N-type semiconducting hydrogel.

Hydrogels are an attractive category of biointerfacing materials with adjustable mechanical properties, diverse biochemical functions, and good ionic conductivity. Despite these advantages, their application in electronics has been restricted because of their lack of semiconducting properties, and they have traditionally only served as insulators or conductors. We developed single- and multiple-network hydrogels based on a water-soluble n-type semiconducting polymer, endowing conventional hydrogels with semiconducting capabilities. These hydrogels show good electron mobilities and high on/off ratios, enabling the fabrication of complementary logic circuits and signal amplifiers with low power consumption and high gains. We demonstrate that hydrogel electronics with good bioadhesive and biocompatible interface can sense and amplify electrophysiological signals with enhanced signal-to-noise ratios.

A novel multidisciplinary machine learning approach based on clinical, imaging, colonoscopy, and pathology features for distinguishing intestinal tuberculosis from Crohn's disease.

OBJECTIVES: Differentiating intestinal tuberculosis (ITB) from Crohn's disease (CD) remains a diagnostic dilemma. Misdiagnosis carries potential grave implications. We aim to establish a multidisciplinary-based model using machine learning approach for distinguishing ITB from CD. METHODS: Eighty-two patients including 25 patients with ITB and 57 patients with CD were retrospectively recruited (54 in training cohort and 28 in testing cohort). The region of interest (ROI) for the lesion was delineated on magnetic resonance enterography (MRE) and colonoscopy images. Radiomic features were extracted by least absolute shrinkage and selection operator regression. Pathological feature was extracted automatically by deep-learning method. Clinical features were filtered by logistic regression analysis. Diagnostic performance was evaluated by receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Delong's test was applied to compare the efficiency between the multidisciplinary-based model and the other four single-disciplinary-based models. RESULTS: The radiomics model based on MRE features yielded an AUC of 0.87 (95% confidence interval [CI] 0.68-0.96) on the test data set, which was similar to the clinical model (AUC, 0.90 [95% CI 0.71-0.98]) and higher than the colonoscopy radiomics model (AUC, 0.68 [95% CI 0.48-0.84]) and pathology deep-learning model (AUC, 0.70 [95% CI 0.49-0.85]). Multidisciplinary model, integrating 3 clinical, 21 MRE radiomic, 5 colonoscopy radiomic, and 4 pathology deep-learning features, could significantly improve the diagnostic performance (AUC of 0.94, 95% CI 0.78-1.00) on the bases of single-disciplinary-based models. DCA confirmed the clinical utility. CONCLUSIONS: Multidisciplinary-based model integrating clinical, MRE, colonoscopy, and pathology features was useful in distinguishing ITB from CD.

Photo-Stimulated Zn-based Batteries: Progress, Challenges, and Perspectives.

Solar energy, as a renewable energy source, dominates the vast majority of human energy, which can be harvested and converted by photovoltaic solar cells. However, the intermittent availability of solar energy restricts the actual utilization circumstances of solar cells. Integrating photo-responsive electrodes into an energy storage device emerges as a dependable and executable strategy, fostering the creation of photo-stimulated batteries that seamlessly amalgamate the process of solar energy collection, conversion, and storage in one system. Endowed by virtues such as cost-effectiveness, facile manufacturing, safety, and environmental friendliness, photo-stimulated Zn-based batteries have attracted considerable attention. The progress report furnishes a brief overview, summarizing various photo-stimulated Zn-based batteries. Their configurations, operational principles, advancements, and the intricate engineering of photoelectrode designs are introduced, respectively. Through rigorous architectural design, photo-stimulated Zn-based batteries exhibit the ability to initiate charging by saving electricity usage, and in certain instances, even without the need for external electrical grids under illumination. Furthermore, the compensation of solar energy can be explored to improve the output electric energy. At last, opportunities and challenges toward photo-stimulated Zn-based batteries in the process of development are proposed and discussed in the hope of expanding their application scenarios and accelerating the commercialization progress.

Molecular authentication of commercial "Qian-hu" through the integration of nrDNA internal transcribed spacer 2 and nucleotide signature.

