Comparative miRNA Expression Profiles in Individuals with Latent and Active Tuberculosis

The mechanism of latent tuberculosis (TB) infection remains elusive. Several host factors that are involved in this complex process were previously identified. Micro RNAs (miRNAs) are endogenous ∼22 nt RNAs that play important regulatory roles in a wide range of biological processes. Several studies demonstrated the clinical usefulness of miRNAs as diagnostic or prognostic biomarkers in various malignancies and in a few nonmalignant diseases. To study the role of miRNAs in the transition from latent to active TB and to discover candidate biomarkers of this transition, we used human miRNA microarrays to probe the transcriptome of peripheral blood mononuclear cells (PBMCs) in patients with active TB, latent TB infection (LTBI), and healthy controls. Using the software package BRB Array Tools for data analyses, 17 miRNAs were differentially expressed between the three groups (P<0.01). Hierarchical clustering of the 17 miRNAs expression profiles showed that individuals with active TB clustered independently of individuals with LTBI or from healthy controls. Using the predicted target genes and previously published genome-wide transcriptional profiles, we constructed the regulatory networks of miRNAs that were differentially expressed between active TB and LTBI. The regulatory network revealed that several miRNAs, with previously established functions in hematopoietic cell differentiation and their target genes may be involved in the transition from latent to active TB. These results increase the understanding of the molecular basis of LTBI and confirm that some miRNAs may control gene expression of pathways that are important for the pathogenesis of this infectious disease

A prospective multicenter clinical research study validating the effectiveness and safety of a chest X-ray-based pulmonary tuberculosis screening software JF CXR-1 built on a convolutional neural network algorithm

BackgroundChest radiography (chest X-ray or CXR) plays an important role in the early detection of active pulmonary tuberculosis (TB). In areas with a high TB burden that require urgent screening, there is often a shortage of radiologists available to interpret the X-ray results. Computer-aided detection (CAD) software employed with artificial intelligence (AI) systems may have the potential to solve this problem.ObjectiveWe validated the effectiveness and safety of pulmonary tuberculosis imaging screening software that is based on a convolutional neural network algorithm.MethodsWe conducted prospective multicenter clinical research to validate the performance of pulmonary tuberculosis imaging screening software (JF CXR-1). Volunteers under the age of 15 years, both with or without suspicion of pulmonary tuberculosis, were recruited for CXR photography. The software reported a probability score of TB for each participant. The results were compared with those reported by radiologists. We measured sensitivity, specificity, consistency rate, and the area under the receiver operating characteristic curves (AUC) for the diagnosis of tuberculosis. Besides, adverse events (AE) and severe adverse events (SAE) were also evaluated.ResultsThe clinical research was conducted in six general infectious disease hospitals across China. A total of 1,165 participants were enrolled, and 1,161 were enrolled in the full analysis set (FAS). Men accounted for 60.0% (697/1,161). Compared to the results from radiologists on the board, the software showed a sensitivity of 94.2% (95% CI: 92.0–95.8%) and a specificity of 91.2% (95% CI: 88.5–93.2%). The consistency rate was 92.7% (91.1–94.1%), with a Kappa value of 0.854 (P = 0.000). The AUC was 0.98. In the safety set (SS), which consisted of 1,161 participants, 0.3% (3/1,161) had AEs that were not related to the software, and no severe AEs were observed.ConclusionThe software for tuberculosis screening based on a convolutional neural network algorithm is effective and safe. It is a potential candidate for solving tuberculosis screening problems in areas lacking radiologists with a high TB burden

Pathological Brain Detection by a Novel Image Feature—Fractional Fourier Entropy

Aim: To detect pathological brain conditions early is a core procedure for patients so as to have enough time for treatment. Traditional manual detection is either cumbersome, or expensive, or time-consuming. We aim to offer a system that can automatically identify pathological brain images in this paper.Method: We propose a novel image feature, viz., Fractional Fourier Entropy (FRFE), which is based on the combination of Fractional Fourier Transform(FRFT) and Shannon entropy. Afterwards, the Welch’s t-test (WTT) and Mahalanobis distance (MD) were harnessed to select distinguishing features. Finally, we introduced an advanced classifier: twin support vector machine (TSVM). Results: A 10 x K-fold stratified cross validation test showed that this proposed “FRFE +WTT + TSVM” yielded an accuracy of 100.00%, 100.00%, and 99.57% on datasets that contained 66, 160, and 255 brain images, respectively. Conclusions: The proposed “FRFE +WTT + TSVM” method is superior to 20 state-of-the-art methods

Factors associated with loss to follow-up before and after treatment initiation among patients with tuberculosis: A 5-year observation in China

