High fried food consumption impacts anxiety and depression due to lipid metabolism disturbance and neuroinflammation.

Western dietary patterns have been unfavorably linked with mental health. However, the long-term effects of habitual fried food consumption on anxiety and depression and underlying mechanisms remain unclear. Our population-based study with 140,728 people revealed that frequent fried food consumption, especially fried potato consumption, is strongly associated with 12% and 7% higher risk of anxiety and depression, respectively. The associations were more pronounced among male and younger consumers. Consistently, long-term exposure to acrylamide, a representative food processing contaminant in fried products, exacerbates scototaxis and thigmotaxis, and further impairs exploration ability and sociality of adult zebrafish, showing anxiety- and depressive-like behaviors. Moreover, treatment with acrylamide significantly down-regulates the gene expression of tjp2a related to the permeability of blood-brain barrier. Multiomics analysis showed that chronic exposure to acrylamide induces cerebral lipid metabolism disturbance and neuroinflammation. PPAR signaling pathway mediates acrylamide-induced lipid metabolism disorder in the brain of zebrafish. Especially, chronic exposure to acrylamide dysregulates sphingolipid and phospholipid metabolism, which plays important roles in the development of anxiety and depression symptoms. In addition, acrylamide promotes lipid peroxidation and oxidation stress, which participate in cerebral neuroinflammation. Acrylamide dramatically increases the markers of lipid peroxidation, including (±)5-HETE, 11(S)-HETE, 5-oxoETE, and up-regulates the expression of proinflammatory lipid mediators such as (±)12-HETE and 14(S)-HDHA, indicating elevated cerebral inflammatory status after chronic exposure to acrylamide. Together, these results both epidemiologically and mechanistically provide strong evidence to unravel the mechanism of acrylamide-triggered anxiety and depression, and highlight the significance of reducing fried food consumption for mental health.

Acidification induce chemical and microbial variation in tea plantation soils and bacterial degradation of the key acidifying phenolic acids.

Camellia sinensis is an important economic plant grown in southern subtropical hilly areas, especially in China, mainly for the production of tea. Soil acidification is a significant cause of the reduction of yield and quality and continuous cropping obstacles in tea plants. Therefore, chemical and microbial properties of tea growing soils were investigated and phenolic acid-degrading bacteria were isolated from a tea plantation. Chemical and ICP-AES investigations showed that the soils tested were acidic, with pH values of 4.05-5.08, and the pH negatively correlated with K (p < 0.01), Al (p < 0.05), Fe and P. Aluminum was the highest (47-584 mg/kg) nonessential element. Based on high-throughput sequencing, a total of 34 phyla and 583 genera were identified in tea plantation soils. Proteobacteria and Acidobacteria were the main dominant phyla and the highest abundance of Acidobacteria was found in three soils, with nearly 22% for the genus Gp2. Based on the functional abundance values, general function predicts the highest abundance, while the abundance of amino acids and carbon transport and metabolism were higher in soils with pH less than 5. According to Biolog Eco Plate™ assay, the soil microorganisms utilized amino acids well, followed by polymers and phenolic acids. Three strains with good phenolic acid degradation rates were obtained, and they were identified as Bacillus thuringiensis B1, Bacillus amyloliquefaciens B2 and Bacillus subtilis B3, respectively. The three strains significantly relieved the inhibition of peanut germination and growth by ferulic acid, p-coumaric acid, p-hydroxybenzoic acid, cinnamic acid, and mixed acids. Combination of the three isolates showed reduced relief of the four phenolic acids due to the antagonist of B2 against B1 and B3. The three phenolic acid degradation strains isolated from acidic soils display potential in improving the acidification and imbalance in soils of C. sinensis.

Comprehensive lipidomic analysis revealed the effects of fermented Morus alba L. intake on lipid profile in backfat and muscle tissue of Yuxi black pigs.