BACKGROUND: Peucedani Radix, also known as "Qian-hu" is a traditional Chinese medicine derived from Peucedanum praeruptorum Dunn. It is widely utilized for treating wind-heat colds and coughs accompanied by excessive phlegm. However, due to morphological similarities, limited resources, and heightened market demand, numerous substitutes and adulterants of Peucedani Radix have emerged within the herbal medicine market. Moreover, Peucedani Radix is typically dried and sliced for sale, rendering traditional identification methods challenging. MATERIALS AND METHODS: We initially examined and compared 104 commercial "Qian-hu" samples from various Chinese medicinal markets and 44 species representing genuine, adulterants or substitutes, utilizing the mini barcode ITS2 region to elucidate the botanical origins of the commercial "Qian-hu". The nucleotide signature specific to Peucedani Radix was subsequently developed by analyzing the polymorphic sites within the aligned ITS2 sequences. RESULTS: The results demonstrated a success rate of 100% and 93.3% for DNA extraction and PCR amplification, respectively. Forty-five samples were authentic "Qian-hu", while the remaining samples were all adulterants, originating from nine distinct species. Peucedani Radix, its substitutes, and adulterants were successfully identified based on the neighbor-joining tree. The 24-bp nucleotide signature (5'-ATTGTCGTACGAATCCTCGTCGTC-3') revealed distinct differences between Peucedani Radix and its common substitutes and adulterants. The newly designed specific primers (PR-F/PR-R) can amplify the nucleotide signature region from commercial samples and processed materials with severe DNA degradation. CONCLUSIONS: We advocate for the utilization of ITS2 and nucleotide signature for the rapid and precise identification of herbal medicines and their adulterants to regulate the Chinese herbal medicine industry.

Hyperspectral imaging combined with GA-SVM for maize variety identification.

The demand for identification of maize varieties has increased dramatically due to the phenomenon of mixed seeds and inferior varieties pretending to be high-quality varieties continuing to occur. It is urgent to solve the problem of efficient and accurate identification of maize varieties. A hyperspectral image acquisition system was used to acquire images of maize seeds. Regions of interest (ROI) with an embryo size of 10 × 10 pixel were extracted, and the average spectral information in the range of 949.43-1709.49 nm was intercepted for the subsequent study in order to eliminate random noise at both ends. Savitzky-Golay (SG) smoothing algorithm and multiple scattering correction (MSC) were used to pretreat the full-band spectrum. The feature wavelengths were screened by successive projection algorithms (SPA), competitive adaptive reweighted sampling (CARS) single screening, and two combinations of CARS-SPA and CARS + SPA, respectively. Support vector machines (SVMs) and models optimized based on genetic algorithm (GA), particle swarm optimization (PSO) were established by using full bands (FB) and feature bands as the model input. The results showed that the MSC-(CARS-SPA)-GA-SVM model had the best performance with 93.00% of the test set accuracy, 8 feature variables, and a running time of 24.45 s. MSC pretreatment can effectively eliminate the scattering effect of spectral data, and the feature wavelengths extracted by CARS-SPA can represent all wavelength information. The study proved that hyperspectral imaging combined with GA-SVM can realize the identification of maize varieties, which provided a theoretical basis for maize variety classification and authenticity identification.

SMS2, a Novel Allele of OsINV3, Regulates Grain Size in Rice.

Grain size has an important effect on rice yield. Although several key genes that regulate seed size have been reported in rice, their molecular mechanisms remain unclear. In this study, a rice small grain size 2 (sms2) mutant was identified, and MutMap resequencing analysis results showed that a 2 bp insertion in the second exon of the LOC_Os02g01590 gene resulted in a grain length and width lower than those of the wild-type Teqing (TQ). We found that SMS2 encoded vacuolar acid invertase, a novel allele of OsINV3, which regulates grain size. GO and KEGG enrichment analyses showed that SMS2 was involved in endoplasmic reticulum protein synthesis, cysteine and methionine metabolism, and propionic acid metabolism, thereby regulating grain size. An analysis of sugar content in young panicles showed that SMS2 reduced sucrose, fructose, and starch contents, thus regulating grain size. A haplotype analysis showed that Hap2 of SMS2 had a longer grain and was widely present in indica rice varieties. Our results provide a new theoretical basis for the molecular and physiological mechanisms by which SMS2 regulates grain size.

