Self-Trained Convolutional Neural Network (CNN) for Tuberculosis Diagnosis in Medical Imaging.

Background Tuberculosis (TB) is a serious infectious disease that primarily affects the lungs. Despite advancements in the medical industry, TB remains a significant global health challenge. Early and accurate detection of TB is crucial for effective treatment and reducing transmission. This article presents a deep learning approach using convolutional neural networks (CNNs) to improve TB detection in chest X-ray images. Methods For the dataset, we collected 7000 images from Kaggle.com, of which 3500 exhibit tuberculosis evidence and the remaining 3500 are normal. Preprocessing techniques such as wavelet transformation, contrast-limited adaptive histogram equalisation (CLAHE), and gamma correction were applied to enhance the image quality. Random flipping, random rotation, random resizing, and random rescaling were among the techniques employed to increase dataset variability and model robustness. Convolutional, max-pooling, flatten, and dense layers comprised the CNN model architecture. For binary classification, sigmoid activation was utilised in the output layer and rectified linear unit (ReLU) activation in the input and hidden layers. Results The CNN model achieved an accuracy of ~96.57% in detecting TB from chest X-ray images, demonstrating the effectiveness of deep learning, particularly CNNs, in this application. Self-trained CNNs have optimised the results as compared to the transfer learning of various pre-trained models. Conclusion This study shows how well deep learning-in particular, CNNs-performs in the identification of tuberculosis. Subsequent efforts have to give precedence to optimising the model by obtaining more extensive datasets from the local hospitals and localities, which are vulnerable to TB, and stress the possibility of augmenting diagnostic knowledge in medical imaging via machine learning methodologies.

Observational study on the clinical profile and treatment outcome on long-term follow-up of COVID-19 associated mucormycosis.

MATERIALS AND METHODS: Patients diagnosed with COVID-19 associated mucormycosis were followed up for 6 months to study the clinical profile, readmissions, long-term treatment outcome and the mortality rate. RESULTS: Among 37 patients with COVID-19 associated mucormycosis, the mortality rate was 33.3 %, 42.9% and 100 % among patients with mild, moderate and severe COVID-19 infection. One month after discharge, among the 20 patients who survived, 10 (50 %) patients had worsening symptoms and required readmission. Nine patients required readmission for amphotericin and 1 patient was admitted for surgical intervention. On follow-up at 1 month, 30 % (6/20) patients became asymptomatic. However, at 3 months, 45 % (9/20) of the patients were asymptomatic. At 6 months of follow-up, 80 % (16/20) were asymptomatic. At 6 months, one each had residual abnormalities like visual loss in one eye, visual field deficit, change in voice and residual weakness of the limbs along with cranial nerve paresis. CONCLUSION: The follow-up study revealed that a significant number of patients required readmission within the first month, but most of the patients became asymptomatic by 6 months. The readmission rate was higher in patients who received a shorter duration of amphotericin.

A novel hybridization capture method for direct whole genome sequencing of clinical specimens to inform Legionnaires' disease investigations.

The unprecedented precision and resolution of whole genome sequencing (WGS) can provide definitive identification of infectious agents for epidemiological outbreak tracking. WGS approaches, however, are frequently impeded by low pathogen DNA recovery from available primary specimens or unculturable samples. A cost-effective hybrid capture assay for Legionella pneumophila WGS analysis directly on primary specimens was developed. DNA from a diverse range of sputum and autopsy specimens PCR-positive for L. pneumophila serogroup 1 (LPSG1) was enriched with this method, and WGS was performed. All tested specimens were determined to be enriched for Legionella reads (up to 209,000-fold), significantly improving the discriminatory power to compare relatedness when no clinical isolate was available. We found the WGS data from some enriched specimens to differ by less than five single-nucleotide polymorphisms (SNPs) when compared to the WGS data of a matched culture isolate. This testing and analysis retrospectively provided previously unconfirmed links to environmental sources for clinical specimens of sputum and autopsy lung tissue. The latter provided the additional information needed to identify the source of these culture-negative cases associated with the South Bronx 2015 Legionnaires' disease (LD) investigation in New York City. This new method provides a proof of concept for future direct clinical specimen hybrid capture enrichment combined with WGS and bioinformatic analysis during outbreak investigations.IMPORTANCELegionnaires' disease (LD) is a severe and potentially fatal type of pneumonia primarily caused by inhalation of Legionella-contaminated aerosols from man-made water or cooling systems. LD remains extremely underdiagnosed as it is an uncommon form of pneumonia and relies on clinicians including it in the differential and requesting specialized testing. Additionally, it is challenging to obtain clinical lower respiratory specimens from cases with LD, and when available, culture requires specialized media and growth conditions, which are not available in all microbiology laboratories. In the current study, a method for Legionella pneumophila using hybrid capture by RNA baiting was developed, which allowed us to generate sufficient genome resolution from L. pneumophila serogroup 1 PCR-positive clinical specimens. This new approach offers an additional tool for surveillance of future LD outbreaks where isolation of Legionella is not possible and may help solve previously unanswered questions from past LD investigations.