Mulberry leaf is a widely used protein feed and is often used as a strategy to reduce feed costs and improve meat quality in the livestock industry. However, to date, there is a lack of research on the improvement of meat quality using mulberry leaves, and the exact mechanisms are not yet known. The results showed that fermented mulberry leaves significantly reduced backfat content but had no significant effect on intramuscular fat (IMF). Lipidomic analysis showed that 98 and 303 differential lipid molecules (p < 0.05) were identified in adipose and muscle tissues, respectively, including triglycerides (TG), phosphatidylcholine, phosphatidylethanolamine, sphingolipids, and especially TG; therefore, we analysed the acyl carbon atom number of TG. The statistical results of acyl with different carbon atom numbers of TG in adipose tissue showed that the acyl group containing 13 carbon atoms (C13) in TG was significantly upregulated, whereas C15, C16, C17, and C23 were significantly downregulated, whereas in muscle tissue, the C12, C19, C23, C25, and C26 in TG were significantly downregulated. Acyl changes in TG were different for different numbers of carbon atoms in different tissues. We found that the correlations of C (14-18) in adipose tissue were higher, but in muscle tissue, the correlations of C (18-26) were higher. Through pathway enrichment analysis, we identified six and four metabolic pathways with the highest contributions of differential lipid metabolites in adipose and muscle tissues respectively. These findings suggest that fermented mulberry leaves improve meat quality mainly by inhibiting TG deposition by downregulating medium- and short-chain fatty acids in backfat tissue and long-chain fatty acids in muscle tissue.

Toxic effects of isofenphos-methyl on zebrafish embryonic development.

Isofenphos-methyl (IFP) is widely used as an organophosphorus for controlling underground insects and nematodes. However, excessive use of IFP may pose potential risks to the environment and humans, but little information is available on its sublethal toxicity to aquatic organisms. To address this knowledge gap, the current study exposed zebrafish embryos to 2, 4, and 8 mg/L IFP within 6-96 h past fertilization (hpf) and measured mortality, hatching, developmental abnormalities, oxidative stress, gene expressions, and locomotor activity. The results showed that IFP exposure reduced the rates of heart and survival rate, hatchability, and body length of embryos and induced uninflated swim bladder and developmental malformations. Reduction in locomotive behavior and inhibition of AChE activity indicated that IFP exposure may induce behavioral defects and neurotoxicity in zebrafish larvae. IFP exposure also led to pericardial edema, longer venous sinus-arterial bulb (SV-BA) distance, and apoptosis of the heart cells. Moreover, IFP exposure increased the accumulation of reactive oxygen species (ROS) and the content of malonaldehyde (MDA), also elevated the levels of antioxidant enzymes of superoxide dismutase (SOD) and catalase (CAT), but decreased glutathione (GSH) levels in zebrafish embryos. The relative expressions of heart development-related genes (nkx2.5, nppa, gata4, and tbx2b), apoptosis-related genes (bcl2, p53, bax, and puma), and swim bladder development-related genes (foxA3, anxa5b, mnx1, and has2) were significantly altered by IFP exposure. Collectively, our results indicated that IFP induced developmental toxicity and neurotoxicity to zebrafish embryos and the mechanisms may be relevant to the activation of oxidative stress and reduction of acetylcholinesterase (AChE) content.

Developmental toxicity, immunotoxicity and cardiotoxicity induced by methidathion in early life stages of zebrafish.

Methidathion is a highly effective organophosphorus pesticide and is extensively utilized for the control of insects in agricultural production. However, there is little information on the adverse effects and underlying mechanisms of methidathion on aquatic organisms. In this work, embryonic zebrafish were exposed to methidathion at concentrations of 4, 10, and 25 mg/L for 96 h, and morphological changes and activities of antioxidant indicators alterations were detected. In addition, the locomotor behavioral abilities of zebrafish exposed to methidathion were also measured. To further explore the mechanism of the toxic effects of methidathion, gene expression levels associated with cardiac development, cell apoptosis, and the immune system were tested through qPCR assays. The findings revealed that methidathion exposure could induce a decrease in survival rate, hatchability, length of body, and increase in abnormality of zebrafish, as well as cardiac developmental toxicity. The LC50 value of methidathion in zebrafish embryos was determined to be about 30.72 mg/L at 96 hpf. Additionally, methidathion exposure triggered oxidative stress in zebrafish by increasing SOD activity, ROS, and MDA content. Acridine orange (AO) staining indicated that methidathion exposure led to apoptosis, which was mainly distributed in the pericardial region. Furthermore, significant impairments of locomotor activity in zebrafish larvae were induced by methidathion exposure. Lastly, the expression of pro-inflammatory factors including IFN-γ, IL-6, IL-8, CXCL-clc, TLR4, and MYD88 significantly up-regulated in exposed zebrafish. Taken together, the results in this work illustrated that methidathion caused developmental toxicity, cardiotoxicity, and immunotoxicity in embryogenetic zebrafish.