BackgroundLoss to follow-up (LTFU) is a significant barrier to the completion of anti-tuberculosis (TB) treatment and a major predictor of TB-associated deaths. Currently, research on LTFU-related factors in China is both scarce and inconsistent.MethodsWe collected information from the TB observation database of the National Clinical Research Center for Infectious Diseases. The data of all patients who were documented as LTFU were assessed retrospectively and compared with those of patients who were not LTFU. Descriptive epidemiology and multivariable logistic regression analyses were conducted to identify the factors associated with LTFU.ResultsA total of 24,265 TB patients were included in the analysis. Of them, 3,046 were categorized as LTFU, including 678 who were lost before treatment initiation and 2,368 who were lost afterwards. The previous history of TB was independently associated with LTFU before treatment initiation. Having medical insurance, chronic hepatitis or cirrhosis, and providing an alternative contact were independent predictive factors for LTFU after treatment initiation.ConclusionLoss to follow-up is frequent in the management of patients with TB and can be predicted using patients’ treatment history, clinical characteristics, and socioeconomic factors. Our research illustrates the importance of early assessment and intervention after diagnosis. Targeted measures can improve patient engagement and ultimately treatment adherence, leading to better health outcomes and disease control

Interactions between CNS and immune cells in tuberculous meningitis

The central nervous system (CNS) harbors its own special immune system composed of microglia in the parenchyma, CNS-associated macrophages (CAMs), dendritic cells, monocytes, and the barrier systems within the brain. Recently, advances in the immune cells in the CNS provided new insights to understand the development of tuberculous meningitis (TBM), which is the predominant form of Mycobacterium tuberculosis (M.tb) infection in the CNS and accompanied with high mortality and disability. The development of the CNS requires the protection of immune cells, including macrophages and microglia, during embryogenesis to ensure the accurate development of the CNS and immune response following pathogenic invasion. In this review, we summarize the current understanding on the CNS immune cells during the initiation and development of the TBM. We also explore the interactions of immune cells with the CNS in TBM. In the future, the combination of modern techniques should be applied to explore the role of immune cells of CNS in TBM

Genetic and Clinical Profiles of Disseminated Bacillus Calmette-Guérin Disease and Chronic Granulomatous Disease in China

Background: Disseminated Bacillus Calmette-Guérin disease (D-BCG) in children with chronic granulomatous disease (CGD) can be fatal, while its clinical characteristics remain unclear because both diseases are extremely rare. The patients with CGD receive BCG vaccination, because BCG vaccination is usually performed within 24 h after delivery in China.Methods: We prospectively followed-up Chinese patients with CGD who developed D-BCG to characterize their clinical and genetic characteristics. The diagnoses were based on the patients' clinical, genetic, and microbiological characteristics.Results: Between September 2009 and September 2016, we identified 23 patients with CGD who developed D-BCG. Their overall 10-year survival rate was 34%. We created a simple dissemination score to evaluate the number of infected organ systems and the survival probabilities after 8 years were 62 and 17% among patients with simple dissemination scores of ≤3 and &gt;3, respectively (p = 0.0424). Survival was not significantly associated with the CGD stimulation index or interferon-γ treatment. Eight patients underwent umbilical cord blood transplantation and 5 of them were successfully treated. The genetic analyses found mutations in CYBB (19 patients), CYBA (1 patient), NCF1 (1 patient), and NCF2 (1 patient). We identified 6 novel highly likely pathogenic mutations, including 4 mutations in CYBB and 2 mutations in NCF1.Conclusions: D-BCG is a deadly complication of CGD. The extent of BCG spreading is strongly associated with clinical outcomes, and hematopoietic stem cell transplantation may be a therapeutic option for this condition

Adult-onset Mendelian Susceptibility to Mycobacterial Diseases: A case report and systematic literature review

Objectives: To help in diagnosis and treatment of adult-onset Mendelian Susceptibility to Mycobacterial Disease (MSMD). Methods: We reported a 27-year-old man who had disease onset at 18 years. Then we reviewed previous reports of adult-onset MSMD patients, and summarized their clinical characteristics. Results: The case was diagnosed as MSMD with tyrosine kinase 2 (TYK2) mutation and had dramatic improvement after treatment. In addition to our presented case and through a review of the literature, 12 cases in total were included in our study. Average age of disease onset was 29.4 years. Medium delay of diagnosis was 2.5 years. Four were with IFN-γR1 deficiency, four with IL-12β1 deficiency, two with NEMO deficiency, one with TYK2 deficiency and one with STAT1 deficiency. Common symptoms were lymphadenopathy (6/12, 50.0 %), weight loss (6/12, 50.0 %), bone/joint pain (5/12, 41.7 %), fever (4/12, 33.3 %) and gastrointestinal symptoms (4/12, 33.3 %). Mycobacteria caused infections in lymph nodes (7/12, 58.3 %), bone/joint (5/12, 41.7 %) and skin (5/12, 41.7 %). After treatment, eight (66.7 %) got favorable prognosis, two (16.7 %) died and one (16.7 %) was unknown. Conclusions: Adult-onset MSMD have complex clinical presentations and are difficult to recognize, which results in delayed diagnosis. However, once identified, antibiotics and IFN-γ might have good efficacy. Therefore, when encountering adult patients with recurrent and refractory mycobacterial infections, especially in lymph nodes, bone/joints, and skin, MSMD should be considered