Methicillin-Resistant Staphylococcus aureus USA300 Clone in Long-Term Care Facility

We performed a longitudinal analysis of 661 methicillin-resistant Staphylococcus aureus (MRSA) isolates obtained from patients in a long-term care facility. USA300 clone increased from 11.3% of all MRSA isolates in 2002 to 64.0% in 2006 (p<0.0001) and was mostly recovered from skin or skin structures (64.3% vs. 27.0% for non-USA300 MRSA; p<0.0001)

LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained deep networks on ImageNet and vision-language foundation models trained on web-scale data are prevailing approaches, their effectiveness on medical tasks is limited due to the significant domain shift between natural and medical images. To bridge this gap, we introduce LVM-Med, the first family of deep networks trained on large-scale medical datasets. We have collected approximately 1.3 million medical images from 55 publicly available datasets, covering a large number of organs and modalities such as CT, MRI, X-ray, and Ultrasound. We benchmark several state-of-the-art self-supervised algorithms on this dataset and propose a novel self-supervised contrastive learning algorithm using a graph-matching formulation. The proposed approach makes three contributions: (i) it integrates prior pair-wise image similarity metrics based on local and global information; (ii) it captures the structural constraints of feature embeddings through a loss function constructed via a combinatorial graph-matching objective; and (iii) it can be trained efficiently end-to-end using modern gradient-estimation techniques for black-box solvers. We thoroughly evaluate the proposed LVM-Med on 15 downstream medical tasks ranging from segmentation and classification to object detection, and both for the in and out-of-distribution settings. LVM-Med empirically outperforms a number of state-of-the-art supervised, self-supervised, and foundation models. For challenging tasks such as Brain Tumor Classification or Diabetic Retinopathy Grading, LVM-Med improves previous vision-language models trained on 1 billion masks by 6-7% while using only a ResNet-50.Comment: Update Appendi

On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive sets of natural image and text data, have emerged as a promising approach. It showcases impressive learning abilities across different tasks with the need for only a limited amount of annotated samples. While numerous techniques have focused on developing better fine-tuning strategies to adapt these models for specific domains, we instead examine their robustness to domain shifts in the medical image segmentation task. To this end, we compare the generalization performance to unseen domains of various pre-trained models after being fine-tuned on the same in-distribution dataset and show that foundation-based models enjoy better robustness than other architectures. From here, we further developed a new Bayesian uncertainty estimation for frozen models and used them as an indicator to characterize the model's performance on out-of-distribution (OOD) data, proving particularly beneficial for real-world applications. Our experiments not only reveal the limitations of current indicators like accuracy on the line or agreement on the line commonly used in natural image applications but also emphasize the promise of the introduced Bayesian uncertainty. Specifically, lower uncertainty predictions usually tend to higher out-of-distribution (OOD) performance.Comment: Advances in Neural Information Processing Systems (NeurIPS) 2023, Workshop on robustness of zero/few-shot learning in foundation model

An Exploration into the Benefits of the CLIP model for Lifelog Retrieval

In this paper, we attempt to fine-tune the CLIP (Contrastive Language-Image Pre-Training) model on the Lifelog Question Answering dataset (LLQA) to investigate retrieval performance of the fine-tuned model over the zero-shot baseline model. We train the model adopting a weight space ensembling approach using a modified loss function to take into account the differences in our dataset (LLQA) when compared with the dataset the CLIP model was originally pretrained on. We further evaluate our fine-tuned model using visual as well as multimodal queries on multiple retrieval tasks, demonstrating improved performance over the zero-shot baseline model

Genetic Diversity of Arginine Catabolic Mobile Element in Staphylococcus epidermidis

BACKGROUND:The methicillin-resistant Staphylococcus aureus clone USA300 contains a novel mobile genetic element, arginine catabolic mobile element (ACME), that contributes to its enhanced capacity to grow and survive within the host. Although ACME appears to have been transferred into USA300 from S. epidermidis, the genetic diversity of ACME in the latter species remains poorly characterized. METHODOLOGY/PRINCIPAL FINDINGS:To assess the prevalence and genetic diversity of ACME, 127 geographically diverse S. epidermidis isolates representing 86 different multilocus sequence types (STs) were characterized. ACME was found in 51% (65/127) of S. epidermidis isolates. The vast majority (57/65) of ACME-containing isolates belonged to the predominant S. epidermidis clonal complex CC2. ACME was often found in association with different allotypes of staphylococcal chromosome cassette mec (SCCmec) which also encodes the recombinase function that facilities mobilization ACME from the S. epidermidis chromosome. Restriction fragment length polymorphism, PCR scanning and DNA sequencing allowed for identification of 39 distinct ACME genetic variants that differ from one another in gene content, thereby revealing a hitherto uncharacterized genetic diversity within ACME. All but one ACME variants were represented by a single S. epidermidis isolate; the singular variant, termed ACME-I.02, was found in 27 isolates, all of which belonged to the CC2 lineage. An evolutionary model constructed based on the eBURST algorithm revealed that ACME-I.02 was acquired at least on 15 different occasions by strains belonging to the CC2 lineage. CONCLUSIONS/SIGNIFICANCE:ACME-I.02 in diverse S. epidermidis isolates were nearly identical in sequence to the prototypical ACME found in USA300 MRSA clone, providing further evidence for the interspecies transfer of ACME from S. epidermidis into USA300