Lasso-Logistic regression model for the identification of serum biomarkers of neurotoxicity induced by strychnos alkaloids.

As a traditional Chinese medicine, strychnos alkaloids have wide effects including antitumor, analgesic, and anti-inflammatory. However, the therapeutic window of strychnos alkaloids is quite narrow due to potential neurotoxicity. Therefore, it is necessary to explore some efficient biomarkers to identify and predict the neurotoxicity induced by strychnos alkaloids and find a therapy to prevent the neurotoxicity of strychnos alkaloids. Based on the previous studies of our research team, 21 endogenous substances related to neurotoxicity were monitored in rats' serum with HPLC-MS/MS and ELISA. Starting from these fundamentals, a Lasso-Logistic regression model was used to select efficient biomarkers from 21 endogenous substances to predict brain injury and verify the neuroprotective effect of peonies. Under the processing of the Lasso-Logistic regression model, 12 biomarkers were identified from 21 endogenous substances to predict the neurotoxicity induced by strychnos alkaloids. At the same time, the neuroprotective effect of peonies was further confirmed by evaluating the level of 12 biomarkers. The results indicated that the development of the Lasso-Logistic regression model would provide a new, simple and efficient method for the prediction and diagnosis of the neurotoxicity induced by strychnos alkaloids.

Paracandidimonas lactea sp. nov., a urea-utilizing bacterium isolated from landfill.

A urea-utilizing bacterium, designated Q2-2 T, was isolated from landfill. Cells of strain Q2-2 T were Gram stain-negative, aerobic, short-rod bacteria. Strain Q2-2 T was observed to grow at a temperature range of 15-37℃ (optimum 30 â„ƒ), a pH range of 5.5-9.5 (optimum pH 8.0) and 0-4% (w/v) NaCl (optimum 1%). The major respiratory quinone was Q-8, and the major polar lipids were diphosphatidyl glycerol, phosphatidylethanolamine, phosphatidylmethylethanolamine, and phosphatidyl glycerol. Based on the 16S rRNA gene sequence, strain Q2-2 T had the highest similarity with Paracandidimonas caeni 24 T (98.0%), followed by Pusillimonas soli MJ07T (97.5%), Parapusillimonas granuli Ch07T (97.2%), Pusillimonas ginsengisoli DCY25T (97.1%) and Paracandidimonas soli IMT-305 T (96.4%). The ANI values between strain Q2-2 T and the above related type strains were 71.02%, 73.52%, 74.32%, 74.59% and 72.29%, respectively. The DNA G + C content of strain Q2-2 T was 61.1%. Therefore, strain Q2-2 T represents a novel species of the genus Paracandidimonas, for which the name Paracandidimonas lactea sp. nov. (type strain Q2-2 T = CGMCC 1.19179 T = JCM 34906 T) is proposed.

Anisodamine affects the pigmentation, mineral density, craniofacial area, and eye development in zebrafish embryos.

