Novel Circular RNA CircSLC2A13 Regulates Chicken Muscle Development by Sponging MiR-34a-3p.

The skeletal muscle is the major muscle tissue in animals, and its production is subject to a complex and strict regulation. The proliferation and differentiation of myoblasts are important factors determining chicken muscle development. Circular RNAs (circRNAs) are endogenous RNAs that are widely present in various tissues of organisms. Recent studies have shown that circRNA plays key roles in the development of skeletal muscles. The solute carrier (SLC) family functions in the transport of metabolites such as amino acids, glucose, nucleotides, and essential nutrients and is widely involved in various basic physiological metabolic processes within the body. In this study, we have cloned a novel chicken circular RNA circSLC2A13 generated from the solute carrier family 2 member 13 gene (SLC2A13). Also, circSLC2A1 was confirmed by sequencing verification, RNase R treatment, and reverse transcription analysis. Currently, our results show that circSLC2A13 promoted the proliferation and differentiation of chicken myoblasts. The double luciferase reporter system revealed that circSLC2A13 regulated the proliferation and differentiation of myoblasts by competitive binding with miR-34a-3p. In addition, results indicated that circSLC2A13 acts as a miR-34a-3p sponge to relieve its inhibitory effect on the target SMAD3 gene. In summary, this study found that chicken circSLC2A13 can bind to miR-34a-3p and weaken its inhibitory effect on the SMAD family member 3 gene (SMAD3), thereby promoting the proliferation and differentiation of myoblasts. This study laid foundations for broiler industry and muscle development research.

New application of intestinal obstruction catheter in enterocutaneous fistula: A case report.

BACKGROUND: Enterocutaneous fistula (ECF) is an abnormal connection between the gastrointestinal tract and the skin. ECF can lead to massive body fluid loss, hypercatabolism, and malnutrition. Therefore, nutritional support plays a crucial role in managing ECFs and promoting the healing of fistulas. For nutritional support, enteral nutrition (EN) is the preferred method when gastrointestinal function is recovering. Currently, various EN approaches have been applied for different anatomical positions of the ECF. However, the effectiveness of administering EN support for treating lower ECFs still needs further exploration and improvement. CASE SUMMARY: We present the case of a 46-year-old male who underwent gastrointestinal stromal tumour resection. Six days after the surgery, the patient presented with fever, fatigue, severe upper abdominal pain, and septic shock. Subsequently, lower ECFs were diagnosed through laboratory and imaging examinations. In addition to symptomatic treatment for homeostasis, total parenteral nutrition support was administered in the first 72 h due to dysfunction of the intestine. After that, we gradually provided EN support through the intestinal obstruction catheter in consideration of the specific anatomic position of the fistula instead of using the nasal jejunal tube. Ultimately, the patient could receive optimal EN support via the catheter, and no complications were found during the treatment. CONCLUSION: Nutritional support is a crucial element in ECF management, and intestinal obstruction catheters could be used for early EN administration.

MOTAI: A Novel Method for the Study of O-GalNAcylation and Complex O-Glycosylation in Cancer.

The Tn antigen, an immature truncated O-glycosylation, is a promising biomarker for cancer detection and diagnosis. However, reliable methods for analyzing O-GalNAcylation and complex O-glycosylation are lacking. Here, we develop a novel method, MOTAI, for the sequential analysis of O-glycosylation using different O-glycoproteases. MOTAI conjugates glycopeptides on a solid support and releases different types of O-glycosylation through sequential enzymatic digestion by O-glycoproteases, including OpeRATOR and IMPa. Because OpeRATOR has less activity on O-GalNAcylation, MOTAI enriches O-GalNAcylation for subsequent analysis. We demonstrate the effectiveness of MOTAI by analyzing fetuin O-glycosylation and Jurkat cell lines. We then apply MOTAI to analyze colorectal cancer and benign colorectal polyps. We identify 32 Tn/sTn-glycoproteins and 43 T/sT-glycoproteins that are significantly increased in tumor tissues. Gene Ontology analysis reveals that most of these proteins are ECM proteins involved in the adhesion process of the intercellular matrix. Additionally, the protein disulfide isomerase CRELD2 has a significant difference in Tn expression, and the abnormally glycosylated T345 and S349 O-glycosylation sites in cancer group samples may promote the secretion of CRELD2 and ultimately tumorigenesis through ECM reshaping. In summary, MOTAI provides a powerful new tool for the in-depth analysis of O-GalNAcylation and complex O-glycosylation. It also reveals the upregulation of Tn/sTn-glycoproteins in colorectal cancer, which may provide new insights into cancer biology and biomarker discovery.