Panton-Valentine Leukocidin Does Play a Role in the Early Stage of Staphylococcus aureus Skin Infections: A Rabbit Model

Despite epidemiological data linking necrotizing skin infections with the production of Panton-Valentine leukocidin (PVL), the contribution of this toxin to the virulence of S. aureus has been highly discussed as a result of inconclusive results of in vivo studies. However, the majority of these results originate from experiments using mice, an animal species which neutrophils - the major target cells for PVL - are highly insensitive to the action of this leukocidin. In contrast, the rabbit neutrophils have been shown to be as sensitive to PVL action as human cells, making the rabbit a better experimental animal to explore the PVL role. In this study we examined whether PVL contributes to S. aureus pathogenicity by means of a rabbit skin infection model. The rabbits were injected intradermally with 108 cfu of either a PVL positive community-associated methicillin-resistant S. aureus isolate, its isogenic PVL knockout or a PVL complemented knockout strain, and the development of skin lesions was observed. While all strains induced skin infection, the wild type strain produced larger lesions and a higher degree of skin necrosis compared to the PVL knockout strain in the first week after the infection. The PVL expression in the rabbits was indirectly confirmed by a raise in the serum titer of anti-LukS-PV antibodies observed only in the rabbits infected with PVL positive strains. These results indicate that the rabbit model is more suitable for studying the role of PVL in staphylococcal diseases than other animal models. Further, they support the epidemiological link between PVL producing S. aureus strains and necrotizing skin infections

Contribution of Panton-Valentine Leukocidin in Community-Associated Methicillin-Resistant Staphylococcus aureus Pathogenesis

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) strains typically carry genes encoding Panton-Valentine leukocidin (PVL). We used wild-type parental and isogenic PVL-deletion (Δpvl) strains of USA300 (LAC and SF8300) and USA400 (MW2) to test whether PVL alters global gene regulatory networks and contributes to pathogenesis of bacteremia, a hallmark feature of invasive staphylococcal disease. Microarray and proteomic analyses revealed that PVL does not alter gene or protein expression, thereby demonstrating that any contribution of PVL to CA-MRSA pathogenesis is not mediated through interference of global gene regulatory networks. Inasmuch as a direct role for PVL in CA-MRSA pathogenesis remains to be determined, we developed a rabbit bacteremia model of CA-MRSA infection to evaluate the effects of PVL. Following experimental infection of rabbits, an animal species whose granulocytes are more sensitive to the effects of PVL compared with the mouse, we found a contribution of PVL to pathogenesis over the time course of bacteremia. At 24 and 48 hours post infection, PVL appears to play a modest, but measurable role in pathogenesis during the early stages of bacteremic seeding of the kidney, the target organ from which bacteria were not cleared. However, the early survival advantage of this USA300 strain conferred by PVL was lost by 72 hours post infection. These data are consistent with the clinical presentation of rapid-onset, fulminant infection that has been associated with PVL-positive CA-MRSA strains. Taken together, our data indicate a modest and transient positive effect of PVL in the acute phase of bacteremia, thereby providing evidence that PVL contributes to CA-MRSA pathogenesis

Genetic Interaction Between Two VNTRs in the SLC6A4 Gene Regulates Nicotine Dependence in Vietnamese Men

