risk score model to better assist clinical identifying high risk of pcPH during initial diagnosis and follow-up. METHODS: We studied 197 consecutive patients with pcPH. A multivariable echocardiographic model was constructed to predict the high risk of pcPH in the training set. Points were assigned to significant risk factors in the final model based on ß-coefficients. We validated the model internally and externally. RESULTS: The echocardiographic score was constructed by multivariable logistic regression, which showed that pericardial effusion, right atrial (RA) area, RV outflow tract proximal diameter (RVOT-Prox), the velocity time integral of the right ventricular outflow tract (TVIRVOT) and S' were predictors of high risk of pcPH. The area under curve (AUC) of the training set of the scoring model was 0.882 (95%CI: 0.809-0.956, p < 0.0001). External validation was tested in a test dataset of 77 patients. The AUC of the external validation set was 0.852. A 10-point score risk score was generated, with scores ranging from 0 to 10 in the training cohort. The estimate risk of high risk of pcPH ranged from 25.1 to 94.6%. CONCLUSIONS: The echocardiographic risk score using five echocardiographic parameters could be comprehensive and useful to predict the high risk of pcPH for initial assessment and follow-up.

The relationship between health literacy and problematic internet use in Chinese college students: The mediating effect of subject well-being and moderating effect of social support.

BACKGROUND: The issue of problematic Internet use (PIU) amongst college students is emerging as a major concern for mental health. Factors such as health literacy, subjective well-being and the extent of social support may be critical in preventing PIU. However, the complex relationship between these factors has not been extensively explored in research. METHODS: A national cross-sectional study based on multistage random sampling was conducted in China in 2022. The subjects for this study were 7669 college students who completed a set of questionnaires assessing their health literacy, subjective well-being, PIU and social support. A structural equation model (SEM) was utilised for exploring the mediating effect of subjective well-being, and the PROCESS macro was used to test the moderating effect of social support. RESULTS: After controlling for demographic factors, a significantly negative correlation was found between health literacy and PIU, and subjective well-being partially mediated this relationship. In addition, social support was negatively related to PIU and could moderate the relationship between health literacy and subjective well-being and between subjective well-being and PIU. LIMITATIONS: This is a cross-sectional study, and the results cannot inform the causality between these variables. CONCLUSION: Results revealed that the relationship between health literacy and PIU was partially mediated by subjective well-being in college students. The correlation between health literacy and subjective well-being and between subjective well-being and PIU were moderated by social support. Thus, future interventions for college students' PIU should be facilitated by improving health literacy, subjective well-being and social support.

Exploring the therapeutic efficacy and pharmacological mechanism of Guizhi Fuling Pill on ischemic stroke: a meta-analysis and network pharmacology analysis.

The role of Guizhi Fuling Pill (GZFL) in the treatment of ischemic stroke (IS) is still controversial, and its pharmacological mechanism remains unclear. To evaluate the efficacy and potential pharmacological mechanisms of GZFL on IS, a comprehensive method integrating meta-analysis, network pharmacology, and molecular docking was employed. Eight electronic databases were searched from inception to November 2023. Review Manager 5.4.1 software was used for meta-analysis. Active compounds and targets of GZFL were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database, Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine, and Encyclopaedia of Traditional Chinese Medicine. Relevant targets of IS were obtained from the DisGeNet, Genecards, and DrugBank databases. GO biological function analysis and KEGG enrichment analysis were performed in the Metascape database. AutoDock Tools and PyMOL software were employed for Molecular docking. The intervention group significantly increased the total effective rate and decreased the NIHSS score. Administration of GZFL also improved the whole blood viscosity (low and high shear rates) and levels of fibrinogen, TNF-α, and IL-6. The key active compounds included quercetin, kaempferol, catechin, and beta-sitosterol, and the core target proteins included SRC, MAPK1, TP53, JUN, RELA, AKT1, and TNF. GO analysis mainly involved inflammation response, cellular response to lipids, and regulation of ion transport. The core pathways were lipid and atherosclerosis, cAMP, calcium, IL-17, and MAPK signaling pathways. Key active compounds showed good affinity with the core targets. The underlying mechanisms of GZFL in IS treatment are primarily related to its anti-inflammatory, anti-atherosclerosis, and neuroprotective effects.

A pH ultra-sensitive hydrated iridium oxyhydroxide films electrochemical sensor for label-free detection of Vibrio parahaemolyticus.

