Mammographic Density Reduction is Associated to the Prognosis in Asian Breast Cancer Patients Receiving Hormone Therapy.

INTRODUCTION: Using mammographic density as a significant biomarker for predicting prognosis in adjuvant hormone therapy patients is controversial due to the conflicting results of recent studies. This study aimed to evaluate hormone therapy-induced mammographic density reduction and its association with prognosis in Taiwanese patients. METHODS: In this retrospective study, 1941 patients with breast cancer were screened, and 399 patients with estrogen receptor-positive breast cancer who received adjuvant hormone therapy were enrolled. The mammographic density was measured using a fully automatic estimation procedure based on full-field digital mammography. The prognosis included relapse and metastasis during treatment follow-up. The Kaplan-Meier method and Cox proportional hazards model were used for disease-free survival analysis. RESULTS: A mammographic density reduction rate >20.8%, measured preoperatively and after receiving hormone therapy from 12-18 months, was a significant threshold for predicting prognosis in patients with breast cancer. The disease-free survival rate was significantly higher in patients whose mammographic density reduction rate was >20.8% (P = .048). CONCLUSION: This study's findings could help estimate the prognosis for patients with breast cancer and may improve the quality of adjuvant hormone therapy after enlarging the study cohort in the future.

Specific Forms of Graphene Quantum Dots Induce Apoptosis and Cell Cycle Arrest in Breast Cancer Cells.

Graphene quantum dots (GQDs), nanomaterials derived from graphene and carbon dots, are highly stable, soluble, and have exceptional optical properties. Further, they have low toxicity and are excellent vehicles for carrying drugs or fluorescein dyes. Specific forms of GQDs can induce apoptosis and could be used to treat cancers. In this study, three forms of GQDs (GQD (nitrogen:carbon = 1:3), ortho-GQD, and meta-GQD) were screened and tested for their potential to inhibit breast cancer cell (MCF-7, BT-474, MDA-MB-231, and T-47D) growth. All three GQDs decreased cell viability after 72 h of treatment and specifically affected breast cancer cell proliferation. An assay for the expression of apoptotic proteins revealed that p21 and p27 were up-regulated (1.41-fold and 4.75-fold) after treatment. In particular, ortho-GQD-treated cells showed G2/M phase arrest. The GQDs specifically induced apoptosis in estrogen receptor-positive breast cancer cell lines. These results indicate that these GQDs induce apoptosis and G2/M cell cycle arrest in specific breast cancer subtypes and could potentially be used for treating breast cancers.

Semantic Segmentation of the Malignant Breast Imaging Reporting and Data System Lexicon on Breast Ultrasound Images by Using DeepLab v3.

In this study, an advanced semantic segmentation method and deep convolutional neural network was applied to identify the Breast Imaging Reporting and Data System (BI-RADS) lexicon for breast ultrasound images, thereby facilitating image interpretation and diagnosis by providing radiologists an objective second opinion. A total of 684 images (380 benign and 308 malignant tumours) from 343 patients (190 benign and 153 malignant breast tumour patients) were analysed in this study. Six malignancy-related standardised BI-RADS features were selected after analysis. The DeepLab v3+ architecture and four decode networks were used, and their semantic segmentation performance was evaluated and compared. Subsequently, DeepLab v3+ with the ResNet-50 decoder showed the best performance in semantic segmentation, with a mean accuracy and mean intersection over union (IU) of 44.04% and 34.92%, respectively. The weighted IU was 84.36%. For the diagnostic performance, the area under the curve was 83.32%. This study aimed to automate identification of the malignant BI-RADS lexicon on breast ultrasound images to facilitate diagnosis and improve its quality. The evaluation showed that DeepLab v3+ with the ResNet-50 decoder was suitable for solving this problem, offering a better balance of performance and computational resource usage than a fully connected network and other decoders.

Multiview Contouring for Breast Tumor on Magnetic Resonance Imaging.