Deep learning on photoacoustic tomography to remove image distortion due to inaccurate measurement of the scanning radius.

Photoacoustic tomography (PAT) is a non-invasive, non-ionizing hybrid imaging modality that holds great potential for various biomedical applications and the incorporation with deep learning (DL) methods has experienced notable advancements in recent times. In a typical 2D PAT setup, a single-element ultrasound detector (USD) is used to collect the PA signals by making a 360° full scan of the imaging region. The traditional backprojection (BP) algorithm has been widely used to reconstruct the PAT images from the acquired signals. Accurate determination of the scanning radius (SR) is required for proper image reconstruction. Even a slight deviation from its nominal value can lead to image distortion compromising the quality of the reconstruction. To address this challenge, two approaches have been developed and examined herein. The first framework includes a modified version of dense U-Net (DUNet) architecture. The second procedure involves a DL-based convolutional neural network (CNN) for image classification followed by a DUNet. The first protocol was trained with heterogeneous simulated images generated from three different phantoms to learn the relationship between the reconstructed and the corresponding ground truth (GT) images. In the case of the second scheme, the first stage was trained with the same heterogeneous dataset to classify the image type and the second stage was trained individually with the appropriate images. The performance of these architectures has been tested on both simulated and experimental images. The first method can sustain SR deviation up to approximately 6% for simulated images and 5% for experimental images and can accurately reproduce the GTs. The proposed DL-approach extends the limits further (approximately 7% and 8% for simulated and experimental images, respectively). Our results suggest that classification-based DL method does not need a precise assessment of SR for accurate PAT image formation.

Posterior Gastric Perforation with an Opening in Transverse Mesocolon: A Rare Case Report.

Posterior gastric perforation is a very rare finding, difficult to diagnose due to the insidious onset of upper abdominal symptoms, and no air under the diaphragm on X-ray. Posterior gastric perforation which opens into transverse mesocolon is even rarer. This is a case report done to entail such a rare case, with only two cases reported in the past. We present the case of a 21-year-old female with pain in the epigastric region spreading to involve the whole abdomen, fever, vomiting, and anorexia. In our case, radiological findings revealed pneumoperitoneum. Intraoperatively, a tract was identified between the posterior wall of the stomach and transverse mesocolon. Tract was excised and primary repair was done using the Graham patch method.

Whole genome sequencing of human Borrelia burgdorferi isolates reveals linked blocks of accessory genome elements located on plasmids and associated with human dissemination.

Lyme disease is the most common vector-borne disease in North America and Europe. The clinical manifestations of Lyme disease vary based on the genospecies of the infecting Borrelia burgdorferi spirochete, but the microbial genetic elements underlying these associations are not known. Here, we report the whole genome sequence (WGS) and analysis of 299 B. burgdorferi (Bb) isolates derived from patients in the Eastern and Midwestern US and Central Europe. We develop a WGS-based classification of Bb isolates, confirm and extend the findings of previous single- and multi-locus typing systems, define the plasmid profiles of human-infectious Bb isolates, annotate the core and strain-variable surface lipoproteome, and identify loci associated with disseminated infection. A core genome consisting of ~900 open reading frames and a core set of plasmids consisting of lp17, lp25, lp36, lp28-3, lp28-4, lp54, and cp26 are found in nearly all isolates. Strain-variable (accessory) plasmids and genes correlate strongly with phylogeny. Using genetic association study methods, we identify an accessory genome signature associated with dissemination in humans and define the individual plasmids and genes that make up this signature. Strains within the RST1/WGS A subgroup, particularly a subset marked by the OspC type A genotype, have increased rates of dissemination in humans. OspC type A strains possess a unique set of strongly linked genetic elements including the presence of lp56 and lp28-1 plasmids and a cluster of genes that may contribute to their enhanced virulence compared to other genotypes. These features of OspC type A strains reflect a broader paradigm across Bb isolates, in which near-clonal genotypes are defined by strain-specific clusters of linked genetic elements, particularly those encoding surface-exposed lipoproteins. These clusters of genes are maintained by strain-specific patterns of plasmid occupancy and are associated with the probability of invasive infection.