Anisodamine is one of the major components of the tropine alkaloid family and is widely used in the treatment of pain, motion sickness, pupil dilatation, and detoxification of organophosphorus poisoning. As a muscarinic receptor antagonist, the low toxicity and moderate drug effect of anisodamine often result in high doses for clinical use, making it important to fully investigate its toxicity. In this study, zebrafish embryos were exposed to 1.3-, 2.6-, and 5.2-mM anisodamine for 7 days to study the toxic effects of drug exposure on pigmentation, mineral density, craniofacial area, and eye development. The results showed that exposure to anisodamine at 1.3 mM resulted in cranial malformations and abnormal pigmentation in zebrafish embryos; 2.6- and 5.2-mM anisodamine resulted in significant eye development defects and reduced bone density in zebrafish embryos. The associated toxicities were correlated with functional development of neural crest cells through gene expression (col1a2, ddb1, dicer1, mab21l1, mab21l2, sox10, tyrp1b, and mitfa) in the dose of 5.2-mM exposed group. In conclusion, this study provides new evidence of the developmental toxicity of high doses of anisodamine in aqueous solutions to organisms and provides a warning for the safe use of this drug.

A surface plasmon resonance immunoassay for the rapid analysis of methamphetamine in forensic oral fluid.

BACKGROUND: Current chromatographic methods applied for the forensic analysis of methamphetamine are costly, time-consuming, and require complicated pretreatment procedures. Thus, the rapid detection of methamphetamine is a critical and unmet need. In this study, a surface plasmon resonance (SPR) system based on indirect inhibitive immunoassay was designed for the analysis of methamphetamine in forensic oral fluid samples. METHODS: For the inhibition immunoassay, the diluted oral fluid was mixed with methamphetamine antibody and then injected into the SPR sensor chip. The biosensor chip was constructed by covalently immobilizing of methamphetamine-bovine serum albumin conjugate onto a carboxymethyl dextran surface at an optimized pH. The concentration of antibody was also optimized. RESULTS: The SPR biosensor showed good sensitivity with a limit of detection of 0.44 ng/mL and was comparable or lower than the pre-existing methods. The method was finally tested using oral fluid samples from 20 suspected drug abusers in forensic cases, and it provided an acceptable recovery of 113.2%, indicating good anti-interference capability of the SPR sensor. CONCLUSION: The SPR biosensor was rapid, reproducible, and had a great potential approach for the forensic detection of methamphetamine.

Dummy-surface molecularly imprinted polymers as a sorbent of micro-solid-phase extraction combined with dispersive liquid-liquid microextraction for determination of five 2-phenylpropionic acid NSAIDs in aquatic environmental samples.

A highly binding dummy template surface of molecularly imprinted polymers (MWNTs-MIPs) was synthesized on multi-walled carbon nanotubes surface using 2-phenylpropionic acid as dummy template, 4-vinylpyridine as the functional monomer, ethylene glycol dimethacrylate as the cross-linker, and DMF as porogen by precipitation polymerization method. MIPs were characterized by FT-IR spectroscopy, scanning electron microscope, thermo-gravimetric analysis, and nitrogen adsorption-desorption experiment. Adsorption and selectivity experiments of MIPs and non-imprinted polymers (NIPs) verified that the MIPs had a good selectivity and adsorption properties for five 2-phenylpropionic acid nonsteroidal anti-inflammatory drugs (NSAIDs). Imprinted polymer was used as a sorbent material for µSPE in current work and µSPE-DLLME method was selected for pretreatment of water samples. The µSPE-DLLME method was successfully used for the pre-concentration of five non-steroidal anti-inflammatory drugs in different environmental water samples prior to ultra-high performance liquid chromatography-tandem mass spectrometry. Efficiencies of µSPE and DLLME were thoroughly investigated and optimized in this study. The optimal results were obtained by using 3 mL of 1% formic acid-acetonitrile as elution solvent and dichloroethane and acetonitrile as extractant and disperser solvent, respectively. Limits of detection and quantification of five NSAIDs for different water matrices varied from 0.50 to 1.10 ng L-1 and 0.93 to 2.20 ng L-1, respectively. Each target analyte had a good linearity in its corresponding concentration range. Enrichment factors of target analytes ranged from 91 to 215. Recoveries of the target analytes were between 72.43 and 113.99% at the concentration levels of 0.02, 0.1, and 0.5 µg L-1. The developed method was successfully applied to extraction and analysis of NSAIDs in different water samples with satisfactory results which could help us better understand their environmental fate and risk to ecological health. Graphical abstract Dummy-surface molecularly imprinted polymers as a sorbent of micro-solid-phase extraction combined with dispersive liquid-liquid microextraction for determination of five 2-phenylpropionic acid NSAIDs in aquatic environmental samples.

