Perfusion Analysis Using High-Definition Indocyanine Green Angiography in Burn Comb Model.

Indocyanine green angiography (ICGA) has been widely employed for quantitative evaluation of the rat comb burn model, but the imaging equipment, imaging protocol, and fluorescence data interpretation of ICGA remain unsatisfactory. This study aims to provide better solutions for the application of ICGA in perfusion analysis. The rat comb burn model was established under a series of different comb contact durations, including 10, 20, 25, 30, 35, and 40 s. Indocyanine green angiography was used to analyze wound perfusion. In total, 16 rats were divided into ibuprofen and control groups for the burn model, and their perfusion was compared. A total of 16 identical models were divided into standard- and high-dose indocyanine green (ICG) groups, and ICGA was conducted to investigate the dynamic change in wound fluorescence. Escharectomy was performed under real-time fluorescence mapping and navigation. The results showed that a comb contact duration of 30 s was optimum for the burn model. Indocyanine green angiography could accurately evaluate the histologically determined depth of thermal injury and wound perfusion in the rat comb model. Digital subtraction of residual fluorescence was necessary for multiple comparisons of perfusion. Dynamic changes in fluorescence and necrotic tissues were observed more clearly by high-dose (0.5 mg/kg) ICG in angiography. In conclusion, perfusion analysis by ICGA can be used to assess the histologically determined depth of thermal injury and the impact of a specific treatment on wound perfusion. Indocyanine green angiography can help to identify necrotic tissue. The above findings and related imaging protocols lay the foundation for future research.

Comparative analysis of productive performance and fattening efficiency of commercial pigs in China for two consecutive years.

THE PURPOSE OF THIS STUDY: (1) propose an evaluation indicator of the fattening efficiency of commercial pigs (Yorkshire × Landrace × Duroc)-fattening efficiency index (FEI). (2) Analyze the correlation to find the main productive factors affecting the FEI. (3) Compare and analyze the yearly/monthly/different piglets' sources of productive performance in 2020 and 2021. The data included 2592 commercial pig batches in 2020 and 3266 in 2021, with a total of 6,134,234 commercial pigs. Descriptive statistics and difference analysis were carried out on 16 productive factors of a whole year and single/multiple sources for two consecutive years. The same period difference between the monthly data and the annual average were also analyzed. The top six productive factors correlated with FEI were average daily gain (ADG) (0.8080), feed conversion rate (FCR) (- 0.7203), survival rate (SR) (0.6968), number of deaths (- 0.4103), feeding days (- 0.3748) and body weight (BW) of marketing pigs (0.3369). The overall productive performance in 2021 was lower than that in 2020, which was reflected in more piglet sources and a lower BW of piglets, more deaths, a lower SR, longer feeding days, a lower ADG, a higher FCR and a lower FEI. The productive performance of a single source was better than that of multiple ones. The contrastive results of monthly data in 2020 and 2021 showed significant differences in most factors except for the number of marketing pigs, the number of piglets and feed consumption. The monthly trend of 15 factors for two consecutive years revealed similar trends only in the month of piglets purchasing, number of piglets sources, number of deaths and ADG. Compared with the annual average, the ADG significantly increased in May. The FEI of multiple sources was markedly lower than that of a single source. FEI may be suitable for evaluating the fattening efficiency of commercial pigs. The annual and monthly productive performance and fattening efficiency in 2021 were significantly lower than those in 2020. Single source was represented better productive performance and fattening efficiency than multiple ones.

CXCL11 negatively regulated by MED19 favours antitumour immune infiltration in breast cancer.

BACKGROUND: Through microarray results, we found that the C-X-C motif chemokine ligand 11 (CXCL11) was negatively regulated by mediator complex subunit 19 (MED19), a protumour factor. However, the biological role and potential mechanism of CXCL11 need to be explored in breast cancer (BRCA). METHODS: The BRCA dataset was obtained from the Cancer Genome Atlas (TCGA) dataset. Our microarray data and the BRCA dataset of TCGA were analysed and visualized using the R software package. The mRNA and protein levels were measured by qRT-PCR and western blotting. RESULTS: Inhibition of MED19 in MDA-MB-231 cells caused CXCL11 upregulation. The relative positive regulation of cytokine pathways was enriched after MED19 knockdown. High CXCL11 was determined to be positively correlated with immune response activation, increased antitumour immune cell infiltration, immune checkpoint molecule expression, and enhanced sensitivity to immunotherapy and chemotherapy. Collectively, CXCL11 promoted antitumour immunity and was regulated by MED19 in BRCA. Clarifying the prognostic value and underlying mechanism of CXCL11 in BRCA could provide a theoretical basis to find new diagnostic and therapeutic targets.

