Diagnosis of Canine Tumours and the Value of Combined Detection of VEGF, P53, SF and NLRP3 for the Early Diagnosis of Canine Mammary Carcinoma.

The average life of a dog is generally maintained at ten to fifteen years, and tumours are the predominant reason that leads to the death of dogs, especially canine mammary carcinoma. Therefore, early diagnosis of tumours is very important. In this study, tumor size, morphology, and texture could be seen through general clinical examination, tumor metastasis could be seen through imaging examination, inflammatory reactions could be seen through hematological examination, and abnormal cell morphology could be seen through cytological and histopathological examination. In the 269 malignant cases and 179 benign cases, we randomly selected 30 cases each, and an additional 30 healthy dogs were selected for the experiment (healthy dogs: dogs in good physical condition without any tumor or other diseases). We used RT-qPCR and ELISA to determine the relative expression of vascular endothelial growth factor (VEGF), tumor protein P53 (P53), serum ferritin (SF), and NOD-like receptor protein 3 (NLRP3) in 30 healthy dogs, 30 dogs with benign mammary tumours, and 30 dogs with malignant mammary tumours. In the results, the same expression trend was obtained both in serum and tissues, and the expression of the four markers was the highest in malignant mammary tumours, with highly significant differences compared with the benign and healthy/paracancerous groups. By plotting the ROC curves, it was found that the results of combined tests were better than a single test and the combination of the four markers was the best for the early diagnosis. In conclusion, this can assist the clinical early diagnosis to a certain extent, and also provides some references and assistance for the development of tumor detection kits in clinical practice.

Development and Validation of a Clinical Model for Predicting Delay in Postoperative Transfer Out of the Post-Anesthesia Care Unit: A Retrospective Cohort Study.

Objective: We aimed to analyze the factors related to delay in transfer of patients in the post-anesthesia care unit (PACU) and to develop and validate a prediction model for understanding these factors to guide precise clinical intervention. Methods: We collected data from two cohorts of 1153 and 297 patients who underwent surgery and were treated in the PACU at two time points. We examined their clinical features and anesthesia care data using analytical methods such as logistic regression, Random Forest, and eXtreme Gradient Boosting (Xgboost) to screen out variables and establish a prediction model. We then validated and simplified the model and plotted a nomogram. Using LASSO regression, we reduced the dimensionality of the data. We developed multiple models and plotted receiver operating characteristic (ROC) and calibration curves. We then constructed a simplified model by pooling the identified variables, which included hemoglobin (HB), alanine transaminase (ALT), glucose levels, duration of anesthesia, and the minimum bispectral index value (BIS_min). Results: The model had good prediction performance parameters in the training and validation sets, with an AUC of 0.909 (0.887-0.932) in the training set and 0.939 (0.919-0.959) in the validation set. When we compared model 6 with other models, the net reclassification index (NRI) and the integrated discriminant improvement (IDI) index indicated that it did not differ significantly from the other models. We developed a scoring system, and it showed good prediction performance when verified with the training and validation sets as well as external data. Additionally, both the decision curve analysis (DCA) and clinical impact curve (CIC) demonstrated the potential clinical efficacy of the model in guiding patient interventions. Conclusion: Predicting transfer delays in the post-anesthesia care unit using predictive models is feasible; however, this merits further exploration.

Research progress of good markers for canine mammary carcinoma.

PURPOSE: Mammary gland tumors are the most common neoplastic diseases in elderly female dogs, about 50% of which are considered to be malignant. Canine mammary tumors are similar to human breast cancers in many respects, so canine mammary tumors are frequently studied alongside human breast cancer. This article mentioned KI-67, HER-2, COX-2, BRCA1, BRCA2, P53, CA15-3, MicroRNA, Top2α and so on. All these markers are expected to have an important role in the clinic. METHODS: Existing markers of canine mammary carcinoma are reviewed, and the expression of each marker and its diagnostic role for this tumor are described in detail. RESULTS: This article introduced several effective markers of canine mammary tumors, among them, antigen KI-67 (KI-67), human epidermal growth factor receptor 2 (HER-2), cyclooxygenase 2 (COX-2) are promising and can be detected in both serum and tissue samples. Breast cancer caused by mutations in the breast cancer 1 gene (BRCA1) and breast cancer 2 gene (BRCA2) is also a hot topic of research. In addition to the above symbols, tumor protein p53 (p53), cancer antigen15-3 (CA15-3), MicroRNA (miRNA), topoisomerase πα (Top2α), proliferating cell nuclear antigen (PCNA), epidermal growth factor receptor (EGFR) and E-cadherin will also be involved in this paper. We will also mention Mammaglobin, which has been rarely reported so far.