A potent new-scaffold androgen receptor antagonist discovered on the basis of a MIEC-SVM model.

Prostate cancer (PCa) is the second most prevalent malignancy among men worldwide. The aberrant activation of androgen receptor (AR) signaling has been recognized as a crucial oncogenic driver for PCa and AR antagonists are widely used in PCa therapy. To develop novel AR antagonist, a machine-learning MIEC-SVM model was established for the virtual screening and 51 candidates were selected and submitted for bioactivity evaluation. To our surprise, a new-scaffold AR antagonist C2 with comparable bioactivity with Enz was identified at the initial round of screening. C2 showed pronounced inhibition on the transcriptional function (IC50 = 0.63 µM) and nuclear translocation of AR and significant antiproliferative and antimetastatic activity on PCa cell line of LNCaP. In addition, C2 exhibited a stronger ability to block the cell cycle of LNCaP than Enz at lower dose and superior AR specificity. Our study highlights the success of MIEC-SVM in discovering AR antagonists, and compound C2 presents a promising new scaffold for the development of AR-targeted therapeutics.

The beta pore-forming bacterial pesticidal protein Tpp78Aa1 is toxic to the Asian citrus psyllid vector of the citrus greening bacterium.

The Asian citrus psyllid (ACP) Diaphorina citri transmits the causative agent of huanglongbing, or citrus greening disease, that has decimated global citrus production. Pesticidal proteins derived from bacteria such as Bacillus thuringiensis (Bt) can provide effective and environmentally friendly alternatives for management of D. citri, but few with sufficient toxicity to D. citri have been identified. Here, we report on the toxicity of 14 Bt-derived pesticidal proteins from five different structural groups against D. citri. These proteins were selected based on previously reported toxicity to other hemipteran species and on pesticidal protein availability. Most of the proteins were expressed in Escherichia coli and purified from inclusion bodies or His-tag affinity purification, while App6Aa2 was expressed in Bt and purified from spore/crystal mixtures. Pesticidal proteins were initially screened by feeding psyllids on a single dose, and lethal concentration (LC50) then determined for proteins with significantly greater mortality than the buffer control. The impact of CLas infection of D. citri on toxicity was assessed for selected proteins via topical feeding. The Bt protein Tpp78Aa1 was toxic to D. citri adults with an LC50 of approximately 204 µg/mL. Nymphs were more susceptible to Tpp78Aa1 than adults but no significant difference in susceptibility was observed between healthy and CLas-infected nymphs or adults. Tpp78Aa1 and other reported D. citri-active proteins may provide valuable tools for suppression of D. citri populations.

Deciphering metabolic heterogeneity in retinoblastoma unravels the role of monocarboxylate transporter 1 in tumor progression.

BACKGROUND: Tumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited. METHODS: The metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion. RESULTS: Distinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications. CONCLUSIONS: This study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.

Ultrasensitive SERS aptasensor using Au@Ag bimetallic nanorod SERS tags for the selective detection of amantadine in foods.

Herein, a novel surface enhanced Raman spectroscopy (SERS) aptasensor was developed for amantadine (AMD) detection, based on magnetite nanoparticles coated with polyethylenimine, silver nanoclusters and aptamers (Fe3O4@PEI@AgNC-apt) as the capture probe and complementary DNA-modified gold nanorods (AuNRs@4-MPBA@Ag-c-DNA containing 4-mercaptophenylboric acid molecules) as the reporter probe. In the presence of AMD, the AMD and the reporter probe competed for the aptamer on the surface of the capture probe, resulting in the reporter probe detaching from the capture probe leading to a decrease in intensity of the SERS signal at 1067 cm-1 for 4-MPBA. Under optimal conditions, a good linear relationship was established between the SERS intensity at 1067 cm-1 and the logarithm of the AMD concentration over the range 10-6-102 mg L-1, with a LOD of 0.50 × 10-6 mg L-1. The AMD levels in spiked samples were evaluated using the SERS aptasensor, with good recoveries ranging from 90.57% to 113.49% being obtained.