Response of dissolved inorganic carbon dynamics to simulated tidal hydrological processes in coastal wetlands.

To clarify the impacts of tidal hydrological process shifts caused by sea level rise on the blue carbon cycle, a typical coastal wetland in Jiaozhou Bay was selected for this study. The soils of Suaeda salsa (SS) and Phragmites australis (PA) wetlands were collected to simulate the effects of three types of tidal hydrological processes (Neap tide group, NT; Middle tide group, MT; Spring tide group, ST) on the soil-water dissolved inorganic carbon (DIC) dynamic. The results showed that the concentration of water dissolved inorganic carbon (WDIC) increased rapidly (115% higher) at early stage (days 0-4) under the influence of the tidal hydrological processes. Significant differences were found in WDIC concentration during different tidal hydrological processes (P < 0.05), which were expressed as MT (52.7 ± 13.3 mg L-1) > ST (52.5 ± 12.9 mg L-1) > NT (48.4 ± 10.1 mg L-1). After experiencing the tidal hydrological processes, the soil DIC content showed a net accumulation (55.1 ± 1.29 mg L-1vs. 46.7 ± 1.76 mg L-1, P < 0.001), whereas the soil inorganic carbon (SIC) decreased (2.73 ± 1.64 mg L-1vs. 4.61 ± 1.71 mg L-1), which may be attributed to the dissolution of SIC caused by the uptake of CO2 to form DIC. The accumulation of soil DIC was directly related to the SIC (λ = 1.03, P < 0.01), and indirectly related to soil nutrients (SOC substrate, λ = -0.003) and microbes (microbial biomass, λ = -0.10), and was mainly dominated by abiotic processes (abiotic: 58.1 ± 1.8% to 82.7 ± 2.46% vs. biotic: 17.4 ± 2.46% to 41.9 ± 1.76%). The increase of tidal frequency generally inhibited the accumulation of soil DIC content and promoted the output of WDIC. However, the response of soil DIC in different wetland types to tidal frequency was divergent, which was mainly regulated by the trade-off between soil nutrients and SIC content. Taken together, tidal hydrological processes and their frequency changes reshaped DIC dynamics, promoted the dissolution of SIC and the potential uptake of CO2. These findings enhance the comprehension of the inorganic carbon cycle within coastal wetlands, particularly amidst the backdrop of climate change and the rising sea levels.

Preliminary investigation on the effect of Vibrio splendidus stimulation on the intestinal flora of Strongylocentrotus intermedius.

To better understand the effect of Vibrio splendidus infection on Strongylocentrotus intermedius, 16S rRNA sequencing was carried out to investigate the intestinal flora of S. intermedius stimulated by 0 CFU/mL (Con), 1.5 × 107 CFU/mL (Vib1) and 1.5 × 108 CFU/mL (Vib2) concentrations of V. splendidus. The results showed that there was significant difference in intestinal flora diversity between Con group and Vib1 group, but no significant difference between Con group and Vib2 group. However, there were significant differences in the composition of intestinal flora among all groups. Bacteroidota, Proteobacteria and Firmicutes were the dominant phylum in the Con group. The abundance of Bacteroidota and Firmicutes decreased and Proteobacteria increased in Vib1 and Vib2 groups. The relative abundance of the potential probiotic bacteria Muribaculaceae and Alloprevotella was significantly lower in the Vib1 and Vib2 groups. In addition, the opportunistic pathogen Desulfovibrio was found in Vib1 and Vib2 groups. It is evident that V. splendidus infection not only alters the composition of the microbial community in the intestinal tract of S. intermedius, but may also lead to the production of opportunistic pathogens, which could be potentially harmful to the health of S. intermedius. The results of this study provide a foundation for exploring the diseases caused by V. splendidus stimulation leading to an imbalance in the intestinal flora of S. intermedius, and contribute to our further understanding of the role of Vibrio on the health of S. intermedius.