The shape and contour of the lesion are shown to be effective features for physicians to identify breast tumor as benign or malignant. The region of the lesion is usually manually created by the physician according to their clinical experience; therefore, contouring tumors on breast magnetic resonance imaging (MRI) is difficult and time-consuming. For this purpose, an automatic contouring method for breast tumors was developed for less burden in the analysis and to decrease the observed bias to help in making decisions clinically. In this study, a multiview segmentation method for detecting and contouring breast tumors in MRI was represented. The preprocessing of the proposed method reduces any amount of noises but preserves the shape and contrast of the breast tumor. The two-dimensional (2D) level-set segmentation method extracts contours of breast tumors from the transverse, coronal, and sagittal planes. The obtained contours are further utilized to generate appropriate three-dimensional (3D) contours. Twenty breast tumor cases were evaluated and the simulation results show that the proposed contouring method was an efficient method for delineating 3D contours of breast tumors in MRI.

Implant volume estimation in direct-to-implant breast reconstruction after nipple-sparing mastectomy.

BACKGROUND: Nipple-sparing mastectomy (NSM) is an increasingly popular alternative to more traditional mastectomy approaches. However, estimating the implant volume during direct-to-implant (DTI) reconstruction following NSM is difficult for surgeons with little-to-moderate experience. We aimed to provide a fast, easy to use, and accurate method to aid in the estimation of implant size for DTI reconstruction using the specimen weight and breast volume. METHODS: A retrospective analysis was performed using data from 145 NSM patients with specific implant types. Standard two-dimensional digital mammograms were obtained in 118 of the patients. Breast morphological factors (specimen weight, mammographic breast density and volume, and implant size and type) were recorded. Curve-fitting and linear regression models were used to develop formulas predicting the implant volume, and the prediction performance of the obtained formulas was evaluated using the prospective data set. RESULTS: Two formulas to estimate the implant size were obtained, one using the specimen weight and one using the breast volume. The coefficients of correlation (R2) in these formulas were over 0.98 and the root mean squared errors were approximately 13. CONCLUSIONS: These implant volume estimate formulas benefit surgeons by providing a preoperative implant volume assessment in DTI reconstruction using the breast volume and an intraoperative assessment using the specimen weight. The implant size estimation formulas obtained in the present study may be applied in a majority of patients.

Using Flow Characteristics in Three-Dimensional Power Doppler Ultrasound Imaging to Predict Complete Responses in Patients Undergoing Neoadjuvant Chemotherapy.

OBJECTIVES: Strategies are needed for the identification of a poor response to treatment and determination of appropriate chemotherapy strategies for patients in the early stages of neoadjuvant chemotherapy for breast cancer. We hypothesize that power Doppler ultrasound imaging can provide useful information on predicting response to neoadjuvant chemotherapy. METHODS: The solid directional flow of vessels in breast tumors was used as a marker of pathologic complete responses (pCR) in patients undergoing neoadjuvant chemotherapy. Thirty-one breast cancer patients who received neoadjuvant chemotherapy and had tumors of 2 to 5 cm were recruited. Three-dimensional power Doppler ultrasound with high-definition flow imaging technology was used to acquire the indices of tumor blood flow/volume, and the chemotherapy response prediction was established, followed by support vector machine classification. RESULTS: The accuracy of pCR prediction before the first chemotherapy treatment was 83.87% (area under the ROC curve [AUC] = 0.6957). After the second chemotherapy treatment, the accuracy of was 87.9% (AUC = 0.756). Trend analysis showed that good and poor responders exhibited different trends in vascular flow during chemotherapy. CONCLUSIONS: This preliminary study demonstrates the feasibility of using the vascular flow in breast tumors to predict chemotherapeutic efficacy.

Attenuation of AML1-ETO cellular dysregulation correlates with increased leukemogenic potential.

AML1-ETO (RUNX1-ETO) fusion proteins are generated by the 8;21 translocation, commonly found in acute myeloid leukemia, which fuses the AML1 (RUNX1) and ETO (MTG8, RUNX1T1) genes. Previous studies have shown that AML1-ETO interferes with AML1 function but requires additional cooperating mutations to induce leukemia development. In mouse models, AML1-ETO forms lacking the C-terminus have been shown to have greatly enhanced leukemogenic potential. Here, we investigate the role of 2 AML1-ETO C-terminal-interacting proteins, N-CoR, a transcriptional corepressor, and SON, a splicing/transcription factor required for cell cycle progression, in AML1-ETO-induced leukemia development. AML1-ETO-W692A loses N-CoR binding at NHR4, displays attenuated transcriptional repression ability and decreased cellular dysregulation, and promotes leukemia in vivo. These results support the importance of the degree of dysregulation by AML1-ETO in cellular transformation and demonstrate that AML1-ETO-W692A can be used as an effective experimental model for determining which factors compromise the leukemogenic potential of AML1-ETO.