Comparative pharmacokinetics study of anastrozole after single administration and combination with celecoxib.

1. There are numerous investigations demonstrating that the cyclooxygenase-2 (COX-2) inhibitors might enhance the efficiency of anastrozole in breast cancer. Hence, this study was conducted to investigate the comparative pharmacokinetics of anastrozole after single administration and combination with celecoxib. 2. A simple protein precipitation procedure was adopted for the sample preparation with satisfactory extraction recovery for both anastrozole and the internal standard, and then anastrozole was separated and analysed on an ACQUITY BEH UPLC C18 column (50 × 2.0 mm, 1.7 µm, Waters) within 2 min. The calibration curves showed good linarites (r = 0.994). Intra- and inter-day precision were within 4.93 and 13.83%, respectively. The mean extraction recoveries across QC levels were within 91.4%, and the matrix effects were within 94.5%. 3. Results showed that the method was reliable to determine anastrozole in rat plasma. Compared with rats in single administration group, no significant difference was found in the combination group. It is workable to use celecoxib combined with anastrozole in clinical therapy.

Comparative pharmacokinetics of (S)-MP3950, a novel 5-HT4 receptor agonist, in normal and atropine-induced gastrointestinal motility disorders rats.

1. (S)-MP3950 is the (S)-enantiomer of active metabolite of mosapride, which exhibits higher 5-HT4 receptor agonistic effect than mosapride. It shows promise to become a novel drug candidate for the treatment of gastrointestinal motility disorders (GMDs). However, the pharmacokinetic behavior of (S)-MP3950 in the pathological state of GMDs remains unclear. Herein, we investigated the comparative pharmacokinetics of (S)-MP3950 in normal and GMDs rats. 2. The comparative pharmacokinetics of (S)-MP3950 in normal and atropine-induced GMD rats were studied by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The validated UPLC-MS/MS method was successfully applied to investigate the pharmacokinetic profiles of (S)-MP3950 in normal and atropine-induced GMDs rats. Results showed that comparing to normal rats, Cmax reduced by 73.8%, AUC0-t decreased by 57.6% and AUC0-∞ declined by 56.8% in model rats. Additionally, the elimination half-life (t1/2) and Tmax were prolonged slightly. 3. The pharmacokinetic results demonstrated that the atropine-induced GMDs reduced the absorption of (S)-MP3950. The pharmacokinetics research in the pathological state might provide more useful information for further study of novel gastric motility candidates.

Identification of chemical components in Baidianling Capsule based on gas chromatography-mass spectrometry and high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry.

Baidianling Capsule, which is made from 16 Chinese herbs, has been widely used for treating vitiligo clinically. In this study, the sensitive and rapid method has been developed for the analysis of chemical components in Baidianling Capsule by gas chromatography-mass spectrometry in combination with retention indices and high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry. Firstly, a total of 110 potential volatile compounds obtained from different extraction procedures including alkanes, alkenes, alkynes, ketones, ethers, aldehydes, alcohols, phenols, organic acids, esters, furans, pyrrole, acid amides, heterocycles, and oxides were detected from Baidianling Capsule by gas chromatography-mass spectrometry, of which 75 were identified by mass spectrometry in combination with the retention index. Then, a total of 124 components were tentatively identified by high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry. Fifteen constituents from Baidianling Capsule were accurately identified by comparing the retention times with those of reference compounds, others were identified by comparing the retention times and mass spectrometry data, as well as retrieving the reference literature. This study provides a practical strategy for rapidly screening and identifying the multiple constituents of a complex traditional Chinese medicine.