Circumscription of the East Asia clade (Apiaceae subfamily Apioideae) and the taxonomic placements of several problematic genera.

The East Asia (or Physospermopsis) clade was recognized in previous molecular phylogenetic investigations into the higher-level relationships of Apiaceae subfamily Apioideae. The composition of this clade, the phylogenetic relationships among its constituent taxa, and the placement of species previously determined to be problematic have yet to be resolved. Herein, nrDNA ITS sequences were obtained for 150 accessions of Apioideae, representing species whose distributions are in East Asia or genera having one or more species included within the East Asia clade. These data, along with published ITS sequences from other Apioideae (for 3678 accessions altogether), were subjected to maximum likelihood and Bayesian inference analyses. The results show that the East Asia clade contains representatives of 11 currently recognized genera: Hansenia, Hymenolaena, Keraymonia, Sinolimprichtia, Acronema, Hymenidium, Physospermopsis, Pimpinella, Sinocarum, Tongoloa, and Trachydium. However, the latter seven genera have members falling outside of the East Asia clade, including the generic types of all except Tongoloa. Within the clade, the species comprising these seven genera are widely intermingled, greatly increasing confusion among relationships than previously realized. The problematic species Physospermopsis cuneata is confirmed as falling within the East Asia clade, whereas P. rubrinervis allies with the generic type in tribe Pleurospermeae. Physospermopsis kingdon-wardii is confirmed as a member of the genus Physospermopsis, whereas the generic attributions of P. cuneata and Tongoloa stewardii remain unclear. Two species of Sinocarum (S. filicinum and S. wolffianum) are transferred into the genus Meeboldia. This is the most comprehensive molecular phylogenetic investigation of the East Asia clade to date, and while the results increase systematic understanding of the clade, they also highlight the need for further studies of one of the most taxonomically intractable groups in Apioideae.

Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma.

BACKGROUND: Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response. METHODS: We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R-CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes. RESULTS: 200 glioma patients (mean age, 33 years ± 19 [standard deviation]) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas. CONCLUSIONS: These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.

Structural and aggregation changes of silver carp myosin induced with alcohols: Effects of ethanol, 1,2-propanediol, and glycerol.

This study investigated the effects of ethanol, 1,2-propanediol, and glycerol on the structure and aggregation behavior of silver carp (Hypophthalmichthys molitrix) myosin. All alcohols induced extensive alteration in the tertiary structure of myosin. Both ethanol and 1,2-propanediol further promoted an increase in the content of ß-sheets in myosin and induced myosin aggregation. While glycerol had almost no impact on the secondary structure of myosin. Molecular dynamics simulations revealed that increasing the concentration of ethanol and 1,2-propanediol affected the overall structural changes in the myosin heavy chain (MHC), while glycerol exerted a more pronounced effect on the MHC tail when compared to the MHC head. Disruption of the hydration layers induced by ethanol and 1,2-propanediol contributed to local structural changes in myosin. Glycerol at a concentration of 20% induced the formation of a larger hydration layer around the MHC tail, which facilitated the stabilization of the protein structure.

X-ray Structure-Guided Discovery of a Potent Benzimidazole Glutaminyl Cyclase Inhibitor That Shows Activity in a Parkinson's Disease Mouse Model.

