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Background: Neuropathic adverse events occur frequently in linezolid-containing regimens, some of which remain irreversible after drug discontinuation. Objective: 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. Methods: 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. Results: 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). Conclusions: 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.

Abstract Background Tuberculosis (TB) is a major cause of mortality worldwide. Children and people living with HIV (PLHIV) have an increased risk of mortality, particularly in the absence of rapid diagnosis. The main challenges of diagnosing TB in these populations are due to the unspecific and paucibacillary disease presentation and the difficulty of obtaining respiratory samples. Thus, novel diagnostic strategies, based on non-respiratory specimens could improve clinical decision making and TB outcomes in high burden TB settings. We propose a multi-country, prospective diagnostic evaluation study with a nested longitudinal cohort evaluation to assess the performance of a new stool-based qPCR, developed by researchers at Baylor College of Medicine (Houston, Texas, USA) for TB bacteriological confirmation with promising results in pilot studies. Methods The study will take place in high TB/HIV burden countries (Mozambique, Eswatini and Uganda) where we will enroll, over a period of 30 months, 650 PLHIV (> 15) and 1295 children under 8 years of age (irrespective of HIV status) presenting pressumptive TB. At baseline, all participants will provide clinical history, complete a physical assessment, and undergo thoracic chest X-ray imaging. To obtain bacteriological confirmation, participants will provide respiratory samples (1 for adults, 2 in children) and 1 stool sample for Xpert Ultra MTB/RIF (Cepheid, Sunnyvale, CA, USA). Mycobacterium tuberculosis (M.tb) liquid culture will only be performed in respiratory samples and lateral flow lipoarabinomannan (LF-LAM) in urine following WHO recommendations. Participants will complete 2 months follow-up if they are not diagnosed with TB, and 6 months if they are. For analytical purposes, the participants in the pediatric cohort will be classified into “confirmed tuberculosis”, “unconfirmed tuberculosis” and “unlikely tuberculosis”. Participants of the adult cohort will be classified as “bacteriologically confirmed TB”, “clinically diagnosed TB” or “not TB”. We will assess accuracy of the novel qPCR test compared to bacteriological confirmation and Tb diagnosis irrespective of laboratory results. Longitudinal qPCR results will be analyzed to assess its use as treatment response monitoring. Discussion The proposed stool-based qPCR is an innovation because both the strategy of using a non-sputum based sample and a technique specially designed to detect M.tb DNA in stool. Protocol registration details ClinicalTrials.gov Identifier: NCT05047315.

Abstract Dressing electronic quantum states with virtual photons creates exotic effects ranging from vacuum-field modified transport to polaritonic chemistry, and squeezing or entanglement of modes. The established paradigm of cavity quantum electrodynamics maximizes the light-matter coupling strength $${\varOmega }_{{{{{{\rm{R}}}}}}}/{\omega }_{{{{{{\rm{c}}}}}}}$$ Ω R / ω c , defined as the ratio of the vacuum Rabi frequency and the frequency of light, by resonant interactions. Yet, the finite oscillator strength of a single electronic excitation sets a natural limit to $${\varOmega }_{{{{{{\rm{R}}}}}}}/{\omega }_{{{{{{\rm{c}}}}}}}$$ Ω R / ω c . Here, we enter a regime of record-strong light-matter interaction which exploits the cooperative dipole moments of multiple, highly non-resonant magnetoplasmon modes tailored by our metasurface. This creates an ultrabroadband spectrum of 20 polaritons spanning 6 optical octaves, calculated vacuum ground state populations exceeding 1 virtual excitation quantum, and coupling strengths equivalent to $${\varOmega }_{{{{{{\rm{R}}}}}}}/{\omega }_{{{{{{\rm{c}}}}}}}=3.19$$ Ω R / ω c = 3.19 . The extreme interaction drives strongly subcycle energy exchange between multiple bosonic vacuum modes akin to high-order nonlinearities, and entangles previously orthogonal electronic excitations solely via vacuum fluctuations.