DSSGNN-PPI: A Protein-Protein Interactions prediction model based on Double Structure and Sequence graph neural networks.

The process of experimentally confirming complex interaction networks among proteins is time-consuming and laborious. This study aims to address Protein-Protein Interactions (PPIs) prediction based on graph neural networks (GNN). A novel multilevel prediction model for PPIs named DSSGNN-PPI (Double Structure and Sequence GNN for PPIs) is designed. Initially, a distance graph between amino acid residues is constructed. Subsequently, the distance graph is fed into an underlying graph attention network module. This enables us to efficiently learn vector representations that encode the three-dimensional structure of proteins and simultaneously aggregate key local patterns and overall topological information to obtain graph embedding that adequately represent local and global structural features. In addition, the embedding representations that reflect sequence properties are obtained. Two features are fused to construct high-level protein complex networks, which are fed into the designed gated graph attention network to extract complex topological patterns. By combining heterogeneous multi-source information from downstream structure graph and upstream sequence models, the understanding of PPIs is comprehensively enhanced. A series of evaluation results validate the remarkable effectiveness of DSSGNN-PPI framework in enhancing the prediction of multi-type interactions among proteins. The multilevel representation learning and information fusion strategies provide a new effective solution paradigm for structural biology problems. The source code for DSSGNN-PPI has been hosted on GitHub and is available at https://github.com/cstudy1/DSSGNN-PPI.

Application research of radiomics in colorectal cancer: A bibliometric study.

BACKGROUND: Radiomics has shown great potential in the clinical field of colorectal cancer (CRC). However, few bibliometric studies have systematically analyzed existing research in this field. The purpose of this study is to understand the current research status and future development directions of CRC. METHODS: Search the English documents on the application of radiomics in the field of CRC research included in the Web of Science Core Collection from its establishment to October 2023. VOSviewer and CiteSpace software were used to conduct bibliometric and visual analysis of online publications related to countries/regions, authors, journals, references, and keywords in this field. RESULTS: A total of 735 relevant documents published from Web of Science Core Collection to October 2023 were retrieved, and a total of 419 documents were obtained based on the screening criteria, including 376 articles and 43 reviews. The number of publications is increasing year by year. Among them, China publishes the most relevant documents (n = 238), which is much higher than Italy (n = 69) and the United States (n = 63). Tian Jie is the author with the most publications and citations (n = 17, citations = 2128), GE Healthcare is the most productive institution (n = 26), Frontiers in Oncology is the journal with the most publications (n = 60), and European Radiology is the most cited journal (n = 776). Hot spots for the application of radiomics in CRC include magnetic resonance, neoadjuvant chemoradiotherapy, survival, texture analysis, and machine learning. These directions are the current hot spots for the application of radiomics research in CRC and may be the direction of continued development in the future. CONCLUSION: Through bibliometric analysis, the application of radiomics in CRC has been increasing year by year. The application of radiomics improves the accuracy of preoperative diagnosis, prediction, and prognosis of CRC. The results of bibliometrics analysis provide a valuable reference for the research direction of radiomics. However, radiomics still faces many challenges in the future, such as the single nature of the data source which may affect the comprehensiveness of the results. Future studies can further expand the data sources and build a multicenter public database to more comprehensively reflect the research status and development trend of CRC radiomics.

Endocrine disrupting effects of parabens in zebrafish (Danio rerio): New insights from transcriptomics, metabolomics, and molecular dynamics simulation.