Whole genome sequencing of Borrelia burgdorferi isolates reveals linked clusters of plasmid-borne accessory genome elements associated with virulence.

Lyme disease is the most common vector-borne disease in North America and Europe. The clinical manifestations of Lyme disease vary based on the genospecies of the infecting Borrelia burgdorferi spirochete, but the microbial genetic elements underlying these associations are not known. Here, we report the whole genome sequence (WGS) and analysis of 299 patient-derived B. burgdorferi sensu stricto ( Bbss ) isolates from patients in the Eastern and Midwestern US and Central Europe. We develop a WGS-based classification of Bbss isolates, confirm and extend the findings of previous single- and multi-locus typing systems, define the plasmid profiles of human-infectious Bbss isolates, annotate the core and strain-variable surface lipoproteome, and identify loci associated with disseminated infection. A core genome consisting of ∻800 open reading frames and a core set of plasmids consisting of lp17, lp25, lp36, lp28-3, lp28-4, lp54, and cp26 are found in nearly all isolates. Strain-variable (accessory) plasmids and genes correlate strongly with phylogeny. Using genetic association study methods, we identify an accessory genome signature associated with dissemination and define the individual plasmids and genes that make up this signature. Strains within the RST1/WGS A subgroup, particularly a subset marked by the OspC type A genotype, are associated with increased rates of dissemination. OspC type A strains possess a unique constellation of strongly linked genetic changes including the presence of lp56 and lp28-1 plasmids and a cluster of genes that may contribute to their enhanced virulence compared to other genotypes. The patterns of OspC type A strains typify a broader paradigm across Bbss isolates, in which genetic structure is defined by correlated groups of strain-variable genes located predominantly on plasmids, particularly for expression of surface-exposed lipoproteins. These clusters of genes are inherited in blocks through strain-specific patterns of plasmid occupancy and are associated with the probability of invasive infection.

Genomic Analysis of Vancomycin-Resistant Staphylococcus aureus Isolates from the 3rd Case Identified in the United States Reveals Chromosomal Integration of the vanA Locus.

Vancomycin-resistant Staphylococcus aureus (VRSA) is a human pathogen of significant public health concern. Although the genome sequences of individual VRSA isolates have been published over the years, very little is known about the genetic changes of VRSA within a patient over time. A total of 11 VRSA, 3 vancomycin-resistant enterococci (VRE), and 4 methicillin-resistant S. aureus (MRSA) isolates, collected over a period of 4.5 months in 2004 from a patient in a long-term-care facility in New York State, were sequenced. A combination of long- and short-read sequencing technologies was used to obtain closed assemblies for chromosomes and plasmids. Our results indicate that a VRSA isolate emerged as the result of the transfer of a multidrug resistance plasmid from a coinfecting VRE to an MRSA isolate. The plasmid then integrated into the chromosome via homologous recombination mediated between two regions derived from remnants of transposon Tn5405. Once integrated, the plasmid underwent further reorganization in one isolate, while two others lost the staphylococcal cassette chromosome mec element (SCCmec) determinant that confers methicillin-resistance. The results presented here explain how a few recombination events can lead to multiple pulsed-field gel electrophoresis (PFGE) patterns that could be mistaken for vastly different strains. A vanA gene cluster that is located on a multidrug resistance plasmid that is integrated into the chromosome could result in the continuous propagation of resistance, even in the absence of selective pressure from antibiotics. The genome comparison presented here sheds light on the emergence and evolution of VRSA within a single patient that will enhance our understanding VRSA genetics. IMPORTANCE High-level vancomycin-resistant Staphylococcus aureus (VRSA) began to emerge in the United States in 2002 and has since then been reported worldwide. Our study reports the closed genome sequences of multiple VRSA isolates obtained in 2004 from a single patient in New York State. Our results show that the vanA resistance locus is located on a mosaic plasmid that confers resistance to multiple antibiotics. In some isolates, this plasmid integrated into the chromosome via homologous recombination between two ant(6)-sat4-aph(3') antibiotic resistance loci. This is, to our knowledge, the first report of a chromosomal vanA locus in VRSA; the effect of this integration event on MIC values and plasmid stability in the absence of antibiotic selection remains poorly understood. These findings highlight the need for a better understanding of the genetics of the vanA locus and plasmid maintenance in S. aureus to address the increase of vancomycin resistance in the health care setting.