Pantothenic Acid Alleviates Fat Deposition and Inflammation by Suppressing the JNK/P38 MAPK Signaling Pathway.

Excessive fat deposition leads to obesity and cardiovascular diseases with abnormal metabolism. Pantothenic acid (PA) is a major B vitamin required for energy metabolism. However, the effect of PA on lipid metabolism and obesity has not been explored. We investigated the effects and molecular mechanism of PA on fat accumulation as well as the influence of adipogenic marker genes in both adult male mice and primary adipocytes. First, we demonstrated that PA attenuates weight gain in mice fed high-fat diet (HFD). Besides, PA supplementation substantially improved glucose tolerance and lipid metabolic disorder in obese mice. Furthermore, PA significantly inhibited white adipose tissue (WAT) deposition as well as fat droplets visualized by magnification in both chow and HFD group. More importantly, PA obviously suppressed the mRNA levels of CD36, IL-6, and TNF-α to alleviate inflammation and reduced the levels of PPARγ, aP2, and C/EBPα genes that are related to lipid metabolism in inguinal white adipose tissue (ing-WAT) and epididymal white adipose tissue (ei-WAT). In vitro, PA supplementation showed a lower lipid droplet aggregation as well as reduced expression levels of adipogentic genes. Finally, we identified that PA inhibits the phosphorylation levels of p38 and JNK in murine primary adipocytes. Collectively, our data demonstrated for the first time that PA attenuates lipid metabolic disorder as well as fat deposition by JNK/p38 MAPK signaling pathway.

The p38/MAPK pathway as a therapeutic target to prevent therapeutic escape of breast cancer stem cells.

Cancer stem cells (CSCs) play an important role in metastasis development, tumor recurrence, and treatment resistance, and are essential for the eradication of cancer. Currently, therapies fail to eradicate CSCs due to their therapeutic stress-induced cellular escape, which leads to enhanced aggressive behaviors compared with CSCs that have never been treated. However, the underlying mechanisms regulating the therapeutic escape remain unknown. To this end, we established a model to isolate the therapeutic escaped CSCs (TSCSCs) from breast CSCs and performed the transcription profile to reveal the mechanism. Mechanistically, we demonstrated that the behavior of therapeutic escape was regulated through the p38/MAPK signaling pathway, resulting in TSCSCs exhibiting enhanced motility and metastasis. Notably, blocking the p38/MAPK signaling pathway effectively reduced motility and metastasis ability both in vitro and in vivo, which were further supported by downregulated motility-related genes and epithelial-mesenchymal transition (EMT)-related proteins vimentin and N-cadherin. The obtained findings reveal the p38/MAPK pathway as a potential therapeutic target for TSCSCs and would provide profound implications for cancer therapy.

SIVA-1 interaction with PCBP1 serves as a predictive biomarker for cisplatin sensitivity in gastric cancer and its inhibitory effect on tumor growth in vivo.

Background: SIVA-1 has been reported to play a key role in cell apoptosis and gastric cancer (GC) chemoresistance in vitro. Nevertheless, the clinical significance of SIVA-1 in GC chemotherapy remains unclear. Methods and results: Immunohistochemistry and histoculture drug response assays were used to determine SIVA-1 expression and the inhibition rate (IR) of agents to GC and to further analyze the relationship between these two phenomena. Additionally, cisplatin (DDP)-resistant GC cells were used to elucidate the role and mechanism of SIVA-1 in vivo. The results demonstrated that SIVA-1 expression was positively correlated with the IR of DDP to GC but not with those of 5-fluorouracil (5-FU) or adriamycin (ADM). Furthermore, SIVA-1 overexpression with DDP treatment synergistically inhibited tumor growth in vivo by increasing PCBP1 and decreasing Bcl-2 and Bcl-xL expression. Conclusions: Our study demonstrated that SIVA-1 may serve as an indicator of the GC sensitivity to DDP, and the mechanism of SIVA-1 in GC resistance to DDP was preliminarily revealed.