Identification of a Risk Predictive Signature Based on Genes Associated with Tumor Size and Lymph Node Involvement in Breast Cancer.

Background: Breast cancer is a heterogeneous disease. Small tumors with extensive lymph node involvement (STEL) in breast cancer often reflect a biologically aggressive phenotype and poor prognosis. The aim of this study was to identify key genes associated with STEL and investigate their prognostic values in breast cancer. Methods: RNA sequence data from breast cancer specimens were acquired from The Cancer Genome Atlas (TCGA) database for differential analysis. Weighted gene correlation network analyses (WGCNA) were performed to identify coexpressed gene modules associated with tumor size and lymph node metastases. Gene set enrichment analysis (GSEA) was employed to investigate the biological functions of the identified genes. A combination of LASSO and Cox regression analyses was conducted to establish a risk predictive signature, and time-dependent receiver operating characteristic (tdROC) and Kaplan-Meier analyses were used to evaluate its prediction precision. Quantitative RT-PCR was employed to validate the expression levels of the key genes from the signature set. Results: A total of 2777 genes from three coexpressed gene modules were identified by WGCNA, and 880 differentially expressed genes were identified by transcriptome analyses. The 63 overlapping genes identified by both methods were considered STEL-associated genes, and a 9-gene risk-predictive signature was established based on them, with AUCs at 3, 5, and 7 years reaching 0.810, 0.811, and 0.753, respectively. Conclusion: This study demonstrated the transcriptomic profile of STEL breast cancer and successfully established a risk predictive signature with satisfactory accuracy. These findings may provide insights in to the genetic etiology of breast cancer.

Long-term in vivo imaging of mouse spinal cord through an optically cleared intervertebral window.

The spinal cord accounts for the main communication pathway between the brain and the peripheral nervous system. Spinal cord injury is a devastating and largely irreversible neurological trauma, and can result in lifelong disability and paralysis with no available cure. In vivo spinal cord imaging in mouse models without introducing immunological artifacts is critical to understand spinal cord pathology and discover effective treatments. We developed a minimally invasive intervertebral window by retaining the ligamentum flavum to protect the underlying spinal cord. By introducing an optical clearing method, we achieve repeated two-photon fluorescence and stimulated Raman scattering imaging at subcellular resolution with up to 15 imaging sessions over 6-167 days and observe no inflammatory response. Using this optically cleared intervertebral window, we study neuron-glia dynamics following laser axotomy and observe strengthened contact of microglia with the nodes of Ranvier during axonal degeneration. By enabling long-term, repetitive, stable, high-resolution and inflammation-free imaging of mouse spinal cord, our method provides a reliable platform in the research aiming at interpretation of spinal cord physiology and pathology.

Effect of pupil matching of cold shield on the fringe contrast of long-wave infrared spatial heterodyne spectroscopy.

Matching the cold shield with the exit pupil of the fringe-imaging system of long-wave infrared (LWIR) spatial heterodyne spectroscopy (SHS) damages illumination uniformity of the interferogram and affects the fringe contrast, which is a significant parameter for LWIR SHS. The optical models of the fringe-imaging system considering and not considering the pupil matching of the cold shield are built to illustrate the effect on the fringe contrast. Simulations based on the optical design software ASAP are conducted to verify the fringe contrast loss for field-widened LWIR SHS. The result shows that the pupil matching of the cold shield decreases the fringe contrast of LWIR SHS and field-widened LWIR SHS by 0.049% and 0.053%, respectively, and the fringe contrast loss increases with the degree of deviation from the telecentric condition of the fringe-imaging system.