RUNX1a enhances hematopoietic lineage commitment from human embryonic stem cells and inducible pluripotent stem cells.

Advancements in human pluripotent stem cell (hPSC) research have potential to revolutionize therapeutic transplantation. It has been demonstrated that transcription factors may play key roles in regulating maintenance, expansion, and differentiation of hPSCs. In addition to its regulatory functions in hematopoiesis and blood-related disorders, the transcription factor RUNX1 is also required for the formation of definitive blood stem cells. In this study, we demonstrated that expression of endogenous RUNX1a, an isoform of RUNX1, parallels with lineage commitment and hematopoietic emergence from hPSCs, including both human embryonic stem cells and inducible pluripotent stem cells. In a defined hematopoietic differentiation system, ectopic expression of RUNX1a facilitates emergence of hematopoietic progenitor cells (HPCs) and positively regulates expression of mesoderm and hematopoietic differentiation-related factors, including Brachyury, KDR, SCL, GATA2, and PU.1. HPCs derived from RUNX1a hPSCs show enhanced expansion ability, and the ex vivo-expanded cells are capable of differentiating into multiple lineages. Expression of RUNX1a in embryoid bodies (EBs) promotes definitive hematopoiesis that generates erythrocytes with ß-globin production. Moreover, HPCs generated from RUNX1a EBs possess ≥9-week repopulation ability and show multilineage hematopoietic reconstitution in vivo. Together, our results suggest that RUNX1a facilitates the process of producing therapeutic HPCs from hPSCs.

SON protein regulates GATA-2 through transcriptional control of the microRNA 23a~27a~24-2 cluster.

SON is a DNA- and RNA-binding protein localized in nuclear speckles. Although its function in RNA splicing for effective cell cycle progression and genome stability was recently unveiled, other mechanisms of SON functions remain unexplored. Here, we report that SON regulates GATA-2, a key transcription factor involved in hematopoietic stem cell maintenance and differentiation. SON is highly expressed in undifferentiated hematopoietic stem/progenitor cells and leukemic blasts. SON knockdown leads to significant depletion of GATA-2 protein with marginal down-regulation of GATA-2 mRNA. We show that miR-27a is up-regulated upon SON knockdown and targets the 3'-UTR of GATA-2 mRNA in hematopoietic cells. Up-regulation of miR-27a was due to activation of the promoter of the miR-23a∼27a∼24-2 cluster, suggesting that SON suppresses this promoter to lower the microRNAs from this cluster. Our data revealed a previously unidentified role of SON in microRNA production via regulating the transcription process, thereby modulating GATA-2 at the protein level during hematopoietic differentiation.

PRMT1 interacts with AML1-ETO to promote its transcriptional activation and progenitor cell proliferative potential.

Fusion protein AML1-ETO, resulting from t(8;21) translocation, is highly related to leukemia development. It has been reported that full-length AML1-ETO blocks AML1 function and requires additional mutagenic events to promote leukemia. We have previously shown that the expression of AE9a, a splice isoform of AML1-ETO, can rapidly cause leukemia in mice. To understand how AML1-ETO is involved in leukemia development, we took advantage of our AE9a leukemia model and sought to identify its interacting proteins from primary leukemic cells. Here, we report the discovery of a novel AE9a binding partner PRMT1 (protein arginine methyltransferase 1). PRMT1 not only interacts with but also weakly methylates arginine 142 of AE9a. Knockdown of PRMT1 affects expression of a specific group of AE9a-activated genes. We also show that AE9a recruits PRMT1 to promoters of AE9a-activated genes, resulting in enrichment of H4 arginine 3 methylation, H3 Lys9/14 acetylation, and transcription activation. More importantly, knockdown of PRMT1 suppresses the self-renewal capability of AE9a, suggesting a potential role of PRMT1 in regulating leukemia development.

Combined gene expression and DNA occupancy profiling identifies potential therapeutic targets of t(8;21) AML.