Improved Residual Network based on norm-preservation for visual recognition.

Residual Network (ResNet) achieves deeper and wider networks with high-performance gains, representing a powerful convolutional neural network architecture. In this paper, we propose architectural refinements to ResNet that address the information flow through several layers of the network, including the input stem, downsampling block, projection shortcut, and identity blocks. We will show that our collective refinements facilitate stable backpropagation by preserving the norm of the error gradient within the residual blocks, which can reduce the optimization difficulties of training very deep networks. Our proposed modifications enhance the learning dynamics, resulting in high accuracy and inference performance by enforcing norm-preservation throughout the network training. The effectiveness of our method is verified by extensive experimental results on five computer vision tasks, including image classification (ImageNet and CIFAR-100), video classification (Kinetics-400), multi-label image recognition (MS-COCO), object detection and semantic segmentation (PASCAL VOC). We also empirically show consistent improvements in generalization performance when applying our modifications over different networks to provide new insights and inspire new architectures. The source code is publicly available at: https://github.com/bharatmahaur/LeNo.

Comparative analysis of multiplexed PCR and short- and long-read whole genome sequencing to investigate a large Klebsiella pneumoniae outbreak in New York State.

In 2017, the New York State Department of Health investigated a large Klebsiella pneumoniae outbreak in a health care facility. A retrospective analysis was conducted to compare the use of multiple molecular typing methods for characterizing the outbreak. Forty-four isolates were characterized using the rapid real-time PCR OpGen Acuitas® AMR Gene Panel. Additionally, short-read whole genome sequencing (WGS) analysis was used to identify antimicrobial resistance (AMR) genes and assess isolate relatedness. Long-read Oxford Nanopore MinION WGS was used to characterize the plasmid content of a subset of isolates. All methods showed overall concordance, identifying four clusters, with a few discrepancies in the clustering of individual isolates. Though short- and long-read WGS results provided a more nuanced understanding of the molecular epidemiology of this outbreak, this study highlights the utility of the Acuitas® PCR-based approach, which can more easily be performed by health care facilities, for rapid clustering of patient isolates.

Depletion of the Microbiota Has a Modest but Important Impact on the Fungal Burden of the Heart and Lungs during Early Systemic Candida auris Infection in Neutropenic Mice.

The progression and systemic pathobiology of C. auris in the absence of a microbiota have not been described. Here, we describe the influence of the microbiota during the first 5 days of C. auris infection in germ-free or antibiotic-depleted mice. Depletion of the bacterial microbiota in both germ-free and antibiotic-depleted models results in a modest but important increase in the early stages of C. auris infection. Particularly the heart and lungs, followed by the cecum, uterus, and stomach, of intravenously (i.v.) infected neutropenic mice showed significant fungal organ burden. Understanding disease progression and pathobiology of C. auris in individuals with a depleted microbiota could potentially help in the development of care protocols that incorporate supplementation or restoration of the microbiota before invasive procedures, such as transplantation surgeries.

ATD: Augmenting CP Tensor Decomposition by Self Supervision.

Tensor decompositions are powerful tools for dimensionality reduction and feature interpretation of multidimensional data such as signals. Existing tensor decomposition objectives (e.g., Frobenius norm) are designed for fitting raw data under statistical assumptions, which may not align with downstream classification tasks. In practice, raw input tensor can contain irrelevant information while data augmentation techniques may be used to smooth out class-irrelevant noise in samples. This paper addresses the above challenges by proposing augmented tensor decomposition (ATD), which effectively incorporates data augmentations and self-supervised learning (SSL) to boost downstream classification. To address the non-convexity of the new augmented objective, we develop an iterative method that enables the optimization to follow an alternating least squares (ALS) fashion. We evaluate our proposed ATD on multiple datasets. It can achieve 0.8% ~ 2.5% accuracy gain over tensor-based baselines. Also, our ATD model shows comparable or better performance (e.g., up to 15% in accuracy) over self-supervised and autoencoder baselines while using less than 5% of learnable parameters of these baseline models.

