In tuberculosis (TB), chest radiography (CXR) patterns are highly variable, mimicking pneumonia and many other diseases. This study aims to evaluate the efficacy of Google teachable machine, a deep neural network-based image classification tool, to develop algorithm for predicting TB probability of CXRs. The training dataset included 348 TB CXRs and 3806 normal CXRs for training TB detection. We also collected 1150 abnormal CXRs and 627 normal CXRs for training abnormality detection. For external validation, we collected 250 CXRs from our hospital. We also compared the accuracy of the algorithm to five pulmonologists and radiological reports. In external validation, the AI algorithm showed areas under the curve (AUC) of 0.951 and 0.975 in validation dataset 1 and 2. The accuracy of the pulmonologists on validation dataset 2 showed AUC range of 0.936-0.995. When abnormal CXRs other than TB were added, AUC decreased in both human readers (0.843-0.888) and AI algorithm (0.828). When combine human readers with AI algorithm, the AUC further increased to 0.862-0.885. The TB CXR AI algorithm developed by using Google teachable machine in this study is effective, with the accuracy close to experienced clinical physicians, and may be helpful for detecting tuberculosis by CXR.

Mycobacterium avium subspecies paratuberculosis (MAP) is the causative agent of Johne\'s Disease, a chronic granulomatous enteritis of ruminants. MAP establishes an infection in the host via the small intestine. This requires the bacterium to adhere to, and be internalised by, cells of the intestinal tract. The effector molecules expressed by MAP for this purpose remain to be fully identified and understood. Mammalian cell entry (mce) proteins have been shown to enable other Mycobacterial species to attach to and invade host epithelial cells. Here, we have expressed Mce1A, Mce1D, Mce3C and Mce4A proteins derived from MAP on the surface of a non-invasive Escherichia coli to characterise their role in the initial interaction between MAP and the host. To this end, expression of mce1A was found to significantly increase the ability of the E. coli to attach and survive intracellularly in human monocyte-like THP-1 cells, whereas expression of mce1D was found to significantly increase attachment and invasion of E. coli to bovine epithelial cell-like MDBK cells, implying cell-type specificity. Furthermore, expression of Mce1A and Mce1D on the surface of a previously non-invasive E. coli enhanced the ability of the bacterium to infect 3D bovine basal-out enteroids. Together, our data contributes to our understanding of the effector molecules utilised by MAP in the initial interaction with the host, and may provide potential targets for therapeutic intervention.

Tuberculosis remains a serious threat to human health as an infectious disease in Mexico. Data about the genotypes of circulating Mycobacterium tuberculosis isolates (MTB) in the State of Nuevo Leon, Mexico are scarce. We aimed to determine the genotypes of circulating MTB belonging to the Beijing lineage recovered from patients in the State of Nuevo Leon, Mexico. A total of 406 MTB isolates from this state were genotyped using the spoligotyping method and 18-locus MIRU-VNTR. Lineage classification and MTB transmission analysis were performed. Based on the spoligotyping analysis, we found 24 strains belonging to the Beijing genotype that were characterized phylogenetically. The MIRUs showed greater discriminatory power than the standard RFLP-IS6110 method; therefore, the greatest allelic diversity among the Beijing strains was observed with MIRU10, MIRU31, MIRU39, MRU40, and MIRU 26. MVLA analysis showed a profile variation between Beijing and non-Beijing strains. The minimum spanning tree (MST) showed that 79% (19) of the strains are related. All Beijing strains exhibited the deletion of region TbD1, which is a characteristic of modern strains. The application of spoligotyping and MIRU-VNTR-18 methods together proved to be more sensitive, discriminatory, and rapid than the standard method for the epidemiological analysis of Mycobacterium Beijing isolates. This study is one of the first to describe the genomic diversity of M. Beijing in the State of Nuevo Leon, Mexico.