Vibrio parahaemolyticus (V. parahaemolyticus) is a major foodborne pathogen, which can cause serious foodborne illnesses like diarrhoea. Rapid on-site detection of foodborne pathogens is an ideal way to respond to foodborne illnesses. Herein, we provide an electrochemical sensor for rapid on-site detection. This sensor utilized a pH-sensitive metal-oxide material for the concurrent isothermal amplification and label-free detection of nucleic acids. Based on a pH-sensitive hydrated iridium oxide oxyhydroxide film (HIROF), the electrode transforms the hydrogen ion compound generated during nucleic acid amplification into potential, so as to achieve a real-time detection. The results can be transmitted to a smartphone via Bluetooth. Moreover, HIROF was applied in nucleic acid device detection, with a super-Nernst sensitivity of 77.6 mV/pH in the pH range of 6.0-8.5, and the sensitivity showed the best results so far. Detection of V. parahaemolyticus by this novel method showed a detection limit of 1.0 × 103 CFU/mL, while the time consumption was only 30 min, outperforming real-time fluorescence loop-mediated isothermal amplification (LAMP). Therefore, the characteristics of compact, portable, and fast make the sensor more widely used in on-site detection.

A Functional Switch Between Asperfumene and Fusicoccadiene Synthase and Entrance to Asperfumene Biosynthesis through a Vicinal Deprotonation-Reprotonation Process.

The diterpene synthase AfAS was identified from Aspergillus fumigatiaffinis. Its amino acid sequence and - according to a structural model - active site architecture are highly similar to those of the fusicocca-2,10(14)-diene synthase PaFS, but AfAS produces a structurally much more complex diterpene with a novel 6-5-5-5 tetracyclic skeleton called asperfumene. The cyclisation mechanism of AfAS was elucidated through isotopic labelling experiments and DFT calculations. The reaction cascade proceeds in its initial steps through similar intermediates as for the PaFS cascade, but then diverges through an unusual vicinal deprotonation-reprotonation process that triggers a skeletal rearrangement at the entrance to the steps leading to the unique asperfumene skeleton. The structural model revealed only one major difference between the active sites: The PaFS residue F65 is substituted by I65 in AfAS. Intriguingly, site-directed mutagenesis experiments with both diterpene synthases revealed that position 65 serves as a bidirectional functional switch for the biosynthesis of tetracyclic asperfumene versus structurally less complex diterpenes.

Erratum: Ophiopogonin-B Suppresses Epithelial-mesenchymal Transition in Human Lung Adenocarcinoma Cells via the Linc00668/miR-432-5p/EMT Axis: Erratum.

[This corrects the article DOI: 10.7150/jca.31338.].

Dual-stream multi-dependency graph neural network enables precise cancer survival analysis.

Histopathology image-based survival prediction aims to provide a precise assessment of cancer prognosis and can inform personalized treatment decision-making in order to improve patient outcomes. However, existing methods cannot automatically model the complex correlations between numerous morphologically diverse patches in each whole slide image (WSI), thereby preventing them from achieving a more profound understanding and inference of the patient status. To address this, here we propose a novel deep learning framework, termed dual-stream multi-dependency graph neural network (DM-GNN), to enable precise cancer patient survival analysis. Specifically, DM-GNN is structured with the feature updating and global analysis branches to better model each WSI as two graphs based on morphological affinity and global co-activating dependencies. As these two dependencies depict each WSI from distinct but complementary perspectives, the two designed branches of DM-GNN can jointly achieve the multi-view modeling of complex correlations between the patches. Moreover, DM-GNN is also capable of boosting the utilization of dependency information during graph construction by introducing the affinity-guided attention recalibration module as the readout function. This novel module offers increased robustness against feature perturbation, thereby ensuring more reliable and stable predictions. Extensive benchmarking experiments on five TCGA datasets demonstrate that DM-GNN outperforms other state-of-the-art methods and offers interpretable prediction insights based on the morphological depiction of high-attention patches. Overall, DM-GNN represents a powerful and auxiliary tool for personalized cancer prognosis from histopathology images and has great potential to assist clinicians in making personalized treatment decisions and improving patient outcomes.

Genomic investigation of bone tuberculosis highlighted the role of subclinical pulmonary tuberculosis in transmission.