FGFR1 Is Associated With Tamoxifen Resistance and Poor Prognosis of ER-Positive Breast Cancers by Suppressing ER Protein Expression.

Fibroblast growth factor receptor 1 (FGFR1) is widely recognized as a key player in mammary carcinogenesis and associated with the prognosis and therapeutic response of breast cancers. With the aim of investigating the correlation between FGFR1 expression and estrogen receptor (ER) and exploring the effect of FGFR1 on endocrine therapy response and ER+ breast cancer prognosis, we examined the FGFR1 protein expression among 184 ER-positive breast cancers by the immunohistochemistry (IHC) method, analyzed the association between FGFR1 expression and disease characters using the Pearson's chi-square test, and assessed the prognostic role of FGFR1 among breast cancers using Cox regression and Kaplan-Meier analyses. Moreover, in vitro assays were conducted to confirm the correlation between FGFR1 and ER expression and investigate the effect of FGFR1 on tamoxifen (TAM) sensitivity in ER+ breast cancer. The results showed that ER expression was negatively correlated with FGFR1 expression (P = 0.011, r = -0.221). Moreover, FGFR1 expression was one of the prognostic factors of ER-positive breast cancer (OR = 1.974, 95% CI = 1.043-3.633), and high FGFR1 expression was correlated with decreased breast cancer overall survival. In addition, knocking down FGFR1 inhibited cell proliferation and enhanced TAM sensitivity in TAM-resistant cells. In conclusion, we found that there was a significant negative correlation between FGFR1 and ER levels in ER+ breast cancers, high FGFR1 protein expression was associated with poor breast cancer prognosis, down-regulating FGFR1 could elevate ER expression and is associated with enhanced TAM sensitivity in ER+ breast cancers.

Identification of Hub Genes and Pathways of Triple Negative Breast Cancer by Expression Profiles Analysis.

PURPOSE: Triple negative breast cancer (TNBC) is an intrinsic subtype of breast cancer with a poor prognosis, characterized by a lack of ER and PR expression and the absence of HER2 amplification. The aim of this study is to characterize hub genes (key genes in the molecular interaction network) expression in TNBC, which may serve as prognostic predictors for TNBC treatment. METHODS: Four transcriptome microarray datasets GSE27447, GSE39004, GSE43358 and GSE45827 were obtained from the Gene Expression Omnibus (GEO) database, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted by DAVID and KOBAS database. Thereafter, protein-protein interaction (PPI) network was constructed according to STRING online database. Functional modules and hub genes were screened by MCODE and cytohubba plug-ins, and the Cancer Genome Atlas (TCGA) survival analysis and qRT-PCR were utilized to validate the expression of these hub genes on TNBC. RESULTS: A total of 134 DEGs were identified by differential expression analysis, consisting of 88 up- and 46 down-regulated genes. GO and KEGG analyses showed that the terms and pathways enriched were mainly associated with cell adhesion, tumorigenesis and cellular immunity. From the PPI network, we identified six hub genes, including CD3D, CD3E, CD3G, FYN, GRAP2 and ITK. Survival analysis and the qRT-PCR results confirmed the robustness of the identified hub genes. CONCLUSION: This study provides a new insight into the understanding of the molecular mechanisms associated with TNBC and suggested that the hub genes may serve as prognostic predictors.

Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis.

Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

Identification of Potential Key Genes and Pathways for Inflammatory Breast Cancer Based on GEO and TCGA Databases.

INTRODUCTION: Inflammatory breast cancer (IBC) is a rare type of breast cancer with poor prognosis, and the pathogenesis of this life-threatening disease is yet to be fully elucidated. This study aims to identify key genes of IBC, which could be potential diagnostic or therapeutic targets. METHODS: Four datasets GSE5847, GSE22597, GSE23720, and GSE45581 were downloaded from the Gene Expression Omnibus (GEO) and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to understand the potential bio-functions of the differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed for functional modules analysis and hub genes identification, and TCGA survival analysis and qRT-PCR of clinical samples were used to further explore and validate the effect of hub genes on IBC. RESULTS: A total of 114 DEGs were identified from the GEO datasets. GO and KEGG analyses showed that the DEGs were mainly enriched in oncogenesis and cell adhesion. From the PPI network, we screened out five hub genes, including PTPRC, IL6, SELL, CD40, and SPN. Survival analysis and expression validation verified the robustness of the hub genes. DISCUSSION: The present study provides new insight into the understanding of IBC pathogenesis and the identified hub genes may serve as potential targets for diagnosis and treatment.