Abstract The computation of a similarity measure for genomic data is a standard tool in computational genetics. The principal components of such matrices are routinely used to correct for biases due to confounding by population stratification, for instance in linear regressions. However, the calculation of both a similarity matrix and its singular value decomposition (SVD) are computationally intensive. The contribution of this article is threefold. First, we demonstrate that the calculation of three matrices (called the covariance matrix, the weighted Jaccard matrix, and the genomic relationship matrix) can be reformulated in a unified way which allows for the application of a randomized SVD algorithm, which is faster than the traditional computation. The fast SVD algorithm we present is adapted from an existing randomized SVD algorithm and ensures that all computations are carried out in sparse matrix algebra. The algorithm only assumes that row-wise and column-wise subtraction and multiplication of a vector with a sparse matrix is available, an operation that is efficiently implemented in common sparse matrix packages. An exception is the so-called Jaccard matrix, which does not have a structure applicable for the fast SVD algorithm. Second, an approximate Jaccard matrix is introduced to which the fast SVD computation is applicable. Third, we establish guaranteed theoretical bounds on the accuracy (in $$L_2$$ L 2 norm and angle) between the principal components of the Jaccard matrix and the ones of our proposed approximation, thus putting the proposed Jaccard approximation on a solid mathematical foundation, and derive the theoretical runtime of our algorithm. We illustrate that the approximation error is low in practice and empirically verify the theoretical runtime scalings on both simulated data and data of the 1000 Genome Project.

ABSTRACT Activin A strongly influences immune responses; yet, few studies have examined its role in infectious diseases. We measured serum activin A levels in two independent tuberculosis (TB) patient cohorts and in patients with pneumonia and sarcoidosis. Serum activin A levels were increased in TB patients compared to healthy controls, including those with positive tuberculin skin tests, and paralleled severity of disease, assessed by X-ray scores. In pneumonia patients, serum activin A levels were also raised, but in sarcoidosis patients, levels were lower. To determine whether blockade of the activin A signaling axis could play a functional role in TB, we harnessed a soluble activin type IIB receptor fused to human IgG1 Fc, ActRIIB-Fc, as a ligand trap in a murine TB model. The administration of ActRIIB-Fc to Mycobacterium tuberculosis-infected mice resulted in decreased bacterial loads and increased numbers of CD4 effector T cells and tissue-resident memory T cells in the lung. Increased frequencies of tissue-resident memory T cells corresponded with downregulated T-bet expression in lung CD4 and CD8 T cells. Altogether, the results suggest a disease-exacerbating role of ActRIIB signaling pathways. Serum activin A may be useful as a biomarker for diagnostic triage of active TB or monitoring of anti-tuberculosis therapy.IMPORTANCETuberculosis remains the leading cause of death by a bacterial pathogen. The etiologic agent of tuberculosis, Mycobacterium tuberculosis, can remain dormant in the infected host for years before causing disease. Significant effort has been made to identify biomarkers that can discriminate between latently infected and actively diseased individuals. We found that serum levels of the cytokine activin A were associated with increased lung pathology and could discriminate between active tuberculosis and tuberculin skin-test-positive healthy controls. Activin A signals through the ActRIIB receptor, which can be blocked by administration of the ligand trap ActRIIB-Fc, a soluble activin type IIB receptor fused to human IgG1 Fc. In a murine model of tuberculosis, we found that ActRIIB-Fc treatment reduced mycobacterial loads. Strikingly, ActRIIB-Fc treatment significantly increased the number of tissue-resident memory T cells. These results suggest a role for ActRIIB signaling pathways in host responses to Mycobacterium tuberculosis and activin A as a biomarker of ongoing disease.

Quantum mechanical phenomena are revolutionizing classical engineering fields such as signal processing or cryptography. When randomness plays an important role, like in cryptography where random bit sequences guarantee certain levels of security, quantum mechanical phenomena allow new ways of generating random bit sequences. Such sequences have a lot of applications in the communication sector, e.g., regarding data transmission, simulation, sensors or radars, and beyond. They can be generated deterministically (e.g., by using polynomials, resulting in pseudo-random sequences) or in a non-deterministic way (e.g., by using physical noise sources like external devices or sensors, resulting in random sequences). Important characteristics of such binary sequences can be modelled by gap processes in conjunction with the probability theory. Recently, all-optical approaches have attracted a lot of research interest. In this work, an adaptation of the quantum key distribution setup is utilized for generating randomised bit sequences. The simulation results show that all-optically generated sequences very well resemble the theoretically ideal probability density characteristic. Additionally, an experimental optical setup is developed that confirms the simulation results. Furthermore, m-sequences show very promising results as well as Gold sequences. Additionally, the level of burstiness, i.e., the distribution of ones and zeros throughout the sequence, is studied for the different sequences. The results enable the finding that generator polynomials with concentrated non-zero coefficients lead to more bursty bit sequences.