Tuberculosis (TB) is an infectious disease that remains one of the major global public health concerns. Early detection of Active Pulmonary TB is therefore of utmost importance for controlling lethality and disease spreading. Currently available TB diagnostics can be broadly categorized into microscopy, culture-based, and molecular approaches, all of which come with compromised sensitivity, limited efficacy, and high expenses. Hence, rapid, sensitive, and affordable diagnostic methods for TB is the current prerequisite for disease management. This review summarizes the proteomics investigations for host-specific biomarkers from serum, sputum, saliva, and urine samples of TB patients, along with patients having comorbidity. Thorough data mining from available literature led us to conclude that the host-specific proteins involved in immunity and defense, metabolic regulation, cellular adhesion, and motility, inflammatory responses, and tissue remodelling have shown significant deregulation upon Mycobacterium tuberculosis (Mtb) infection. Notably, the immunoregulatory protein orosomucoid (ORM) was up-regulated in active TB compared to non-TB individuals, as observed in multiple studies from diverse sample types. Mannose receptor C type 2 (MRC2) was identified as an upregulated, treatment response biomarker in two independent serum proteomics investigations. Thorough mechanistic investigation on these candidate proteins would be fascinating to dig into potential drug targets and customized therapeutics for TB patients, along with their diagnostic potentials.

BACKGROUND: Isoniazid-induced pancreatitis is a potentially serious adverse drug reaction, however, the frequency of its occurrence is unknown. We conducted a systematic review to explore this adverse drug reaction comprehensively.
METHODS: We performed an advanced search in PubMed, Web of Science, Scopus, Ovid, and Embase for studies that reported isoniazid-induced pancreatitis. From the extracted data of eligible cases, we performed a descriptive analysis and a methodological risk of bias assessment using a standardized tool.
RESULTS: We included 16 case reports from eight countries comprising 16 patients in our systematic review. Most of the isoniazid-induced pancreatitis cases were extrapulmonary tuberculosis cases. We found the mean age across all case reports was 36.7 years. In all the cases, discontinuation of isoniazid resulted in the resolution of pancreatitis.
CONCLUSIONS: We found the latency period for isoniazid-induced pancreatitis to be ranged from 12 to 45 days after initiation of isoniazid therapy. A low threshold for screening of pancreatitis by measuring pancreatic enzymes in patients on isoniazid presenting with acute abdominal pain is recommended. This would facilitate an early diagnosis and discontinuation of isoniazid, thus reducing the severity of pancreatitis and preventing the complications of pancreatitis.

BACKGROUND: TBAJ-876 is a next-generation diarylquinoline. In vivo, diarylquinoline metabolites are formed with activity against Mycobacterium tuberculosis. Species-specific differences in parent drug-to-metabolite ratios might impact the translational value of animal model-based predictions. This study investigates the contribution of TBAJ-876 and its major active metabolite, TBAJ-876-M3 (M3), to the total bactericidal activity in a mouse tuberculosis model.
METHODS: In vitro activity of TBAJ-876 and M3 was investigated and compared to bedaquiline. Subsequently, a dose-response study was conducted in M. tuberculosis-infected BALB/c mice treated with TBAJ-876 (1.6/6.3/25 mg/kg) or M3 (3.1/12.5/50 mg/kg). Colony-forming units in the lungs and TBAJ-876 and M3 plasma concentrations were determined. M3\'s contribution to TBAJ-876\'s bactericidal activity was estimated based on M3-exposure following TBAJ-876 treatment and corresponding M3-activity observed in M3-treated animals.
RESULTS: TBAJ-876 and M3 demonstrated profound bactericidal activity. Lungs of mice treated for 4 weeks with 50 mg/kg M3 were culture-negative. Following TBAJ-876 treatment, M3-exposures were 2.2-3.6x higher than for TBAJ-876. TBAJ-876 activity was substantially attributable to M3, given its high exposure and potent activity.
CONCLUSIONS: These findings emphasize the need to consider metabolites and their potentially distinct exposure and activity profiles compared to parent drugs to enhance the translational value of mouse model-driven predictions.