The role of chemical shift magnetic resonance imaging in differentiating osteoporotic benign and malignant vertebral marrow lesions.

PURPOSE: To evaluate the usefulness of chemical shift imaging (CSI) in differentiating benign osteoporotic and malignant vertebral marrow lesions. MATERIAL AND METHODS: Patients undergoing spinal magnetic resonance imaging (MRI) for back pain, which showed altered marrow signal intensity on conventional MRI sequences, were included in the study. Patients with acute traumatic vertebral fractures, infective spondylodiscitis, paravertebral collections, etc. were excluded. The patients underwent CSI. In-phase and opposed-phase images were taken to calculate the signal intensity ratio (SIR) of the abnormal vertebra. The SIR of the mean signal intensity measured on opposed-phase to mean signal intensity measured on in-phase images was measured and recorded. RESULTS: The studied population included 30 patients, in whom 58 vertebrae were accessed, which included 38 dorsal, 18 lumbar, 1 sacral, and 1 cervical. Out of 58 vertebrae, 46 (79%) were malignant and 12 (20%) were benign. The mean CSI/SIR of malignant lesions was 0.96 and the mean SIR of benign lesions was 0.76. CONCLUSIONS: Conventional MRI sequences cannot always differentiate between benign and malignant lesions. So newer sequences like CSI have been developed. CSI SIR can be used as a new tool in differentiating benign osteoporotic and malignant vertebral marrow lesions.

Whole-Genome Sequencing of SARS-CoV-2: Assessment of the Ion Torrent AmpliSeq Panel and Comparison with the Illumina MiSeq ARTIC Protocol.

Fast and effective methods are needed for sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome to track genetic mutations and to identify new and emerging variants during the ongoing pandemic. The objectives were to assess the performance of the SARS-CoV-2 AmpliSeq research panel and S5 plug-in analysis tools for whole-genome sequencing analysis of SARS-CoV-2 and to compare the results with those obtained with the MiSeq-based ARTIC analysis pipeline, using metrics such as depth, coverage, and concordance of single-nucleotide variant (SNV) calls. A total of 191 clinical specimens and a single cultured isolate were extracted and sequenced with AmpliSeq technology and analysis tools. Of the 191 clinical specimens, 83 (with threshold cycle [CT] values of 15.58 to 32.54) were also sequenced using an Illumina MiSeq-based method with the ARTIC analysis pipeline, for direct comparison. A total of 176 of the 191 clinical specimens sequenced on the S5XL system and prepared using the SARS-CoV-2 research panel had nearly complete coverage (>98%) of the viral genome, with an average depth of 5,031×. Similar coverage levels (>98%) were observed for 81/83 primary specimens that were sequenced with both methods tested. The sample with the lowest viral load (CT value of 32.54) achieved 89% coverage using the MiSeq method and failed to sequence with the AmpliSeq method. Consensus sequences produced by each method were identical for 81/82 samples in areas of equal coverage, with a single difference present in one sample. The AmpliSeq approach is as effective as the Illumina-based method using ARTIC v3 amplification for sequencing SARS-CoV-2 directly from patient specimens across a range of viral loads (CT values of 15.56 to 32.54 [median, 22.18]). The AmpliSeq workflow is very easily automated with the Ion Chef and S5 instruments and requires less training and experience with next-generation sequencing sample preparation than the Illumina workflow.

Regulatory roles of Escherichia coli 5' UTR and ORF-internal RNAs detected by 3' end mapping.

Many bacterial genes are regulated by RNA elements in their 5´ untranslated regions (UTRs). However, the full complement of these elements is not known even in the model bacterium Escherichia coli. Using complementary RNA-sequencing approaches, we detected large numbers of 3´ ends in 5´ UTRs and open reading frames (ORFs), suggesting extensive regulation by premature transcription termination. We documented regulation for multiple transcripts, including spermidine induction involving Rho and translation of an upstream ORF for an mRNA encoding a spermidine efflux pump. In addition to discovering novel sites of regulation, we detected short, stable RNA fragments derived from 5´ UTRs and sequences internal to ORFs. Characterization of three of these transcripts, including an RNA internal to an essential cell division gene, revealed that they have independent functions as sRNA sponges. Thus, these data uncover an abundance of cis- and trans-acting RNA regulators in bacterial 5´ UTRs and internal to ORFs.