Background: Coronary artery calcium (CAC) is a marker of subclinical atherosclerosis and is a complex heritable trait with both genetic and environmental risk factors, including sex and smoking. Methods: We performed genome-wide association (GWA) analyses for CAC among all participants and stratified by sex in the COPDGene study (n = 6144 participants of European ancestry and n = 2589 participants of African ancestry) with replication in the Diabetes Heart Study (DHS). We adjusted for age, sex, current smoking status, BMI, diabetes, self-reported high blood pressure, self-reported high cholesterol, and genetic ancestry (as summarized by principal components computed within each racial group). For the significant signals from the GWA analyses, we examined the single nucleotide polymorphism (SNP) by sex interactions, stratified by smoking status (current vs. former), and tested for a SNP by smoking status interaction on CAC. Results: We identified genome-wide significant associations for CAC in the chromosome 9p21 region [CDKN2B-AS1] among all COPDGene participants (p = 7.1 × 10−14) and among males (p = 1.0 × 10−9), but the signal was not genome-wide significant among females (p = 6.4 × 10−6). For the sex stratified GWA analyses among females, the chromosome 6p24 region [PHACTR1] had a genome-wide significant association (p = 4.4 × 10−8) with CAC, but this signal was not genome-wide significant among all COPDGene participants (p = 1.7 × 10−7) or males (p = 0.03). There was a significant interaction for the SNP rs9349379 in PHACTR1 with sex (p = 0.02), but the interaction was not significant for the SNP rs10757272 in CDKN2B-AS1 with sex (p = 0.21). In addition, PHACTR1 had a stronger association with CAC among current smokers (p = 6.2 × 10−7) than former smokers (p = 7.5 × 10−3) and the SNP by smoking status interaction was marginally significant (p = 0.03). CDKN2B-AS1 had a strong association with CAC among both former (p = 7.7 × 10−8) and current smokers (p = 1.7 × 10−7) and the SNP by smoking status interaction was not significant (p = 0.40). Conclusions: Among current and former smokers of European ancestry in the COPDGene study, we identified a genome-wide significant association in the chromosome 6p24 region [PHACTR1] with CAC among females, but not among males. This region had a significant SNP by sex and SNP by smoking interaction on CAC.

Tuberculosis (TB) and sarcoidosis are both granulomatous diseases. Here, we compared the immunological microenvironments of granulomas from TB and sarcoidosis patients using in situ sequencing (ISS) transcriptomic analysis and multiplexed immunolabeling of tissue sections. TB lesions consisted of large necrotic and cellular granulomas, whereas “multifocal” granulomas with macrophages or epitheloid cell core and a T-cell rim were observed in sarcoidosis samples. The necrotic core in TB lesions was surrounded by macrophages and encircled by a dense T-cell layer. Within the T-cell layer, compact B-cell aggregates were observed in most TB samples. These B-cell clusters were vascularized and could contain defined B-/T-cell and macrophage-rich areas. The ISS of 40–60 immune transcripts revealed the enriched expression of transcripts involved in homing or migration to lymph nodes, which formed networks at single-cell distances in lymphoid areas of the TB lesions. Instead, myeloid-annotated regions were enriched in CD68, CD14, ITGAM, ITGAX, and CD4 mRNA. CXCL8 and IL1B mRNA were observed in granulocytic areas in which M. tuberculosis was also detected. In line with ISS data indicating tertiary lymphoid structures, immune labeling of TB sections expressed markers of high endothelial venules, follicular dendritic cells, follicular helper T cells, and lymph-node homing receptors on T cells. Neither ISS nor immunolabeling showed evidence of tertiary lymphoid aggregates in sarcoidosis samples. Together, our finding suggests that despite their heterogeneity, the formation of tertiary immune structures is a common feature in granulomas from TB patients.