Isolation, Identification and Antimicrobial Resistance Analysis of Canine Oral and Intestinal Escherichia coli Resistant to Colistin.

In recent years, the antimicrobial resistance in Escherichia coli has gradually developed into a global problem. These resistant bacteria could be transmitted to humans through animal feces in the environment or direct contact with pets, leading to a problem in bacterial treatment for humans and animals. Now, the antibiotic resistance of oral and intestinal microbiota from dog origins remains unclear in China. Therefore, this study first analyzed the current colistin resistance of oral and intestinal microbiota from dog origins in mainland China. A total of 536 samples were collected from dogs in mainland China and, respectively, cultured on the SS and MacConkey agar plate containing colistin (4 µg/mL) to obtain bacteria, and the antibiotic-resistance phenotype of Escherichia coli was investigated for nine antibiotics. Results showed that a total of 2259 colistin-resistant bacteria were isolated from samples and identified, and among them, the isolated rate of Escherichia coli (34.01%, 769/2259) was relatively higher than that of other bacteria. Subsequently, it was found that the resistance of these Escherichia coli was very severe by exploring its resistance to different antibiotics, particularly to three common antibiotics in a clinic which were ceftriaxone, ampicillin and trimethoprim/sulfamethoxazole, with the resistance rates of 60.60% (466/769), 57.22% (440/769), and 53.06% (408/769), respectively. Moreover, the simultaneous resistance of Escherichia coli to one or more antibiotics was determined, and 69.96% (538/769) strains have defined the resistance to both two or more antibiotics, and even 13 of Escherichia coli strains that were resistant to all nine antibiotics, indicating that the Escherichia coli from dog origins has severe antibiotic resistance in the clinic. In conclusion, this study guided the use of antibiotics and could draw attention to antibiotic resistance in veterinary clinical treatment for animals in the future.

Identification of canine mammary tumor-associated metabolites using untargeted metabolomics.

The canine mammary tumor is the most common tumor type in female dogs and seriously threatens their life. Currently, no effective treatments are available for this condition. Hence, it is essential to identify biomarkers that positively influence the early diagnosis and treatment and prognosis of this disease. To provide a basis for early diagnosis of canine breast tumors, in this study, 23 dogs with mammary tumors were identified via histopathological examination combined with ancillary diagnoses via blood examinations and diagnostic imaging. The canine mammary tumor and tumor-adjacent healthy tissues were collected, and their metabolites were identified utilizing a UHPLC-qTOF-MS-based untargeted metabolomics approach. The metabolic results revealed a total of 979 ion features in the positive polarity mode and 371 ion features in the negative polarity mode in the tissues of two groups; among them, 536 differential metabolites (385 in the positive and 151 in the negative polarity mode) were analyzed by PCA and PLS-DA. Subsequently, the enrichment pathways purine metabolism, alpha-linolenic acid metabolism, vitamin B6 metabolism, and fatty acid biosynthesis were analyzed using Metaboanalyst 4.0, which suggested that these pathways were valuable diagnostic and therapeutic targets. Moreover, the receiver operating characteristic curves further confirmed 13Z,16Z-docosadienoic acid, 23-nordeoxycholic acid, and (±)12(13)-DiHOME as expected candidate biomarkers of canine mammary tumors. In conclusion, the discovery of tumor biomarkers based on untargeted metabolomics is informative for pathological mechanism studies and facilitates the early diagnosis of canine mammary tumors.

A study on the correlation between intrauterine microbiota and uterine pyogenesis in dogs.