Screening and Identification of Key Biomarkers in Inflammatory Breast Cancer Through Integrated Bioinformatic Analyses.

Background: Inflammatory breast cancer (IBC) is a rare type of breast cancer with poor prognoses, moreover its pathogenesis is not entirely clear. The aim of this study was to identify key genes of IBC, which might serve as diagnostic biomarkers and/or therapeutic targets. Methods: Two microarray datasets, GSE23720 and GSE45581, were obtained from the Gene Expression Omnibus database, and a differential expression analysis was performed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to understand the potential biological functions of the differentially expressed genes (DEGs). Next, a protein-protein interaction (PPI) network was constructed and visualized by Cytoscape. Functional modules and hub genes were screened using MCODE and cytohubba plug-ins, and the Cancer Genome Atlas survival analysis along with quantitative reverse transcriptional polymerase chain reactions of clinical samples was used to validate the effect that the hub genes have on IBC. Results: A total of 215 DEGs were identified, consisting of 105 upregulated and 110 downregulated genes. GO and KEGG analyses showed that the enriched terms and pathways were mainly associated with cell cycle, proliferation, drug metabolism, and oncogenesis. From the PPI network, we identified six hub genes, including Cell Division Cycle 45 (CDC45), Polo Like Kinase 1 (PLK1), BUB1 Mitotic Checkpoint Serine/Threonine Kinase B (BUB1B), Cell Division Cycle 20 (CDC20), Aurora Kinase A (AURKA), and Mitotic Arrest Deficient 2 Like 1 (MAD2L1). The survival analyses and expression validation studies verified the robustness of these hub genes. Conclusion: This study provides new insights into the understanding of the molecular mechanisms of IBC; in addition, the identified hub genes may serve as potential targets for diagnosis and treatment.

Identification of a four-long non-coding RNA signature in predicting breast cancer survival.

Long non-coding RNAs (lncRNAs) serve key roles in tumorigenesis and are differentially expressed in cancer. Using bioinformatics and statistical methods, the present study aimed to identify an lncRNA signature to predict breast cancer survival. The gene expression data of 768 patients with breast cancer were downloaded from The Cancer Genome Atlas database, and Cox regression, Kaplan-Meier and receiver operating characteristic (ROC) analyses were performed to construct and validate a predictive model. Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were employed to predict the functions of the indicated lncRNAs. A signature consisting of four lncRNAs, including PVT1, MAPT-AS1, LINC00667 and LINC00938, was identified, and patients were subsequently divided into high- and low-risk groups according to the median risk score. Kaplan-Meier analysis confirmed that patients in the high-risk group exhibited significantly poorer overall survival rate in both the training (P=0.0151) and the validation set (P=0.0016); furthermore, ROC analysis confirmed that the model could predict patient survival with a certain sensitivity and specificity. In conclusion, the four-lncRNA signature presents a potential prognostic biomarker for breast cancer that may be relevant for clinical application.

Landscape of tumor suppressor long noncoding RNAs in breast cancer.