The secretory glutaminyl cyclase (sQC) and Golgi-resident glutaminyl cyclase (gQC) are responsible for N-terminal protein pyroglutamation and associated with various human diseases. Although several sQC/gQC inhibitors have been reported, only one inhibitor, PQ912, is currently undergoing clinic trials for the treatment of Alzheimer's disease. We report an X-ray crystal structure of sQC complexed with PQ912, revealing that the benzimidazole makes "anchor" interactions with the active site zinc ion and catalytic triad. Structure-guided design and optimization led to a series of new benzimidazole derivatives exhibiting nanomolar inhibition for both sQC and gQC. In a MPTP-induced Parkinson's disease (PD) mouse model, BI-43 manifested efficacy in mitigating locomotor deficits through reversing dopaminergic neuronal loss, reducing microglia, and decreasing levels of the sQC/gQC substrates, α-synuclein, and CCL2. This study not only offers structural basis and new leads for drug discovery targeting sQC/gQC but also provides evidence supporting sQC/gQC as potential targets for PD treatment.

Ozone pollution aggravated by mountain-valley breeze over the western Sichuan Basin, Southwest China.

The impact of thermally driven mountain-valley breezes (MVB) on the atmospheric environment remains poorly understood, especially in ozone (O3)-polluted regions with complex underlying topography. To address this knowledge gap, we focused on the western Sichuan Basin (SCB), situated immediately east of the Tibetan Plateau (TP), which is considered susceptible to MVB coupled with severe O3 pollution in southwest China. We revealed the MVB driving diurnal O3 variations and meteorological mechanisms using surface observations and ERA5 reanalysis data. Local MVB days accounted for up to 47% of cases in the summers of 2015-2022. Driven by the MVB, the near-surface O3 concentrations increased by 8.8%, with 12.7% and 50.0% deterioration in the O3 light and moderate exceedance rates, respectively, on the western SCB edge. The daytime upslope valley breeze with 20% higher wind speed drove the westward transport of rich O3 and precursors from the upwind-polluted inner SCB towards its western edge, and the O3 photochemical production, followed by intensifying solar radiation and air temperature, gave rise to 14.8% of surface O3 concentrations over the western SCB edge. The nighttime downward mountain breeze with a 20% increase in wind speed could transport the rich O3 in the mountainous area to the basin edge, causing O3 levels to increase by 2.8%. In summary, we quantitatively assessed the impacts of MVB on changes in O3 concentrations and air quality along with its meteorological mechanisms, facilitating a comprehensive understanding of meteorological drivers in the atmospheric environment.

Rosmarinic acid plus deferasirox inhibits ferroptosis to alleviate crush syndrome-related AKI via Nrf2/Keap1 pathway.

BACKGROUND: Myoglobin (Mb) induced death of renal tubular epithelial cells (RTECs) is a major pathological factor in crush syndrome-related acute kidney injury (CS-AKI). It is unclear whether ferroptosis is involved and could be a target for treatment. PURPOSE: This study aimed to evaluate the potential therapeutic effects of combining the natural small molecule rosemarinic acid (RA) and the iron chelator deferasirox (Dfe) on CS-AKI through inhibition of ferroptosis. METHODS: Sequencing data were downloaded from the GEO database, and differential expression analysis was performed using the R software limma package. The CS-AKI mouse model was constructed by squeezing the bilateral thighs of mice for 16 h with 1.5 kg weight. TCMK1 and NRK-52E cells were induced with 200 µM Mb and then treated with RA combined with Dfe (Dfe + RA, both were 10 µM). Functional and pathological changes in mouse kidney were evaluated by glomerular filtration rate (GFR) and HE pathology. Immunofluorescence assay was used to detect Mb levels in kidney tissues. The expression levels of ACSL4, GPX4, Keap1, and Nrf2 were analyzed by WB. RESULTS: We found that AKI mice in the GSE44925 cohort highly expressed the ferroptosis markers ACSL4 and PTGS2. CS-AKI mice showed a rapid decrease in GFR, up-regulation of ACSL4 expression in kidney tissue, and down-regulation of GPX4 expression, indicating activation of the ferroptosis pathway. Mb was found to deposit in renal tubules, and it has been proven to cause ferroptosis in TCMK1 and NRK-52E cells in vitro. We found that Dfe had a strong iron ion scavenging effect and inhibited ACSL4 expression. RA could disrupt the interaction between Keap1 andNrf2, stabilize Nrf2, and promote its nuclear translocation, thereby exerting antioxidant effects. The combination of Dfe and RA effectively reversed Mb induced ferroptosis in RTECs. CONCLUSION: In conclusion, we found that RA combined with Dfe attenuated CS-AKI by inhibiting Mb-induced ferroptosis in RTECs via activating the Nrf2/Keap1 pathway.