Pyometra is a common and high-incidence reproductive system disease in female dogs, and its development involves both hormonal and bacterial factors. Characterization of the endometrial microbiome in healthy dogs and diseased dogs with pyometra remains unclear at present, however. In this study, dogs with pyometra were identified based on the clinical examinations, hematology examinations, vaginal smears and uterine histopathology. The endometrial samples of healthy dogs (n = 30) and diseased dogs (n = 41) were then collected and sequenced by 16S rRNA high-throughput sequencing technology. Dogs with pyometra suffered from inflammation, and their endometrial microbial diversity (ACE and Chao 1 indices) was significantly lower than that of healthy dogs (P < 0.05). The endometrial samples of both groups were enriched in four phyla (Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria), with a greater abundance of Firmicutes in diseased dogs (P < 0.05). At the genus level, the most prevalent microbes in diseased dogs belonged to Pseudomonas, Escherichia-Shigella, Mycoplasma, Enterococcus, Haemophilus, Vibrio and Ralstonia, with lower levels of Mycoplasma, Enterococcus and Haemophilus in the healthy control. Principal co-ordinates analysis and non-metric multi-dimensional scaling showed that the endometrial microbiome of diseased dogs clustered separately from that of the healthy controls (P < 0.05). In the LDA effect size analysis, 18 members of the endometrial microbiome were screened. Of these, the bacterial species Pseudomonas_aeruginosa and microbes within the genera Mycoplasma, Enterococcus and Haemophilus were found to be enriched in the uteruses of diseased dogs. Furthermore, the Random Forests model further confirmed that Mycoplasma and Haemophilus could be considered as biomarkers of diseased endometrium. In conclusion, this study provided a theoretical basis for the development of probiotic preparation in the future.

Identification of Canine Pyometra-Associated Metabolites Using Untargeted Metabolomics.

Canine pyometra frequently occurs in middle-aged to older intact bitches, which seriously affects the life of dogs and brings an economic loss to their owners. Hence, finding a key metabolite is very important for the diagnosis and development of a new safe and effective therapy for the disease. In this study, dogs with pyometra were identified by blood examinations, laboratory analyses and diagnostic imaging, and fifteen endometrium tissues of sick dogs with pyometra and fifteen controls were collected and their metabolites were identified utilizing a UHPLC-qTOF-MS-based untargeted metabolomics approach. The results indicated that the elevated inflammatory cells were observed in dogs with pyometra, suggesting that sick dogs suffered systemic inflammation. In the untargeted metabolic profile, 705 ion features in the positive polarity mode and 414 ion features in the negative polarity mode were obtained in endometrium tissues of sick dogs with pyometra, with a total of 275 differential metabolites (173 in positive and 102 in negative polarity modes). Moreover, the multivariate statistical analyses such as PCA and PLS-DA also showed that the metabolites were significantly different between the two groups. Then, these differential metabolites were subjected to pathway analysis using Metaboanalyst 4.0, and Galactose metabolism, cAMP signaling pathway and Glycerophospholipid metabolism were enriched, proving some insights into the metabolic changes during pyometra. Moreover, the receiver operating characteristic curves further confirmed kynurenic acid was expected to be a candidate biomarker of canine pyometra. In conclusion, this study provided a new idea for exploring early diagnosis methods and a safe and effective therapy for canine pyometra.

The Relationship of Tumor Microbiome and Oral Bacteria and Intestinal Dysbiosis in Canine Mammary Tumor.

Canine mammary tumor (CMT) is the most common tumor in dogs, with 50% of malignant cases, and lacks an effective therapeutic schedule, hence its early diagnosis is of great importance to achieve a good prognosis. Microbiota is believed to play important roles in systemic diseases, including cancers. In this study, 91 tumors, 21 oral and fecal samples in total were collected from dogs with CMTs, and 31 oral and 21 fecal samples from healthy dogs were collected as control. The intratumoral, oral and gut bacterial community of dogs with CMTs and healthy dogs was profiled by 16S rRNA high-throughput sequencing and bioinformatic methods. The predominant intratumoral microbes were Ralstonia, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Pseudomonas, unidentified_Chloroplast and Bacteroides at the genus level. In addition, our findings demonstrated striking changes in the composition of the oral and gut bacterium community in the dogs suffered from CMTs compared to the healthy dogs, with a significant increase of Bacteroides which also was the significant microbial biomarker in the oral and gut bacterium community. It showed that the Bacteroides was shared in the intratumoral, oral and intestinal bacterial microbiomes, confirming that microbiota might travel from the mouth to the intestine and finally to the distant mammary tumor tissue. This study provides a new microbiological idea for the treatment of canine mammary tumors, and also provides a theoretical basis for the study of human breast cancer.