Molecular cloning and functional study of a Rel homologous gene in sea urchin Strongylocentrotus intermedius.

NF-κB (Nuclear factor-kappa B) family proteins are versatile transcription factors that play crucial regulatory roles in cell development, growth, apoptosis, inflammation, and immune response. However, there is limited research on the function of these key genes in echinoderms. In this study, an NF-κB family gene (SiRel) was identified in sea urchin Strongylocentrotus intermedius. The gene has an open reading frame length of 1809 bp and encodes for 602 amino acids. Domain prediction results revealed that the N-terminal of SiRel protein encodes a conserved Rel homology domain (RHD), including the RHD-DNA binding domain and the RHD-dimerization domain. Multiple sequence comparison results showed that the protein sequences of these two domains were conserved. Phylogenetic analysis indicated that SiRel clustered with Strongylocentrotus purpuratus p65 protein and Rel protein of other echinoderms. Results from quantitative real-time PCR demonstrated detectable SiRel mRNA expression in all tested sea urchin tissues, with the highest expression level found in the gills. And SiRel mRNA expression levels were significantly induced after LPS (Lipopolysaccharide) and poly(I:C) (Polyinosinic:polycytidylic acid) stimulation. In addition, SiRel protein expression can be found in cytoplasm and nucleus of HEK293T cells. Co-immunoprecipitation results showed that SiRel could interact with sea urchin IκB (Inhibitor of NF-κB) protein. Western blotting and dual-luciferase reporter gene assay results indicated that overexpression of SiRel in HEK293T cells could impact the phosphorylation levels of JNK (c-Jun N-terminal kinase) and Erk1/2 (Extracellular signal-regulated kinases1/2) and activate interleukin-6 (IL-6), activating protein 1 (AP-1), interferon (IFN)α/ß/γ, and signal transducer and activator of transcription 3 (STAT3) reporter genes in HEK293T cells. In conclusion, this study reveals that SiRel plays an important role in the innate immune response of sea urchins and enriches our understanding of comparative immunology theory.

Advances in Label-Free Glucose Detection Using Self-Assembled Nanoparticles and Surface-Enhanced Raman Spectroscopy.

In the landscape of biomolecular detection, surface-enhanced Raman spectroscopy (SERS) confronts notable obstacles, particularly in the label-free detection of biomolecules, with glucose and other sugars presenting a quintessential challenge. This study heralds the development of a pioneering SERS substrate, ingeniously engineered through the self-assembly of nanoparticles of diverse sizes (Ag1@Ag2NPs). This configuration strategically induces 'hot spots' within the interstices of nanoparticles, markedly amplifying the detection signal. Rigorous experimental investigations affirm the platform's rapidity, precision, and reproducibility, and the detection limit of this detection method is calculated to be 6.62 pM. Crucially, this methodology facilitates nondestructive glucose detection in simulated samples, including phosphate-buffered saline and urine. Integrating machine learning algorithms with simulated serum samples, the approach adeptly discriminates between hypoglycemic, normoglycemic, and hyperglycemic states. Moreover, the platform's versatility extends to the detection and differentiation of monosaccharides, disaccharides, and methylated glycosides, underscoring its universality and specificity. Comparative Raman spectroscopic analysis of various carbohydrate structures elucidates the unique SERS characteristics pertinent to these molecules. This research signifies a major advance in nonchemical, label-free glucose determination with enhanced sensitivity via SERS, laying a new foundation for its application in precision medicine and advancing structural analysis in the sugar domain.