Parabens (PBs), a group of widely used synthetic preservatives with potential endocrine disrupting activity, have been detected with increasing frequency in organisms and environmental matrices. This study assessed the hormone interference effects of four typical PBs, namely methylparaben (MeP), ethylparaben (EtP), propylparaben (PrP), and butylparaben (BuP), in zebrafish and elucidated the probable underlying mechanisms. Transcriptomic and metabolomic analyses showed that the differentially expressed genes and metabolites were associated with the tyrosine metabolism, arachidonate metabolism, and glycerophospholipid metabolism, indicating they were essential precursors of steroid hormone biosynthesis and metabolism. Histopathological analysis revealed impaired gonad development in the zebrafish exposed to PBs, as evidenced by the significantly increased vitellogenin (VTG) and estradiol (E2) levels. Furthermore, molecular dynamics simulation suggested that the four PBs could preferentially activate the zebrafish estrogen receptor, zfERß2, to regulate the downstream pathways. Disruption of the amino acid metabolism and lipid metabolism, and activation of zfERß2 signaling pathway were found to be the key mechanisms for the endocrine disrupting effects of PBs. The hormone interference effects of PBs were apparently dependent on the shared oxybenzene on their structures, with the degree of interference determined largely by the length of their alkyl chains. These findings provide new insights into the endocrine disrupting effects of PBs and could help better assess their risk to human health.

Comparative Evaluation of Machine Learning Models for Subtyping Triple-Negative Breast Cancer: A Deep Learning-Based Multi-Omics Data Integration Approach.

Objective: Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model based on the latest multi-omics data to enhance the accuracy of TNBC subtype and prognosis prediction. The study focuses on addressing the constraints of prior studies by showcasing a model with substantial advancements in data integration, statistical performance, and algorithmic optimization. Methods: Breast cancer-related molecular characteristic data, including mRNA, miRNA, gene mutations, DNA methylation, and magnetic resonance imaging (MRI) images, were retrieved from the TCGA and TCIA databases. This study not only compared single-omics with multi-omics machine learning models but also applied Bayesian optimization to innovatively optimize the neural network structure of a DL model for multi-omics data. Results: The DL model for multi-omics data significantly outperformed single-omics models in subtype prediction, achieving a 98.0% accuracy in cross-validation, 97.0% in the validation set, and 91.0% in an external test set. Additionally, the MRI radiomics model showed promising performance, especially with the training set; however, a decrease in performance during transfer testing underscored the advantages of the DL model for multi-omics data in data consistency and digital processing. Conclusion: Our multi-omics DL model presents notable innovations in statistical performance and transfer learning capability, bearing significant clinical relevance for TNBC classification and prognosis prediction. While the MRI radiomics model proved effective, it requires further optimization for cross-dataset application to enhance accuracy and consistency. Our findings offer new insights into improving TNBC classification and prognosis through multi-omics data and DL algorithms.

MCD-LightGBM System for Intelligent Analyzing Heterogeneous Clinical Drug Therapeutic Effects.

Causal effect estimation of individual heterogeneity is a core issue in the field of causal inference, and its application in medicine poses an active and challenging problem. In high-risk decision-making domain such as healthcare, inappropriate treatments can have serious negative impacts on patients. Recently, machine learning-based methods have been proposed to improve the accuracy of causal effect estimation results. However, many of these methods concentrate on estimating causal effects of continuous outcome variables under binary intervention conditions, and give less consideration to multivariate intervention conditions or discrete outcome variables, thus limiting their scope of application. To tackle this issue, we combine the double machine learning framework with Light Gradient Boosting Machine (LightGBM) and propose a double LightGBM model. This model can estimate binary causal effects more accurately and in less time. Two cyclic structures were added to the model. Data correction method was introduced and improved to transform discrete outcome variables into continuous outcome variables. Multivariate Cyclic Double LightGBM model (MCD-LightGBM) was proposed to intelligently estimate multivariate treatment effects. A visual human-computer interaction system for heterogeneous causal effect estimation was designed, which can be applied to different types of data. This paper reports that the system improved the Logarithm of the Minimum Angle of Resolution (LogMAR) of visual acuity change after Vascular Endothelial Growth Factor (anti-VEGF) treatment in patients with diabetic macular degeneration. The improvement was observed in two clinical problems, from 0.05 to 0.33, and the readmission rate of diabetic patients after cure was reduced from 48.4% to 10.5%. The results above demonstrate the potential of the proposed system in predicting heterogeneous clinical drug treatment effects.

Mulberry Leaf Dietary Supplementation Can Improve the Lipo-Nutritional Quality of Pork and Regulate Gut Microbiota in Pigs: A Comprehensive Multi-Omics Analysis.