Chromosome translocation 8q22;21q22 [t(8;21)] is commonly associated with acute myeloid leukemia (AML), and the resulting AML1-ETO fusion proteins are involved in the pathogenesis of AML. To identify novel molecular and therapeutic targets, we performed combined gene expression microarray and promoter occupancy (ChIP-chip) profiling using Lin(-)/Sca1(-)/cKit(+) cells, the major leukemia cell population, from an AML mouse model induced by AML1-ETO9a (AE9a). Approximately 30% of the identified common targets of microarray and ChIP-chip assays overlap with the human t(8;21)-gene expression molecular signature. CD45, a protein tyrosine phosphatase and a negative regulator of cytokine/growth factor receptor and JAK/STAT signaling, is among those targets. Its expression is substantially down-regulated in leukemia cells. Consequently, JAK/STAT signaling is enhanced. Re-expression of CD45 suppresses JAK/STAT activation, delays leukemia development, and promotes apoptosis of t(8;21)-positive cells. This study demonstrates the benefit of combining gene expression and promoter occupancy profiling assays to identify molecular and potential therapeutic targets in human cancers and describes a previously unappreciated signaling pathway involving t(8;21) fusion proteins, CD45, and JAK/STAT, which could be a potential novel target for treating t(8;21) AML.

An Integrated Approach using YOLOv8 and ResNet, SeResNet & Vision Transformer (ViT) Algorithms based on ROI Fracture Prediction in X-ray Images of the Elbow.

INTRODUCTION: In this study, we harnessed three cutting-edge algorithms' capabilities to refine the elbow fracture prediction process through X-ray image analysis. Employing the YOLOv8 (You only look once) algorithm, we first identified Regions of Interest (ROI) within the X-ray images, significantly augmenting fracture prediction accuracy. METHODS: Subsequently, we integrated and compared the ResNet, the SeResNet (Squeeze-and-Excitation Residual Network) ViT (Vision Transformer) algorithms to refine our predictive capabilities. Furthermore, to ensure optimal precision, we implemented a series of meticulous refinements. This included recalibrating ROI regions to enable finer-grained identification of diagnostically significant areas within the X-ray images. Additionally, advanced image enhancement techniques were applied to optimize the X-ray images' visual quality and structural clarity. RESULTS: These methodological enhancements synergistically contributed to a substantial improvement in the overall accuracy of our fracture predictions. The dataset utilized for training, testing & validation, and comprehensive evaluation exclusively comprised elbow X-ray images, where predicting the fracture with three algorithms: Resnet50; accuracy 0.97, precision 1, recall 0.95, SeResnet50; accuracy 0.97, precision 1, recall 0.95 & ViTB- 16 with high accuracy of 0.99, precision same as the other two algorithms, with a recall of 0.95. CONCLUSION: This approach has the potential to increase the precision of diagnoses, lessen the burden of radiologists, easily integrate into current medical imaging systems, and assist clinical decision-making, all of which could lead to better patient care and health outcomes overall.

Refined protocol for newly onset identification in non-obese diabetic mice: an animal-friendly, cost-effective, and efficient alternative.

BACKGROUND: Therapeutic interventions for diabetes are most effective when administered in the newly onset phase, yet determining the exact onset moment can be elusive in practice. Spontaneous autoimmune diabetes among NOD mice appears randomly between 12 and 32 weeks of age with an incidence range from 60 to 90%. Furthermore, the disease often progresses rapidly to severe diabetes within days, resulting in a very short window of newly onset phase, that poses significant challenge in early diagnosis. Conventionally, extensive blood glucose (BG) testing is typically required on large cohorts throughout several months to conduct prospective survey. We incorporated ultrasensitive urine glucose (UG) testing into an ordinary BG survey process, initially aiming to elucidate the lag period required for excessive glucose leaking from blood to urine during diabetes progression in the mouse model. RESULTS: The observations unexpectedly revealed that small amounts of glucose detected in the urine often coincide with, sometimes even a couple days prior than elevated BG is diagnosed. Accordingly, we conducted the UG-based survey protocol in another cohort that was validated to accurately identified every individual near onset, who could then be confirmed by following few BG tests to fulfill the consecutive BG + criteria. This approach required fewer than 95 BG tests, compared to over 700 tests with traditional BG survey, to diagnose all the 37-38 diabetic mice out of total 60. The average BG level at diagnosis was slightly below 350 mg/dl, lower than the approximately 400 mg/dl observed with conventional BG monitoring. CONCLUSIONS: We demonstrated a near perfect correlation between BG + and ultrasensitive UG + results in prospective survey with no lag period detected under twice weekly of testing frequency. This led to the refined protocol based on surveying with noninvasive UG testing, allowing for the early identification of newly onset diabetic mice with only a few BG tests required per mouse. This protocol significantly reduces the need for extensive blood sampling, lancet usage, labor, and animal distress, aligning with the 3Rs principle. It presents a convenient, accurate, and animal-friendly alternative for early diabetes diagnosis, facilitating research on diagnosis, pathogenesis, prevention, and treatment.