Molluscan pleiotropic FADD involved in innate immune signaling and induces apoptosis.

Fas-associated protein with death domain (FADD) was initially identified as a crucial adaptor protein in the apoptotic pathway mediated by death receptor (DR). Subsequently, many studies have confirmed that FADD plays a vital role in innate immunity and inflammatory responses in animals. However, the function of this pleiotropic molecule in mollusk species has not been well explored. In this study, we successfully verified the gene sequence of FADD in the Zhikong scallop (Chlamys farreri) and designated it as CfFADD. The CfFADD protein contains a conserved death effector and death domains. Phylogenetic analysis showed that CfFADD is a novel addition to the molluscan FADD family with a close evolutionary relationship with molluscan FADD subfamily proteins. CfFADD mRNA expression in various scallop tissues was significantly induced by challenge with pathogen-associated molecular patterns (lipopolysaccharide, peptidoglycan, and poly(I:C)), suggesting its role in innate immunity in scallops. Co-immunoprecipitation showed that CfFADD interacted with the scallop DR (tumor necrosis factor receptor) and a signaling molecule involved in the Toll-like receptor pathway (interleukin-1 receptor-associated kinase), confirming that CfFADD may be involved in DR-mediated apoptosis and innate immune signaling pathways. Further studies showed that CfFADD interacted with CfCaspase-8 and activated caspase-3. HEK293T cells exhibited distinct apoptotic features after transfection with a CfFADD-expression plasmid, suggesting a functional DR-FADD-caspase apoptotic pathway in scallops. Overexpression of CfFADD led to a significant dose-dependent activation of interferon ß and nuclear factor-κB reporter genes, demonstrating the key role of CfFADD in innate immunity. In summary, our research has confirmed the critical roles of CfFADD in innate immunity and apoptosis and provides valuable information for developing comparative immunology theories.

Tensile-Strained Cu Penetration Electrode Boosts Asymmetric C-C Coupling for Ampere-Level CO2-to-C2+ Reduction in Acid.

The synthesis of multicarbon (C2+) products remains a substantial challenge in sustainable CO2 electroreduction owing to the need for sufficient current density and faradaic efficiency alongside carbon efficiency. Herein, we demonstrate ampere-level high-efficiency CO2 electroreduction to C2+ products in both neutral and strongly acidic (pH = 1) electrolytes using a hierarchical Cu hollow-fiber penetration electrode (HPE). High concentration of K+ could concurrently suppress hydrogen evolution reaction and facilitate C-C coupling, thereby promoting C2+ production in strong acid. By optimizing the K+ and H+ concentration and CO2 flow rate, a faradaic efficiency of 84.5% and a partial current density as high as 3.1 A cm-2 for C2+ products, alongside a single-pass carbon efficiency of 81.5% and stable electrolysis for 240 h were demonstrated in a strong acidic solution of H2SO4 and KCl (pH = 1). Experimental measurements and density functional theory simulations suggested that tensile-strained Cu HPE enhances the asymmetric C-C coupling to steer the selectivity and activity of C2+ products.

Convolutional neural network for automated tooth segmentation on intraoral scans.

BACKGROUND: Tooth segmentation on intraoral scanned (IOS) data is a prerequisite for clinical applications in digital workflows. Current state-of-the-art methods lack the robustness to handle variability in dental conditions. This study aims to propose and evaluate the performance of a convolutional neural network (CNN) model for automatic tooth segmentation on IOS images. METHODS: A dataset of 761 IOS images (380 upper jaws, 381 lower jaws) was acquired using an intraoral scanner. The inclusion criteria included a full set of permanent teeth, teeth with orthodontic brackets, and partially edentulous dentition. A multi-step 3D U-Net pipeline was designed for automated tooth segmentation on IOS images. The model's performance was assessed in terms of time and accuracy. Additionally, the model was deployed on an online cloud-based platform, where a separate subsample of 18 IOS images was used to test the clinical applicability of the model by comparing three modes of segmentation: automated artificial intelligence-driven (A-AI), refined (R-AI), and semi-automatic (SA) segmentation. RESULTS: The average time for automated segmentation was 31.7 ± 8.1 s per jaw. The CNN model achieved an Intersection over Union (IoU) score of 91%, with the full set of teeth achieving the highest performance and the partially edentulous group scoring the lowest. In terms of clinical applicability, SA took an average of 860.4 s per case, whereas R-AI showed a 2.6-fold decrease in time (328.5 s). Furthermore, R-AI offered higher performance and reliability compared to SA, regardless of the dentition group. CONCLUSIONS: The 3D U-Net pipeline was accurate, efficient, and consistent for automatic tooth segmentation on IOS images. The online cloud-based platform could serve as a viable alternative for IOS segmentation.