Nicotine dependence is an addiction to tobacco products and a global public health concern. Association between the SLC6A4 polymorphisms and nicotine dependence is controversial. Two variable number tandem repeat (VNTR) domains, termed HTTLPR and STin2, in the SLC6A4 gene are well characterized transcriptional regulatory elements. Their polymorphism in the copy number of the repeat correlates with the particular personality and psychiatric traits. We analyzed nicotine dependence in 1,804 participants from Central Vietnam. The Fagerström Test (FTND) was used to evaluate the nicotine dependence and PCR was used to determine the SLC6A4 HTTLPR and STin2 VNTRs. The HTTLPR VNTR was associated with difficulties to refrain from smoking in a prohibiting environment. The STIn2 10/10 genotype was associated with (1) years of smoking, (2) difficulties to quit the first cigarette, and (3) higher number of cigarettes smoked per day (CPD). Stratification analysis was used to find the genetic interaction between these two VNTRs in nicotine dependence as they may synergistically regulate the SLC6A4 expression. Smokers with the S/S HTTLPR genotypes showed a much stronger association between STin2 10/10 variant and CPD. This finding is consistent with the molecular evidence for the functional interaction between HTTLPR and STin2 in cell line models, where STin2 has described as a stronger expressional regulator. Similarly, we found that STin2 is a much stronger modifier of smoking with 10/10 genotype related to higher nicotine dependence. The present study supports genetic interaction between HTTLPR and STin2 VNTRs in the regulation of nicotine dependence with the dominance of the STin2 effects. This finding could be explained by their differential effect on the SLC6A4 expression

Staphylococcal Toxic Shock Syndrome 2000–2006: Epidemiology, Clinical Features, and Molecular Characteristics

Circulating strains of Staphylococcus aureus (SA) have changed in the last 30 years including the emergence of community-associated methicillin-resistant SA (MRSA). A report suggested staphylococcal toxic shock syndrome (TSS) was increasing over 2000-2003. The last population-based assessment of TSS was 1986.Population-based active surveillance for TSS meeting the CDC definition using ICD-9 codes was conducted in the Minneapolis-St. Paul area (population 2,642,056) from 2000-2006. Medical records of potential cases were reviewed for case criteria, antimicrobial susceptibility, risk factors, and outcome. Superantigen PCR testing and PFGE were performed on available isolates from probable and confirmed cases.Of 7,491 hospitalizations that received one of the ICD-9 study codes, 61 TSS cases (33 menstrual, 28 non-menstrual) were identified. The average annual incidence per 100,000 of all, menstrual, and non-menstrual TSS was 0.52 (95% CI, 0.32-0.77), 0.69 (0.39-1.16), and 0.32 (0.12-0.67), respectively. Women 13-24 years had the highest incidence at 1.41 (0.63-2.61). No increase in incidence was observed from 2000-2006. MRSA was isolated in 1 menstrual and 3 non-menstrual cases (7% of TSS cases); 1 isolate was USA400. The superantigen gene tst-1 was identified in 20 (80%) of isolates and was more common in menstrual compared to non-menstrual isolates (89% vs. 50%, p = 0.07). Superantigen genes sea, seb and sec were found more frequently among non-menstrual compared to menstrual isolates [100% vs 25% (p = 0.4), 60% vs 0% (p<0.01), and 25% vs 13% (p = 0.5), respectively].TSS incidence remained stable across our surveillance period of 2000-2006 and compared to past population-based estimates in the 1980s. MRSA accounted for a small percentage of TSS cases. tst-1 continues to be the superantigen associated with the majority of menstrual cases. The CDC case definition identifies the most severe cases and has been consistently used but likely results in a substantial underestimation of the total TSS disease burden

Global Changes in Staphylococcus aureus Gene Expression in Human Blood

Staphylococcus aureus is a leading cause of bloodstream infections worldwide. In the United States, many of these infections are caused by a strain known as USA300. Although progress has been made, our understanding of the S. aureus molecules that promote survival in human blood and ultimately facilitate metastases is incomplete. To that end, we analyzed the USA300 transcriptome during culture in human blood, human serum, and trypticase soy broth (TSB), a standard laboratory culture media. Notably, genes encoding several cytolytic toxins were up-regulated in human blood over time, and hlgA, hlgB, and hlgC (encoding gamma-hemolysin subunits HlgA, HlgB, and HlgC) were among the most highly up-regulated genes at all time points. Compared to culture supernatants from a wild-type USA300 strain (LAC), those derived from an isogenic hlgABC-deletion strain (LACΔhlgABC) had significantly reduced capacity to form pores in human neutrophils and ultimately cause neutrophil lysis. Moreover, LACΔhlgABC had modestly reduced ability to cause mortality in a mouse bacteremia model. On the other hand, wild-type and LACΔhlgABC strains caused virtually identical abscesses in a mouse skin infection model, and bacterial survival and neutrophil lysis after phagocytosis in vitro was similar between these strains. Comparison of the cytolytic capacity of culture supernatants from wild-type and isogenic deletion strains lacking hlgABC, lukS/F-PV (encoding PVL), and/or lukDE revealed functional redundancy among two-component leukotoxins in vitro. These findings, along with a requirement of specific growth conditions for leukotoxin expression, may explain the apparent limited contribution of any single two-component leukotoxin to USA300 immune evasion and virulence