Evaluating the Margins of Breast Cancer Tumors by Using Digital Breast Tomosynthesis with Deep Learning: A Preliminary Assessment.

BACKGROUND: The assessment information of tumor margins is extremely important for the success of the breast cancer surgery and whether the patient undergoes a second operation. However, conducting surgical margin assessments is a time-consuming task that requires pathology-related skills and equipment, and often cannot be provided in a timely manner. To address this challenge, digital breast tomosynthesis technology was utilized to generate detailed cross-sectional images of the breast tissue and integrate deep learning algorithms for image segmentation, achieving an assessment of tumor margins during surgery. METHODS: this study utilized post-operative tissue samples from 46 patients who underwent breast-conserving treatment, and generated image sets using digital breast tomosynthesis for the training and evaluation of deep learning models. RESULTS: Deep learning algorithms effectively identifying the tumor area. They achieved a Mean Intersection over Union (MIoU) of 0.91, global accuracy of 99%, weighted IoU of 44%, precision of 98%, recall of 83%, F1 score of 89%, and dice coefficient of 93% on the training dataset; for the testing dataset, MIoU was at 83%, global accuracy at 97%, weighted IoU at 38%, precision at 87%, recall rate at 69%, F1 score at 76%, dice coefficient at 86%. CONCLUSIONS: The initial evaluation suggests that the deep learning-based image segmentation method is highly accurate in measuring breast tumor margins. This helps provide information related to tumor margins during surgery, and by using different datasets, this research method can also be applied to the surgical margin assessment of various types of tumors.

Improving Breast Cancer Detection and Diagnosis through Semantic Segmentation Using the Unet3+ Deep Learning Framework.

We present an analysis and evaluation of breast cancer detection and diagnosis using segmentation models. We used an advanced semantic segmentation method and a deep convolutional neural network to identify the Breast Imaging Reporting and Data System (BI-RADS) lexicon for breast ultrasound images. To improve the segmentation results, we used six models to analyse 309 patients, including 151 benign and 158 malignant tumour images. We compared the Unet3+ architecture with several other models, such as FCN, Unet, SegNet, DeeplabV3+ and pspNet. The Unet3+ model is a state-of-the-art, semantic segmentation architecture that showed optimal performance with an average accuracy of 82.53% and an average intersection over union (IU) of 52.57%. The weighted IU was found to be 89.14% with a global accuracy of 90.99%. The application of these types of segmentation models to the detection and diagnosis of breast cancer provides remarkable results. Our proposed method has the potential to provide a more accurate and objective diagnosis of breast cancer, leading to improved patient outcomes.

Cryptococcal granulomas of basal ganglia due to Cryptococcus neoformans in a cat: a case report and literature review.

A 3-year-old spayed female domestic short-haired cat presented with a head turning to the left, circling to the right, seizures, and opisthotonos for approximately one month. Neurological examination revealed a deficit in the postural reaction of the left limbs and visual abnormalities. Forensic computed tomography revealed a hyperattenuating round mass of 1.3 cm diameter with a hypoattenuating center in the right hemisphere. Histopathology showed multifocal granuloma lesions with the major mass mostly affecting the right basal ganglia. Cryptococcus neoformans variety grubii molecular type VNI/ST31 was isolated from the cryptococcal granulomas. This report highlights the epidemiological distribution and differential diagnosis of a feline central nervous system cryptococcosis caused by C. neoformans that occurred in an Asian country.

A Novel 16S rRNA PCR-Restriction Fragment Length Polymorphism Assay to Accurately Distinguish Zoonotic Capnocytophaga canimorsus and C. cynodegmi.