BFE-Net: bilateral fusion enhanced network for gastrointestinal polyp segmentation.

Accurate segmentation of polyp regions in gastrointestinal endoscopic images is pivotal for diagnosis and treatment. Despite advancements, challenges persist, like accurately segmenting small polyps and maintaining accuracy when polyps resemble surrounding tissues. Recent studies show the effectiveness of the pyramid vision transformer (PVT) in capturing global context, yet it may lack detailed information. Conversely, U-Net excels in semantic extraction. Hence, we propose the bilateral fusion enhanced network (BFE-Net) to address these challenges. Our model integrates U-Net and PVT features via a deep feature enhancement fusion module (FEF) and attention decoder module (AD). Experimental results demonstrate significant improvements, validating our model's effectiveness across various datasets and modalities, promising advancements in gastrointestinal polyp diagnosis and treatment.

A newly identified scallop MyD88 interacts with TLR and functions in innate immunity.

Myeloid differentiation factor-88 (MyD88) is a key adaptor of the toll-like receptor (TLR) signaling pathway and plays a crucial role in innate immune signal transduction in animals. However, the MyD88-mediated signal transduction mechanism in shellfish has not been well studied. In this study, a new MyD88 gene, CfMyD88-2, was identified in the Zhikong scallop, Chlamys farreri. The 1779 bp long open reading frame encodes 592 amino acids. The N-terminus of CfMyD88-2 contains a conserved death domain (DD), followed by a TIR (TLR/Interleukin-1 Receptor) domain. The results of the multi-sequence comparison showed that the TIR domain sequences were highly conserved. Phylogenetic analysis revealed that CfMyD88-2 was first associated with Mizuhopecten yessoensis MyD88-4 and Argopecten irradians MyD88-4. CfMyD88-2 mRNA was expressed in all scallop tissues, as detected by qRT-PCR, and the expression level was the highest in the mantle and hepatopancreas. In addition, CfMyD88-2 mRNA expression significantly increased after pathogen-associated molecular patterns (PAMPs, such as lipopolysaccharide, peptidoglycan, or polyinosinic-polycytidylic acid) stimulation. The results of the co-immunoprecipitation experiments in HEK293T cells showed that both CfMyD88-1 and CfMyD88-2 interacted with the TLR protein of scallops, suggesting the existence of more than one functional TLR-MyD88 signaling axis in scallops. Dual luciferase reporter gene assays indicated that the overexpressed CfMyD88-2 in HEK293T cells activated interferon (IFN) α, IFN-ß, IFN-γ, and NF-κB reporter genes, indicating that the protein has multiple functions. The results of the subcellular localization experiment uncovered that CfMyD88-2 was mainly localized in the cytoplasm of human cells. In summary, the novel identified CfMyD88-2 can respond to the challenge of PAMPs, participate in TLR immune signaling, and may activate downstream effector genes such as NF-κB gene. These research results will be useful in advancing the theory of innate immunity in invertebrates and provide a reference for the selection of disease-resistant scallops in the future.

Predictive models of Alzheimer's disease dementia risk in older adults with mild cognitive impairment: a systematic review and critical appraisal.