BACKGROUND: The landscape and biological functions of tumor suppressor long noncoding RNAs in breast cancer are still unknown. METHODS: Data from whole transcriptome sequencing of 33 breast specimens in the Harbin Medical University Cancer Center cohort and The Cancer Genome Atlas was applied to identify and validate the landscape of tumor suppressor long noncoding RNAs, which was further validated by The Cancer Genome Atlas pancancer data including 33 cancer types and 12,839 patients. Next, the expression model, prognostic roles, potential biological functions and epigenetic regulation of tumor suppressor long noncoding RNAs were investigated and validated in the breast cancer and pancancer cohorts. Finally, EPB41L4A-AS2 was selected to validate our novel finding, and the tumor suppressive roles of EPB41L4A-AS2 in breast cancer were examined. RESULTS: We identified and validated the landscape of tumor suppressor long noncoding RNAs in breast cancer. The expression of the identified long noncoding RNAs was downregulated in cancer tissue samples compared with normal tissue samples, and these long noncoding RNAs correlated with a favorable prognosis in breast cancer patients and the patients in the pancancer cohort. Multiple carcinogenesis-associated biological functions were predicted to be regulated negatively by these long noncoding RNAs. Moreover, these long noncoding RNAs were transcriptionally regulated by epigenetic modification, including DNA methylation and histone methylation modification. Finally, EPB41L4A-AS2 inhibited breast cancer cell proliferation, migration and invasion and induced cell apoptosis in vitro. Mechanistically, EPB41L4A-AS2, acting at least in part as a tumor suppressor, upregulated tumor suppressor gene expression. Moreover, ZNF217 recruited EZH2 to the EPB41L4A-AS2 locus and suppressed the expression of EPB41L4A-AS2 by epigenetically increasing H3K27me3 enrichment. CONCLUSIONS: This work enlarges the functional landscape of known long noncoding RNAs in human cancer and provides novel insights into the suppressive roles of these long noncoding RNAs.

Upregulation of DLEU1 expression by epigenetic modification promotes tumorigenesis in human cancer.

The function of DLEU1 in human cancer is largely unknown. The Cancer Genome Atlas data were applied to identify the landscape of differential genes between tumor tissues and normal tissues, which was further validated by our cohort data and pan-cancer data including 33 cancer types with 11,060 patients. Next, DLEU1 was selected to validate the novel finding and result showed that it promoted tumorigenesis in vitro and in vivo. Mechanistically, DLEU1 promotes SRP4 expression via increasing H3K27ac enrichment to SRP4 locus epigenetically. Moreover, epigenetic modification leads to upregulation of DLEU1 expression via decreased DNA methylation and increased H3K27ac and H3K4me3 histone modification in its locus. Finally, high expression of DLEU1 correlates with worse prognosis not only in specific cancer type patients but also in patients in the pan-cancer cohort. In summary, the work broadens the function landscape of known long noncoding RNAs in human cancer and provides novel insights into their roles in tumorigenesis.

Effects of FGFR1 Gene Polymorphisms on the Risk of Breast Cancer and FGFR1 Protein Expression.

BACKGROUND/AIMS: Fibroblast growth factor receptor 1 (FGFR1) is widely considered to play an important role in mammary carcinogenesis. Some common variants in FGFR1 might be associated with its expression, and further affect breast cancer risk. The aim of this study was to investigate effects of single-nucleotide polymorphisms (SNPs) in FGFR1 on breast cancer susceptibility and FGFR1 protein expression. METHODS: SNPs rs17182023, rs17175624 and rs10958704 in FGFR1 were genotyped in 747 breast cancer cases and 716 healthy controls by SNaPshot method. The associations between SNPs and breast cancer were examined by logistic regression. Immunohistochemistry(IHC) was used to detect FGFR1 protein expression, and the association of FGFR1 polymorphisms with its protein expression was analyzed by Pearson's chi-square test. Additionally, Cox regression and Kaplan-Meier analysis was used to evaluate the association between FGFR1 protein expression and breast cancer prognosis. RESULTS: The minor allele of rs17182023 in FGFR1 was significantly associated with reduced breast cancer risk, with an odds ratio of 0.800 (95%CI = 0.684-0.935). No significant associations were detected between other SNPs and breast cancer. Moreover, rs17182023 was correlated to FGFR1 protein expression (P = 0.006), and patients with high FGFR1 protein expression tended to have poor outcomes. CONCLUSIONS: SNP rs17182023 was correlated to reduced breast cancer risk, and was associated with FGFR1 protein expression. High FGFR1 protein expression was an independent risk factor of breast cancer, and resulted in poor prognosis.

Efficacy of vaccination and nisin Z treatments to eliminate intramammary Staphylococcus aureus infection in lactating cows.