The zoonotic bacteria Capnocytophaga canimorsus and C. cynodegmi, the predominant Capnocytophaga species in the canine oral biota, can cause human local wound infections or lethal sepsis, usually transmitted through dog bites. Molecular surveying of these Capnocytophaga species using conventional 16S rRNA-based PCR is not always accurate due to their high genetic homogeneity. In this study, we isolated Capnocytophaga spp. from the canine oral cavity and identified them using 16S rRNA and phylogenetic analysis. A novel 16S rRNA PCR-restriction fragment length polymorphism (RFLP) method was designed based on our isolates and validated using published C. canimorsus and C. cynodegmi 16S rRNA sequences. The results showed that 51% of dogs carried Capnocytophaga spp. Among these, C. cynodegmi (47/98, 48%) was the predominant isolated species along with one strain of C. canimorsus (1/98, 1%). Alignment analysis of 16S rRNA sequences revealed specific site nucleotide diversity in 23% (11/47) of the C. cynodegmi isolates, which were misidentified as C. canimorsus using previously reported species-specific PCR. Four RFLP types could be classified from all the isolated Capnocytophaga strains. The proposed method demonstrates superior resolution in distinguishing C. cynodegmi (with site-specific polymorphism) from C. canimorsus and especially in distinguishing C. canimorsus from other Capnocytophaga species. After in silico validation, this method was revealed to have an overall detection accuracy of 84%; notably, accuracy reached 100% in C. canimorsus strains isolated from human patients. Overall, the proposed method is a useful molecular tool for the epidemiological study of Capnocytophaga in small animals and for the rapid diagnosis of human C. canimorsus infections. IMPORTANCE With the increased number of small animal breeding populations, zoonotic infections associated with small animals need to be taken more seriously. Capnocytophaga canimorsus and C. cynodegmi are part of common biota in the mouths of small animals and can cause human infections through bites or scratches. In this study, C. cynodegmi with site-specific 16S rRNA sequence polymorphisms was erroneously identified as C. canimorsus during the investigation of canine Capnocytophaga by conventional PCR. Consequently, the prevalence of C. canimorsus is incorrectly overestimated in epidemiological studies in small animals. We designed a new 16S rRNA PCR-RFLP method to accurately distinguish zoonotic C. canimorsus from C. cynodegmi. After validation against published Capnocytophaga strains, this novel molecular method had high accuracy and could detect 100% of C. canimorsus-strain infections in humans. This novel method can be used for epidemiological studies and the diagnosis of human Capnocytophaga infection following exposure to small animals.

Whole-genome sequencing and identification of Morganella morganii KT pathogenicity-related genes.

BACKGROUND: The opportunistic enterobacterium, Morganella morganii, which can cause bacteraemia, is the ninth most prevalent cause of clinical infections in patients at Changhua Christian Hospital, Taiwan. The KT strain of M. morganii was isolated during postoperative care of a cancer patient with a gallbladder stone who developed sepsis caused by bacteraemia. M. morganii is sometimes encountered in nosocomial settings and has been causally linked to catheter-associated bacteriuria, complex infections of the urinary and/or hepatobiliary tracts, wound infection, and septicaemia. M. morganii infection is associated with a high mortality rate, although most patients respond well to appropriate antibiotic therapy. To obtain insights into the genome biology of M. morganii and the mechanisms underlying its pathogenicity, we used Illumina technology to sequence the genome of the KT strain and compared its sequence with the genome sequences of related bacteria. RESULTS: The 3,826,919-bp sequence contained in 58 contigs has a GC content of 51.15% and includes 3,565 protein-coding sequences, 72 tRNA genes, and 10 rRNA genes. The pathogenicity-related genes encode determinants of drug resistance, fimbrial adhesins, an IgA protease, haemolysins, ureases, and insecticidal and apoptotic toxins as well as proteins found in flagellae, the iron acquisition system, a type-3 secretion system (T3SS), and several two-component systems. Comparison with 14 genome sequences from other members of Enterobacteriaceae revealed different degrees of similarity to several systems found in M. morganii. The most striking similarities were found in the IS4 family of transposases, insecticidal toxins, T3SS components, and proteins required for ethanolamine use (eut operon) and cobalamin (vitamin B12) biosynthesis. The eut operon and the gene cluster for cobalamin biosynthesis are not present in the other Proteeae genomes analysed. Moreover, organisation of the 19 genes of the eut operon differs from that found in the other non-Proteeae enterobacterial genomes. CONCLUSIONS: This is the first genome sequence of M. morganii, which is a clinically relevant pathogen. Comparative genome analysis revealed several pathogenicity-related genes and novel genes not found in the genomes of other members of Proteeae. Thus, the genome sequence of M. morganii provides important information concerning virulence and determinants of fitness in this pathogen.