BACKGROUND: Mild cognitive impairment has received widespread attention as a high-risk population for Alzheimer's disease, and many studies have developed or validated predictive models to assess it. However, the performance of the model development remains unknown. OBJECTIVE: The objective of this review was to provide an overview of prediction models for the risk of Alzheimer's disease dementia in older adults with mild cognitive impairment. METHOD: PubMed, EMBASE, Web of Science, and MEDLINE were systematically searched up to October 19, 2023. We included cohort studies in which risk prediction models for Alzheimer's disease dementia in older adults with mild cognitive impairment were developed or validated. The Predictive Model Risk of Bias Assessment Tool (PROBAST) was employed to assess model bias and applicability. Random-effects models combined model AUCs and calculated (approximate) 95% prediction intervals for estimations. Heterogeneity across studies was evaluated using the I2 statistic, and subgroup analyses were conducted to investigate sources of heterogeneity. Additionally, funnel plot analysis was utilized to identify publication bias. RESULTS: The analysis included 16 studies involving 9290 participants. Frequency analysis of predictors showed that 14 appeared at least twice and more, with age, functional activities questionnaire, and Mini-mental State Examination scores of cognitive functioning being the most common predictors. From the studies, only two models were externally validated. Eleven studies ultimately used machine learning, and four used traditional modelling methods. However, we found that in many of the studies, there were problems with insufficient sample sizes, missing important methodological information, lack of model presentation, and all of the models were rated as having a high or unclear risk of bias. The average AUC of the 15 best-developed predictive models was 0.87 (95% CI: 0.83, 0.90). DISCUSSION: Most published predictive modelling studies are deficient in rigour, resulting in a high risk of bias. Upcoming research should concentrate on enhancing methodological rigour and conducting external validation of models predicting Alzheimer's disease dementia. We also emphasize the importance of following the scientific method and transparent reporting to improve the accuracy, generalizability and reproducibility of study results. REGISTRATION: This systematic review was registered in PROSPERO (Registration ID: CRD42023468780).

Inflammatory proteins may mediate the causal relationship between gut microbiota and inflammatory bowel disease: A mediation and multivariable Mendelian randomization study.

This research investigates the causal relationships among gut microbiota, inflammatory proteins, and inflammatory bowel disease (IBD), including crohn disease (CD) and ulcerative colitis (UC), and identifies the role of inflammatory proteins as potential mediators. Our study analyzed gut microbiome data from 13,266 samples collected by the MiBioGen alliance, along with inflammatory protein data from recent research by Zhao et al, and genetic data on CD and UC from the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC). We used Mendelian randomization (MR) to explore the associations, complemented by replication, meta-analysis, and multivariable MR techniques for enhanced accuracy and robustness. Our analysis employed several statistical methods, including inverse-variance weighting, MR-Egger, and the weighted median method, ensuring comprehensive and precise evaluation. After MR analysis, replication and meta-analysis, we revealed significant associations between 11 types of gut microbiota and 17 inflammatory proteins were associated with CD and UC. Mediator MR analysis and multivariable MR analysis showed that in CD, the CD40L receptor mediated the causal effect of Defluviitaleaceae UCG-011 on CD (mediation ratio 8.3%), and the Hepatocyte growth factor mediated the causal effect of Odoribacter on CD (mediation ratio 18%). In UC, the C-C motif chemokine 4 mediated the causal effect of Ruminococcus2 on UC (mediation ratio 4%). This research demonstrates the interactions between specific gut microbiota, inflammatory proteins, and CD and UC. Furthermore, the CD40L receptor may mediate the relationship between Defluviitaleaceae UCG-011 and CD; the Hepatocyte growth factor may mediate the relationship between Odoribacter and CD; and the C-C motif chemokine 4 may mediate the relationship between Ruminococcus2 and UC. The identified associations and mediation effects offer insights into potential therapeutic approaches targeting the gut microbiome for managing CD and UC.

Changes of microbial communities and metabolites in the fermentation of persimmon vinegar by bioaugmentation fermentation.