Encapsulation of caffeic acid phenethyl ester by self-assembled sorghum peptide nanoparticles: Fabrication, storage stability and interaction mechanisms.

Caffeic acid phenethyl ester (CAPE) is a naturally occurring phenolic compound with various biological activities. However, poor water solubility and storage stability limit its application. In this context, sorghum peptides were used to encapsulate CAPE. Sorghum peptides could self-assemble into regularly spherical nanoparticles (SPNs) by hydrophobic interaction and hydrogen bonds. Solubility of encapsulated CAPE was greatly increased, with 9.44 times higher than unencapsulated CAPE in water. Moreover, the storage stability of CAPE in aqueous solution was significantly improved by SPNs encapsulation. In vitro release study indicated that SPNs were able to delay CAPE release during the process of gastrointestinal digestion. Besides, fluorescence quenching analysis showed that a static quenching existed between SPNs and CAPE. The interaction between CAPE and SPNs occurred spontaneously, mainly driven by hydrophobic interactions. The above results suggested that SPNs encapsulation was an effective approach to improve the water solubility and storage stability of CAPE.

Deep learning-based vessel extraction in 3D confocal microscope images of cleared human glioma tissues.

Comprehensive visualization and accurate extraction of tumor vasculature are essential to study the nature of glioma. Nowadays, tissue clearing technology enables 3D visualization of human glioma vasculature at micron resolution, but current vessel extraction schemes cannot well cope with the extraction of complex tumor vessels with high disruption and irregularity under realistic conditions. Here, we developed a framework, FineVess, based on deep learning to automatically extract glioma vessels in confocal microscope images of cleared human tumor tissues. In the framework, a customized deep learning network, named 3D ResCBAM nnU-Net, was designed to segment the vessels, and a novel pipeline based on preprocessing and post-processing was developed to refine the segmentation results automatically. On the basis of its application to a practical dataset, we showed that the FineVess enabled extraction of variable and incomplete vessels with high accuracy in challenging 3D images, better than other traditional and state-of-the-art schemes. For the extracted vessels, we calculated vascular morphological features including fractal dimension and vascular wall integrity of different tumor grades, and verified the vascular heterogeneity through quantitative analysis.

Weissella cibaria Relieves Gut Inflammation Caused by Escherichia coli through Inflammation Modulation and Gut Microbiota Regulation.

The emergence of multi-drug-resistant (MDR) pathogens has considerably challenged the development of new drugs. Probiotics that inhibit MDR pathogens offer advantages over chemical antibiotics and drugs due to their increased safety and fewer side effects. This study reported that Weissella cibaria P-8 isolated from pickles showed excellent antibacterial activity against intestinal pathogens, particularly the antibacterial activity against MDR Escherichia coli B2 was the highest. This study showed that the survival rates of W. cibaria P-8 at pH 2.0 and 0.3% bile salt concentration were 72% and 71.56%, respectively, and it still had antibacterial activity under pepsin, trypsin, protease K, and catalase hydrolysis. Moreover, W. cibaria P-8 inhibits the expression of inflammatory factors interleukin-1ß, tumor necrosis factor-α, and interleukin-6, upregulates the interleukin-10 level, and increases total antioxidant capacity and superoxide dismutase enzyme activity in serum. W. cibaria P-8 also efficiently repairs intestinal damage caused by E. coli infection. The gut microbiota analysis demonstrated that W. cibaria P-8 colonizes the intestine and increases the abundance of some beneficial intestinal microorganisms, particularly Prevotella. In conclusion, W. cibaria P-8 alleviated MDR E. coli-induced intestinal inflammation by regulating inflammatory cytokine and enzyme activity and rebalancing the gut microbiota, which could provide the foundation for subsequent clinical analyses and probiotic product development.