Risk Factors for Antimicrobial Resistance of Staphylococcus Species Isolated from Dogs with Superficial Pyoderma and Their Owners.

The microbial communities on the skin of dogs include several species of bacteria, which contribute to skin health and disease. Staphylococcus pseudintermedius, cultured at high frequency from the skin of dogs, is an opportunistic pathogen causing superficial pyoderma. Effective treatment against S. pseudintermedius infections is an important issue in veterinary medicine. However, multiple antibiotic-resistant mechanisms gradually developed by bacteria make treatment more challenging nowadays. Drug-resistant genes may have the chance to be transferred from infected dogs to other staphylococci in humans. The objective of this survey is to investigate the bacterial species that cause canine superficial pyoderma and characterize the antibiotic-resistant profiles and drug-resistant genes of isolated S. pseudintermedius. In addition, the possible risk factors causing S. pseudintermedius colonizing owners were also evaluated by a questionnaire survey. Sixty-five bacteria were isolated from dogs with superficial pyoderma, which included 47 S. pseudintermedius (72.3%), 12 other staphylococci (18.5%), 4 other Gram-positive bacteria (6.2%) and 2 Gram-negative bacteria (3.1%). Strains containing mecA and blaZ genes showed multiple-drug resistance characteristics. Dogs that received antimicrobial treatment within a recent month were at significantly higher risk of MRSP infections. Only five S. pseudintermedius strains (8.33%) were isolated from 60 samples of owners. Risk factor analysis indicated there was no significant association between S. pseudintermedius isolated from dogs and owners, but the "Keeping three or more dogs" and "Dogs can lick the owner's face" have high odds ratios of 3.503 and 5.712, respectively. MRSP isolates belonged to three different dru types, including dt11y (29.41%), dt11a (47.06%) and dt10cp (23.53%). In conclusion, the major pathogen of canine superficial pyoderma is found to be S. pseudintermedius in Taiwan, and isolates which are mecA- or blaZ-positive are generally more resistant to commonly used antibiotics. Although S. pseudintermedius isolated from the owners might be transferred from their dogs, definite risk factors should be examined in the future study.

Effect of Carbonyl Cyanide Chlorophenylhydrazone on Intrabacterial Concentration and Antimicrobial Activity of Amphenicols against Swine Resistant Actinobacillus pleuropneumoniae and Pasteurella multocida.

Effects and mechanism of carbonyl cyanide chlorophenylhydrazone (CCCP) on antimicrobial activity of florfenicol (FF) and thiamphenicol (TAP) were investigated against amphenicol-resistant Actinobacillus pleuropneumoniae and Pasteurella multocida isolated from diseased swine. Broth microdilution and time-kill assays indicated that CCCP dose-dependently and substantially (4-32 fold MIC reduction) improved amphenicol antimicrobial activity. When combined with CCCP at the lowest literature reported dose (2-5 µg/mL), 85% FF resistant A. pleuropneumoniae and 92% resistant P. multocida showed significantly reduced FF MICs (≥ 4-fold). In contrast, none or few of the susceptible A. pleuropneumoniae and P. multocida had FF MICs reduction ≥ 4-fold. 90% FF resistant A. pleuropneumoniae and 96% resistant P. multocida carried the floR gene, indicating strong association with the FloR efflux pump. With CCCP, the intracellular FF concentration increased by 71% in floR+ resistant A. pleuropneumoniae and 156% in floR+ resistant P. multocida strains but not the susceptible strains. The degree of reduction in TAP MICs was found consistently in parallel to FF for both bacteria. Taken together, partially attributed to blockage of drug-efflux, the combination of FF or TAP with CCCP at sub-cytotoxic concentrations was demonstrated and showed feasibility to combat amphenicol-resistant A. pleuropneumoniae and P. multocida isolated from diseased swine.