Mulberry leaves, a common traditional Chinese medicine, represent a potential nutritional strategy to improve the fat profile, also known as the lipo-nutrition, of pork. However, the effects of mulberry leaves on pork lipo-nutrition and the microorganisms and metabolites in the porcine gut remain unclear. In this study, multi-omics analysis was employed in a Yuxi black pig animal model to explore the possible regulatory mechanism of mulberry leaves on pork quality. Sixty Yuxi black pigs were divided into two groups: the control group (n = 15) was fed a standard diet, and the experimental group (n = 45) was fed a diet supplemented with 8% mulberry leaves. Experiments were performed in three replicates (n = 15 per replicate); the two diets were ensured to be nutritionally balanced, and the feeding period was 120 days. The results showed that pigs receiving the diet supplemented with mulberry leaves had significantly reduced backfat thickness (p < 0.05) and increased intramuscular fat (IMF) content (p < 0.05) compared with pigs receiving the standard diet. Lipidomics analysis showed that mulberry leaves improved the lipid profile composition and increased the proportion of triglycerides (TGs). Interestingly, the IMF content was positively correlated with acyl C18:2 and negatively correlated with C18:1 of differential TGs. In addition, the cecal microbiological analysis showed that mulberry leaves could increase the abundance of bacteria such as UCG-005, Muribaculaceae_norank, Prevotellaceae_NK3B31_group, and Limosilactobacillus. Simultaneously, the relative levels of L-tyrosine-ethyl ester, oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, and mulberrin were increased. Furthermore, we found that mulberry leaf supplementation significantly increased the mRNA expression of lipoprotein lipase, fatty acid-binding protein 4, and peroxisome proliferators-activated receptor γ in muscle (p < 0.01). Mulberry leaf supplementation significantly increased the mRNA expression of diacylglycerol acyltransferase 1 (p < 0.05) while significantly decreasing the expression of acetyl CoA carboxylase in backfat (p < 0.05). Furthermore, mulberry leaf supplementation significantly upregulated the mRNA expression of hormone-sensitive triglyceride lipase and peroxisome proliferator-activated receptor α (p < 0.05) in backfat. In addition, mulberry leaf supplementation led to increased serum leptin and adiponectin (p < 0.01). Collectively, this omic profile is consistent with an increased ratio of IMF to backfat in the pig model.

Habitual Daily Intake of Fried Foods Raises Transgenerational Inheritance Risk of Heart Failure Through NOTCH1-Triggered Apoptosis.

Consumption of fried foods is highly prevalent in the Western dietary pattern. Western diet has been unfavorably linked with high risk of developing cardiovascular diseases. Heart failure (HF) as a cardiovascular disease subtype is a growing global pandemic with high morbidity and mortality. However, the causal relationship between long-term fried food consumption and incident HF remains unclear. Our population-based study revealed that frequent fried food consumption is strongly associated with 15% higher risk of HF. The causal relationship may be ascribed to the dietary acrylamide exposure in fried foods. Further cross-sectional study evidenced that acrylamide exposure is associated with an increased risk of HF. Furthermore, we discover and demonstrate that chronic acrylamide exposure may induce HF in zebrafish and mice. Mechanistically, we reveal that acrylamide induces energy metabolism disturbance in heart due to the mitochondria dysfunction and metabolic remodeling. Moreover, acrylamide exposure induces myocardial apoptosis via inhibiting NOTCH1-phosphatidylinositol 3-kinase/AKT signaling. In addition, acrylamide exposure could affect heart development during early life stage, and the adverse effect of acrylamide exposure is a threat for next generation via epigenetic change evoked by DNA methyltransferase 1 (DNMT1). In this study, we reveal the adverse effects and underlying mechanism of fried foods and acrylamide as a typical food processing contaminant on HF from population-based observations to experimental validation. Collectively, these results both epidemiologically and mechanistically provide strong evidence to unravel the mechanism of acrylamide-triggered HF and highlight the significance of reducing fried food consumption for lower the risk of HF.