Half a Century in Hiding: A Unique Case of Tuberculoid Leprosy with an Unprecedented Incubation Period.

BACKGROUND Leprosy, also known as Hansen's disease, is a neglected tropical disease with low prevalence in the United States. The disease's long incubation period can cause delayed presentation, and most affected individuals have a history of travel or work in leprosy-endemic regions. The immune response to Mycobacterium leprae determines the clinical characteristics of leprosy, with tuberculoid leprosy being characterized by well-defined granulomas and involvement of peripheral nerves. The recommended treatment is a combination of dapsone and rifampin for 12 months. CASE REPORT A 78-year-old man with a history of extensive travel to Africa and Asia 50 years ago, presented with a non-tender, non-pruritic, and hypopigmented skin lesion on his left knee. Biopsy results confirmed granulomatous inflammation and the presence of Mycobacterium leprae, leading to a diagnosis of tuberculoid/paucibacillary leprosy. The patient received dapsone and rifampin treatment, which resulted in symptom improvement. CONCLUSIONS The patient's long incubation period of 50 years between exposure and symptom onset is remarkable and possibly one of the longest reported for tuberculoid leprosy. It emphasizes the importance of considering leprosy in cases with an extensive travel history and long incubation periods. Our patient's case presented contradictory staining results, suggesting potential sampling variation or a rare mixed leprosy form. Based on his clinical findings, he was diagnosed with tuberculoid leprosy. Early diagnosis and treatment are crucial to prevent irreversible nerve damage and improve patient outcomes. Healthcare providers should be vigilant in acquiring a detailed travel history to facilitate early diagnosis and appropriate management of leprosy cases.

Clinical and genetic predictors of cardiac dysfunction assessed by echocardiography in patients with hereditary hemochromatosis.

PURPOSE: Hereditary hemochromatosis (HH) may cause iron deposition in cardiac tissue. We aimed to describe the echocardiographic findings in patients with HH and identify risk factors for cardiac dysfunction. METHODS: In this retrospective study, we included patients with HH who underwent transthoracic echocardiography at our tertiary care center between August 2000 and July 2022. We defined three primary outcomes for cardiac dysfunction: 1) left ventricular ejection fraction (LVEF) < 55%, 2) ratio between early mitral inflow velocity and mitral annular early diastolic velocity (E/e') > 15, and 3) global longitudinal strain (GLS) < 18. Multivariable logistic regression was utilized to identify predictors of cardiac dysfunction. RESULTS: 582 patients (median age 57 years, 61.2% male) were included. The frequency of LVEF < 55%, E/e' > 15 and GLS < 18 was 9.0% (52/580), 9.6% (51/534) and 20.2% (25/124), respectively. In multivariable analysis, non-White race, age, and hypertension were associated with E/e' > 15. No specific HFE genetic mutation was associated with LVEF < 55%. A history of myocardial infarction was strongly associated with both LVEF < 55% and E/e' > 15. In patients with LVEF ≥ 55%, the C282Y/H63D genetic mutation was associated with reduced likelihood of E/e' > 15, p = 0.024. Patients with C282Y/H63D had a higher frequency of myocardial infarction. Smoking and alcohol use were significantly associated with GLS < 18 in unadjusted analysis. CONCLUSION: We found the traditional risk factors of male sex, and history of myocardial infarction or heart failure, were associated with a reduced LVEF, irrespective of the underlying HFE genetic mutation. Patients with a C282Y/H63D genetic mutation had a higher frequency of myocardial infarction, yet this mutation was associated with reduced odds of diastolic dysfunction compared to other genetic mutations in patients with a normal LVEF.

A systemic review of Mycobacterium nebraskense case reports up to october 2023, featuring our unique case study.

Background: Mycobacterium nebraskense is a rare, slow growing nontuberculous mycobacterium species with limited documented cases. This systematic review aims to comprehensively analyze the clinical characteristics, presentation, and management of M. nebraskense infections by analyzing the available literature, including a newly reported case that we present in this article. Methods: A comprehensive search was conducted using PubMed and Google Scholar to identify relevant cases up to October 2023. Only seven reported cases were found, highlighting the scarcity of information on this pathogen. Results: Our analysis revealed several key findings. First, gender disparities were observed, with females being more susceptible to M. nebraskense infections. Additionally, a significant portion of patients presented with asymptomatic infections. Most affected individuals were over the age of 60, emphasizing potential age-related susceptibility. Comorbidity profiles varied widely among cases, and patients with preexisting lung comorbidities were at an increased risk of infection. The decision to treat or observe depended on clinical presentation, with even immunosuppressed individuals not always requiring treatment. Regarding treatment, we proposed an empirical approach with amikacin, clarithromycin, or rifabutin, considering the reported resistance to doxycycline and minocycline. Combination therapy was commonly employed to minimize resistance development, consistent with mycobacterial infection management. Conclusion: This study underscores the need for further research to validate these findings and enhance our understanding of M. nebraskense infections. As limited data are available, this review aims to provide valuable insights into a rare and emerging pathogen to guide clinical practice and future research endeavors.

Feedback-based, system-level properties of vertebrate-microbial interactions.

BACKGROUND: Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. METHODS: To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. RESULTS: In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D-, or microbial-negative) groups: D+ and D- data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D- data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. CONCLUSIONS: More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.