To evaluate the effects of bioaugmentation fermentation inoculated with one ester-producing strain (Wickerhamomyces anomalus ZX-1) and two strains of lactic acid bacteria (Lactobacillus plantarum CGMCC 24035 and Lactobacillus acidophilus R2) for improving the flavor of persimmon vinegar, microbial community, flavor compounds and metabolites were analyzed. The results of microbial diversity analysis showed that bioaugmentation fermentation significantly increased the abundance of Lactobacillus, Saccharomyces, Pichia and Wickerhamomyces, while the abundance of Acetobacter, Apiotrichum, Delftia, Komagataeibacter, Kregervanrija and Aspergillus significantly decreased. After bioaugmentation fermentation, the taste was softer, and the sensory irritancy of acetic acid was significantly reduced. The analysis of HS-SPME-GC-MS and untargeted metabolomics based on LC-MS/MS showed that the contents of citric acid, lactic acid, malic acid, ethyl lactate, methyl acetate, isocitrate, acetoin and 2,3-butanediol were significantly increased. By multivariate analysis, 33 differential metabolites were screened out to construct the correlation between the differential metabolites and microorganisms. Pearson correlation analysis showed that methyl acetate, ethyl lactate, betaine, aconitic acid, acetoin, 2,3-butanediol and isocitrate positively associated with Wickerhamomyces and Lactobacillus. The results confirmed that the quality of persimmon vinegar was improved by bioaugmentation fermentation.

Surface-Enhanced Raman Scattering Imaging Assisted by Machine Learning Analysis: Unveiling Pesticide Molecule Permeation in Crop Tissues.

Surface-enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate preparation that enhances Raman signal strength on a global scale. To systematically solve these problems, artificial intelligence techniques are applied to analyze the signals of pesticides based on 3D and dynamic SERS imaging. Utilizing perovskite/silver nanoparticles composites (CaTiO3/Ag@BONPs) as enhanced substrates, enabling it not only to cleanse pesticide residues from the surface to pulp of fruits and vegetables, but also to investigate the penetration dynamics of an array of pesticides (chlorpyrifos, thiabendazole, thiram, and acetamiprid). The findings challenge existing paradigms, unveiling a previously unnoticed weakening process during pesticide invasion and revealing the surprising permeability of non-systemic pesticides. Of particular note is easy to overlook that the combined application of pesticides can inadvertently intensify their invasive capacity due to pesticide interactions. The innovative study delves into the realm of pesticide penetration, propelling a paradigm shift in the understanding of food safety. Meanwhile, this strategy provides strong support for the cutting-edge application of SERS imaging technology and also brings valuable reference and enlightenment for researchers in related fields.

Neural Network Classification Algorithm Based on Self-attention Mechanism and Ensemble Learning for MASLD Ultrasound Images.

BACKGROUND: Ultrasound image examination has become the preferred choice for diagnosing metabolic dysfunction-associated steatotic liver disease (MASLD) due to its non-invasive nature. Computer-aided diagnosis (CAD) technology can assist doctors in avoiding deviations in the detection and classification of MASLD. METHOD: We propose a hybrid model that integrates the pre-trained VGG16 network with an attention mechanism and a stacking ensemble learning model, which is capable of multi-scale feature aggregation based on the self-attention mechanism and multi-classification model fusion (Logistic regression, random forest, support vector machine) based on stacking ensemble learning. The proposed hybrid method achieves four classifications of normal, mild, moderate, and severe fatty liver based on ultrasound images. RESULT AND CONCLUSION: Our proposed hybrid model reaches an accuracy of 91.34% and exhibits superior robustness against interference, which is better than traditional neural network algorithms. Experimental results show that, compared with the pre-trained VGG16 model, adding the self-attention mechanism improves the accuracy by 3.02%. Using the stacking ensemble learning model as a classifier further increases the accuracy to 91.34%, exceeding any single classifier such as LR (89.86%) and SVM (90.34%) and RF (90.73%). The proposed hybrid method can effectively improve the efficiency and accuracy of MASLD ultrasound image detection.