BACKGROUND: World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome increasing trend yearly. The disease is caused by Mycobacterium tuberculosis (MTB) through airborne transmission. Treatment of TB is estimated to be 85% successful, however, this drops to 57% if MTB exhibits multiple antimicrobial resistance (AMR), for which fewer treatment options are available.
RESULTS: We develop a robust machine-learning classifier using both linear and nonlinear models (i.e. LASSO logistic regression (LR) and random forests (RF)) to predict the phenotypic resistance of Mycobacterium tuberculosis (MTB) for a broad range of antibiotic drugs. We use data from the CRyPTIC consortium to train our classifier, which consists of whole genome sequencing and antibiotic susceptibility testing (AST) phenotypic data for 13 different antibiotics. To train our model, we assemble the sequence data into genomic contigs, identify all unique 31-mers in the set of contigs, and build a feature matrix M, where M[i, j] is equal to the number of times the ith 31-mer occurs in the jth genome. Due to the size of this feature matrix (over 350 million unique 31-mers), we build and use a sparse matrix representation. Our method, which we refer to as MTB++, leverages compact data structures and iterative methods to allow for the screening of all the 31-mers in the development of both LASSO LR and RF. MTB++ is able to achieve high discrimination (F-1 >80%) for the first-line antibiotics. Moreover, MTB++ had the highest F-1 score in all but three classes and was the most comprehensive since it had an F-1 score >75% in all but four (rare) antibiotic drugs. We use our feature selection to contextualize the 31-mers that are used for the prediction of phenotypic resistance, leading to some insights about sequence similarity to genes in MEGARes. Lastly, we give an estimate of the amount of data that is needed in order to provide accurate predictions.
BACKGROUND: The models and source code are publicly available on Github at https://github.com/M-Serajian/MTB-Pipeline.

Introduction and Objective. Pets infected with zoonotic pathogens might become a source of infections for their owners, especially those who are immuno-compromised. The aim of this report is to describe a case of chronic, untreatable pneumonia in a domestic ferret. Materials and method. The subject was a 5-year-old female ferret suffering from recurrent pneumonia. Ante-mortally, swabs from the nasal cavity, alveolus and throat were collected from the animal. Post-mortally, lesioned organ fragments were collected. Standard microbiological testing was performed. Additionally, mycobacterial diagnosis including culture and molecular tests was performed. Results. The co-infection of Mycobacterium avium and Klebsiella pneumoniae was microbiologically confirmed. Conclusions. This case demonstrates the need to pay attention to the possibility of zoonotic pathogens in ferrets. Veterinarians diagnosing ferrets are potentially exposed to Mycobacteria spp. infections and other pathogens.

Hepatic tuberculosis (TB) is an uncommon extrapulmonary manifestation of tuberculosis. Hepatic TB is more common in immunocompromised patients, such as those on immunosuppressive medications or those with a human immunodeficiency virus (HIV) infection. Primary hepatic TB is rare, and liver involvement is often secondary to spreading from the lymphatics, portal vein, or hepatic artery. We report a case of hepatic TB in a patient on adalimumab for ankylosing spondylitis (AS).

UNASSIGNED: Neuropathic adverse events occur frequently in linezolid-containing regimens, some of which remain irreversible after drug discontinuation.
UNASSIGNED: We aimed to identify and validate a host RNA-based biomarker that can predict linezolid-associated neuropathy before multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR-TB) treatment initiation and to identify genes and pathways that are associated with linezolid-associated neuropathy.
UNASSIGNED: Adult patients initiating MDR/RR-TB treatment including linezolid were prospectively enrolled in 3 independent cohorts in Germany. Clinical data and whole blood RNA for transcriptomic analysis were collected. The primary outcome was linezolid-associated optic and/or peripheral neuropathy. A random forest algorithm was used for biomarker identification. The biomarker was validated in an additional fourth cohort of patients with MDR/RR-TB from Romania.
UNASSIGNED: A total of 52 patients from the 3 identification cohorts received linezolid treatment. Of those, 24 (46.2%) developed peripheral and/or optic neuropathies during linezolid treatment. The majority (59.3%) of the episodes were of moderate (grade 2) severity. In total, the expression of 1,479 genes differed significantly at baseline of treatment. Suprabasin (SBSN) was identified as a potential biomarker to predict linezolid-associated neuropathy. In the validation cohort, 10 of 42 (23.8%) patients developed grade ≥3 neuropathies. The area under the curve for the biomarker algorithm prediction of grade ≥3 neuropathies was 0.63 (poor; 95% confidence interval: 0.42 - 0.84).
UNASSIGNED: We identified and preliminarily validated a potential clinical biomarker to predict linezolid-associated neuropathies before the initiation of MDR/RR-TB therapy. Larger studies of the SBSN biomarker in more diverse populations are warranted.