In most organisms, specific segments of a cell's genetic information are copied to form single-stranded molecules of various sizes and purposes. Each of these RNA molecules, as they are known, is constructed as a chain that starts at the 5´ end and terminates at the 3´ end. Certain RNAs carry the information present in a gene, which provides the instructions that a cell needs to build proteins. Some, however, are 'non-coding' and instead act to fine-tune the activity of other RNAs. These regulatory RNAs can be separate from the RNAs they control, or they can be embedded in the very sequences they regulate; new evidence also shows that certain regulatory RNAs can act in both ways. Many regulatory RNAs are yet to be catalogued, even in simple, well-studied species such as the bacterium Escherichia coli. Here, Adams et al. aimed to better characterize the regulatory RNAs present in E. coli by mapping out the 3´ ends of every RNA molecule in the bacterium. This revealed many new regulatory RNAs and offered insights into where these sequences are located. For instance, the results show that several of these RNAs were embedded within RNA produced from larger genes. Some were nested in coding RNAs, and were parts of a longer RNA sequence that is adjacent to the protein coding segment. Others, however, were present within the instructions that code for a protein. The work by Adams et al. reveals that regulatory RNAs can be located in unexpected places, and provides a method for identifying them. This can be applied to other types of bacteria, in particular in species with few known RNA regulators.

RecipeDB: a resource for exploring recipes.

Cooking is the act of turning nature into the culture, which has enabled the advent of the omnivorous human diet. The cultural wisdom of processing raw ingredients into delicious dishes is embodied in their cuisines. Recipes thus are the cultural capsules that encode elaborate cooking protocols for evoking sensory satiation as well as providing nourishment. As we stand on the verge of an epidemic of diet-linked disorders, it is eminently important to investigate the culinary correlates of recipes to probe their association with sensory responses as well as consequences for nutrition and health. RecipeDB (https://cosylab.iiitd.edu.in/recipedb) is a structured compilation of recipes, ingredients and nutrition profiles interlinked with flavor profiles and health associations. The repertoire comprises of meticulous integration of 118 171 recipes from cuisines across the globe (6 continents, 26 geocultural regions and 74 countries), cooked using 268 processes (heat, cook, boil, simmer, bake, etc.), by blending over 20 262 diverse ingredients, which are further linked to their flavor molecules (FlavorDB), nutritional profiles (US Department of Agriculture) and empirical records of disease associations obtained from MEDLINE (DietRx). This resource is aimed at facilitating scientific explorations of the culinary space (recipe, ingredient, cooking processes/techniques, dietary styles, etc.) linked to taste (flavor profile) and health (nutrition and disease associations) attributes seeking for divergent applications. Database URL:  https://cosylab.iiitd.edu.in/recipedb.

Nanopore MinION Sequencing Reveals Possible Transfer of bla KPC-2 Plasmid Across Bacterial Species in Two Healthcare Facilities.

Carbapenemase-producing Enterobacteriaceae are a major threat to global public health. Klebsiella pneumoniae carbapenemase (KPC) is the most commonly identified carbapenemase in the United States and is frequently found on mobile genetic elements including plasmids, which can be horizontally transmitted between bacteria of the same or different species. Here we describe the results of an epidemiological investigation of KPC-producing bacteria at two healthcare facilities. Using a combination of short-read and long-read whole-genome sequencing, we identified an identical 44 kilobase plasmid carrying the bla KPC-2 gene in four bacterial isolates belonging to three different species (Citrobacter freundii, Klebsiella pneumoniae, and Escherichia coli). The isolates in this investigation were collected from patients who were epidemiologically linked in a region in which KPC was uncommon, suggesting that the antibiotic resistance plasmid was transmitted between these bacterial species. This investigation highlights the importance of long-read sequencing in investigating the relatedness of bacterial plasmids, and in elucidating potential plasmid-mediated outbreaks caused by antibiotic resistant bacteria.

Origin of 3 Rabid Terrestrial Animals in Raccoon Rabies Virus-Free Zone, Long Island, New York, USA, 2016-2017.

During 2016-2017, three rabid terrestrial animals were discovered in the raccoon rabies virus-free zone of Long Island, New York, USA. Whole-genome sequencing and phylogenetic analyses revealed the likely origins of the viruses, enabling the rabies outbreak response (often costly and time-consuming) to be done less expensively and more efficiently.