BACKGROUND: Extrapulmonary tuberculosis (EPTB) without symptomatic pulmonary involvement has been thought to be non-transmissible, but EPTB with asymptomatic pulmonary tuberculosis (PTB) could transmit tuberculosis (TB). Genomic investigation of Mycobacterium tuberculosis (Mtb) isolates from EPTB may provide insight into its epidemiological role in TB transmission. METHODS: Between January 2017 and May 2020, 107 Mtb isolates were obtained from surgical drainage of bone TB patients at the Beijing Chest Hospital, and 218 Mtb strains were isolated from PTB cases. These 325 Mtb isolates were whole-genome sequenced to reconstruct a phylogenetic tree, identify transmission clusters, and infer transmission links using a Bayesian approach. Possible subclinical PTB in the bone TB patients was investigated with chest imaging by two independent experts. RESULTS: Among 107 bone TB patients, 10 were in genomic clusters (≤12 SNPs). Phylogenetic analysis suggested that three bone TB patients transmitted the infection to secondary cases, supported by epidemiological investigations. Pulmonary imaging of 44 bone TB patients revealed that 79.5 % (35/44) had radiological abnormalities suggestive of subclinical PTB. CONCLUSIONS: This study provides genomic evidence that bone TB patients without clinically diagnosed PTB can be sources of TB transmission, underscoring the importance of screening for subclinical, transmissible PTB among EPTB cases.

Identification of the global regulatory roles of RraA via the integrative transcriptome and proteome in Vibrio alginolyticus.

Bacterial ribonuclease E (RNase E) is vital for posttranscriptional regulation by degrading and processing RNA. The RraA protein inhibits RNase E activity through protein-protein interactions, exerting a global regulatory effect on gene expression. However, the specific role of RraA remains unclear. In this study, we investigated rraA expression in Vibrio alginolyticus ZJ-T and identified three promoters responsible for its expression, resulting in transcripts with varying 5'-UTR lengths. During the stationary phase, rraA was significantly posttranscriptionally inhibited. Deletion of rraA had no impact on bacterial growth in rich medium Luria-Bertani broth with salt (LBS) but resulted in decreased biofilm formation and increased resistance to polymyxin B. Transcriptome analysis revealed 350 differentially expressed genes (DEGs) between the wild type and the rraA mutant, while proteome analysis identified 267 differentially expressed proteins (DEPs). Integrative analysis identified 55 genes common to both DEGs and DEPs, suggesting that RraA primarily affects gene expression at the posttranscriptional level. KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis demonstrated that RraA facilitates the conversion of fatty acids, propionic acid, and branched-chain amino acids to acetyl-CoA while enhancing amino acid and peptide uptake. Notably, RraA positively regulates the expression of virulence-associated genes, including those involved in biofilm formation and the type VI secretion system. This study expands the understanding of the regulatory network of RraA through transcriptome analysis, emphasizing the importance of proteomic analysis in investigating posttranscriptional regulation.IMPORTANCERraA is an inhibitor protein of ribonuclease E that interacts with and suppresses its endonucleolytic activity, thereby playing a widespread regulatory role in the degradation and maturation of diverse mRNAs and noncoding small RNAs. However, the physiological functions and associated regulon of RraA in Vibrio alginolyticus have not been fully elucidated. Here, we report that RraA impacts virulence-associated physiological processes, namely, antibiotic resistance and biofilm formation, in V. alginolyticus. By conducting an integrative analysis of both the transcriptome and proteome, we revealed the involvement of RraA in carbon metabolism, amino acid catabolism, and transport, as well as in the type VI secretion system. Collectively, these findings elucidate the regulatory influence of RraA on multiple pathways associated with metabolism and pathogenesis in V. alginolyticus.

Plasma Ionomic Profile and Interaction Patterns in Coronary Artery Disease Patients.

Humans are exposed to various chemical elements that have been associated with the development and progression of diseases such as coronary artery disease (CAD). Unlike previous research, we employed a multi-element approach to investigate CAD patients and those with comorbid conditions such as diabetes (CAD-DM2), high blood pressure (CAD-HBP), or high blood lipids (CAD-HBL). Plasma concentrations of 21 elements, including lithium (Li), boron (B), aluminum (Al), calcium (Ca), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), strontium (Sr), cadmium (Cd), tin (Sn), stibium (Sb), barium (Ba), and lead (Pb), were measured in CAD patients (n = 201) and healthy subjects (n = 110) using inductively coupled plasma-mass spectrometry (ICP-MS). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were utilized to analyze the ionomic profiles. Spearman correlation analysis was employed to identify the interaction patterns among individual elements. We found that levels of Ba, Li, Ni, Zn and Pb were elevated in the CAD group compared to the healthy group, while Sb, Ca, Cu, Ti, Fe, and Se were lower. Furthermore, the CAD-DM2 group exhibited higher levels of Ni and Cd, while the CAD-HBP group showed lower levels of Co and Mn. In the CAD-HBL group, Ti was increased, whereas Ba, Cr, Cu, Co, Mn, and Ni were reduced. In conclusion, ionomic profiles can be utilized to differentiate CAD patients from healthy individuals, potentially providing insights for future treatment or dietary interventions.