This study evaluated the effect of a Staphylococcus aureus bacterin and nisin on bovine subclinical mastitis. A total of 75 Holstein subclinically mastitic cows were randomly allocated to three groups with 25 cows per group. In group I, an intramammary infusion of nisin Z at a dose of 2.50×106 IU was carried out once daily for three days, and an autogenous S. aureus bacterin was inoculated into the supramammary lymph node one week before and one week after nisin treatment. In group II, nisin was administered in the same way as in group I, but no bacterin was inoculated. Group III received no treatment and served as a control. Milk was aseptically sampled from the affected quarters before and 2, 4, and 6 weeks after treatment, for bacteriological examination and analyses of N-acetyl-ß-D-glucosaminidase (NAGase) activity, somatic cell count (SCC), and milk protein and fat contents. Results indicated that, compared to the nisin-treated group, nisin-bacterin treatment significantly reduced intramammary S. aureus infections, reduced the number of quarters with milk SCCs of more than 5×105 cells/ml, and increased the protein and fat contents of the milk. Therefore, nisin-bacterin therapy is suggested when subclinical mastitis occurs in lactating cows.

Ethylene is Involved in Brassinosteroids Induced Alternative Respiratory Pathway in Cucumber (Cucumis sativus L.) Seedlings Response to Abiotic Stress.

Effects of brassinosteroids (BRs) on cucumber (Cucumis sativus L.) abiotic stresses resistance to salt, polyethylene glycol (PEG), cold and the potential mechanisms were investigated in this work. Previous reports have indicated that BRs can induce ethylene production and enhance alternative oxidase (AOX) pathway. The mechanisms whether ethylene is involved as a signal molecule which connected BR with AOX in regulating stress tolerance are still unknown. Here, we found that pretreatment with 1 µM brassinolide (BL, the most active BRs) relieved stress-caused oxidative damage in cucumber seedlings and clearly enhanced the capacity of AOX and the ethylene biosynthesis. Furthermore, transcription level of ethylene signaling biosynthesis genes including ripening-related ACC synthase1 (C S ACS1), ripening-related ACC synthase2 (C S ACS2), ripening-related ACC synthase3 (C S ACS3), 1-aminocyclopropane-1-carboxylate oxidase1 (C S ACO1), 1-aminocyclopropane-1-carboxylate oxidase2 (C S ACO2), and C S AOX were increased after BL treatment. Importantly, the application of the salicylhydroxamic acid (SHAM, AOX inhibitor) and ethylene biosynthesis inhibitor aminooxyacetic acid (AOA) decreased plant resistance to environmental stress by blocking BRs-induced alternative respiration. Taken together, our results demonstrated that ethylene was involved in BRs-induced AOX activity which played important roles in abiotic stresses tolerance in cucumber seedlings.

Therapeutic effect of nisin Z on subclinical mastitis in lactating cows.

Bovine subclinical mastitis is an inflammation of the mammary gland caused by bacterial intramammary infection, accounting for large economic losses. Treatment of subclinical mastitis is not suggested for lactating cows due to the risk of milk contamination. The objectives of this study were to evaluate an antimicrobial peptide, nisin, in the treatment of subclinical mastitis in lactating cows. A total of 90 lactating Holstein cows with subclinical mastitis were randomly divided into nisin-treated (n = 46) and control (n = 44) groups. In the nisin-treated group, cows received an intramammary infusion of nisin at a dose of 2,500,000 IU once daily for 3 days while the control cows received no treatment. Milk samples were collected from the affected mammary quarters before treatment and 1 and 2 weeks after treatment for analyses of bacteria, somatic cells, and N-acetyl-beta-D-glucosaminidase (NAGase). Results indicated that nisin therapy had bacteriological cure rates of 90.1% for Streptococcus agalactiae (10 of 11), 50% for Staphylococcus aureus (7 of 14), 58.8% for coagulase-negative staphylococci (7 of 17), and 65.2% for all cases (30 of 46). Meanwhile, only 15.9% (7 of 44) of untreated cows spontaneously recovered. NAGase activity in milk samples and the number of mammary quarters with a milk somatic cell count of > or =500,000/ml were significantly decreased after nisin treatment while no significant changes took place in the control group. Because of its therapeutic effects on bovine subclinical mastitis, as well as its safety in humans, nisin deserves further study to clarify its effects on mastitis caused by different pathogens.