Epidemiological Investigation of Canine Mammary Tumors in Mainland China Between 2017 and 2021.

Epidemiological studies enable us to analyze disease behavior, define risk factors, and establish fundamental prognostic criteria. This study aimed to determine the epidemiological and clinical characteristics of canine tumors diagnosed during the years 2017-2021. The results showed that canine mammary tumors were the most common tumors, and their relative incidence for 5-years-total was 46.71% (504/1,079), with 48.41% (244/504) of benign, and 51.59% (260/504) of malignant. Pure breeds accounted for 84.13% (424/504) of submissions, and adult female dogs (9-12 years old) were most frequently involved, followed by 5-8-year-old females. Remarkably, 2.58% (13/504) occurred in the male dogs. In addition, a high prevalence of mammary tumors (77.38%, 390/504) was diagnosed in unneutered dogs, and different incidence rates were observed in different regions (Northeast, Southeast, Northwest and Southwest China). For clinical factors, the tumor size ranged from 0.5 to 28 cm, with the 0-5 cm being the most common tumor size (47.82%, 241/504), and malignant tumors (4.33 ± 2.88 cm, mean ± SD) were bigger than benign ones (3.06 ± 1.67 cm, mean ± SD) (p < 0.001). The incidence of single tumor (55.36%, 279/504) was higher than that of multiple tumors in dogs, while the latter had a higher incidence of malignant tumors (74.67%, 168/225). According to this study, we also found that canine mammary tumors were more common in the last two pairs of mammary glands. In addition, multiple linear regression analysis showed that there was linear significant relationship between three independent variables (age, tumor size, and tumor number) and histological properties of canine mammary tumor [(p>|t|) < 0.05]. This is the first retrospective statistical analysis of such a large dataset in China to reveal the link between epidemiological clinical risks and histological diagnosis. It aids in the improvement of the host's knowledge of canine tumor disorders and the early prevention of canine mammary tumors.

LncRNA MALAT1 facilitates inflammasome activation via epigenetic suppression of Nrf2 in Parkinson's disease.

The goal of the present study was to elucidate the mechanism by which long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (lncRNA MALAT1) promotes inflammation in Parkinson's disease (PD). 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) was used to induce PD development in C57BL/6 mice, and tyrosine hydroxylase (TH) expression was analysed by immunohistochemical analysis. Western blot and qPCR analyses were conducted to assess the expression of protein and mRNA levels, respectively. Lipopolysaccharide/adenosine triphosphate (LPS/ATP) was used to activate microglia in vitro. Chromatin immunoprecipitation (ChIP), RNA pull-down and RNA immunoprecipitation chip (RIP) assays were performed to investigate the interaction among specific molecules. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was used to evaluate cell viability and proliferation. Flow cytometry was performed to analyse cell apoptosis after staining. The dichlorofluorescein diacetate (DCFH-DA) assay was used to measure the generation of reactive oxygen species (ROS) in cells. The results showed that MALAT1 was highly expressed in the brains of MPTP-induced PD model mice and in LPS/ATP-induced microglia cells. Knockdown of MALAT1 inhibited elevated nuclear factor (erythroid-derived 2)-like-2 factor (NRF2) expression, thereby inhibiting inflammasome activation and ROS production. MALAT1 was shown to promote neuroinflammation by recruiting enhancer of zeste homologue 2 (EZH2) to the promoter of NRF2, suppressing Nrf2 expression. In summary, MALAT1 epigenetically inhibits NRF2, thereby inducing inflammasome activation and reactive oxygen species (ROS) production in PD mouse and microglial cell models.