ABSTRACT We assessed the performance of a novel real-time PCR-based transrenal DNA (trDNA) assay for the specific detection of Mycobacterium tuberculosis as a candidate marker of the early anti-tuberculosis therapy response. The study was performed on 288 urine samples from 72 tuberculosis patients collected at baseline and days 3, 7, and 14 of treatment with amoxicillin-clavulanic acid alone or in combination with meropenem, ertapenem, optimized-dose rifampicin, or standard treatment control in South Africa. trDNA was detected in one-third of the samples. The highest proportion of positive PCR results (cycle threshold < 36) was observed on days 3 and 7, reflecting the point in time when maximum bacterial killing and disintegration are expected. When analyzed by study arms, the trend was observed in groups treated with active antibiotics affecting cell wall integrity (meropenem, control) but not in inactive drugs (ertapenem, amoxicillin/clavulanic acid alone) or active drugs not affecting the cell wall (rifampicin). Overall, however, the trDNA assay did not correlate well with sputum culture-based decline of viable bacteria. This is possibly due to trDNA reflecting the killing of both culturable and non-culturable bacteria and should be explored further. IMPORTANCE This study presents the results of the evaluation of a novel method for the detection of Mycobacterium tuberculosis, the causative agent of tuberculosis, in urine. Detecting parts of the mycobacteria in urine is of particular interest as it allows us to use a sample that is easy to obtain and that does not require uncomfortable procedures or safety precautions like obtaining sputum for culture, which is the most commonly used sample in the diagnosis of tuberculosis. In certain groups of individuals who cannot produce sputum, for example, children, non-sputum-based methods have particular importance. We found that the method tested was able to detect bacterial killing by active antibiotics that disrupt the cell wall and lead to fragmentation of bacteria. However, the assay can't detect inactive bacteria or bacteria that are active with an intact cell wall.

ABSTRACTBackground: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical powerResults: We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content.Conclusions: Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.

Applying whole-genome-sequencing, we aimed to detect transmission events of multidrug-resistant/rifampin-resistant strains of Mycobacterium tuberculosis complex at a tuberculosis hospital in Chisinau, Moldova. We recorded ward, room, and bed information for each patient and monitored in-hospital transfers over 1 year. Detailed molecular and patient surveillance revealed only 2 nosocomial transmission events.

In the past 2 years, remarkable advances have been made in shortening tuberculosis (TB) treatment. In particular, four clinical trials (Study 31/A5349, Nix-TB, ZeNix and TB-PRACTECAL) have provided evidence of the efficacy of regimens based on new and repurposed drugs: the 4-month regimen for drug-susceptible TB, and the 6-month bedaquiline–pretomanid–linezolid regimen with or without moxifloxacin for multidrug-resistant/rifampicin-resistant TB. Even if the evidence at the basis of these new regimens is compelling, several questions remain open, particularly concerning linezolid dose finding, the upsurging threat of bedaquiline-resistant Mycobacterium tuberculosis and the feasibility of applying these results to the paediatric population. Several ongoing trials may fill the remaining gaps and produce further reliable evidence to address the outstanding questions in TB treatment shortening.

Summary: Background: Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases. Methods: We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables. Findings: We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P

Abstract Background The association between genetic variants on the X chromosome to risk of COPD has not been fully explored. We hypothesize that the X chromosome harbors variants important in determining risk of COPD related phenotypes and may drive sex differences in COPD manifestations. Methods Using X chromosome data from three COPD-enriched cohorts of adult smokers, we performed X chromosome specific quality control, imputation, and testing for association with COPD case–control status, lung function, and quantitative emphysema. Analyses were performed among all subjects, then stratified by sex, and subsequently combined in meta-analyses. Results Among 10,193 subjects of non-Hispanic white or European ancestry, a variant near TMSB4X, rs5979771, reached genome-wide significance for association with lung function measured by FEV1/FVC ( $$\beta$$ β 0.020, SE 0.004, p 4.97 × 10–08), with suggestive evidence of association with FEV1 ( $$\beta$$ β 0.092, SE 0.018, p 3.40 × 10–07). Sex-stratified analyses revealed X chromosome variants that were differentially trending in one sex, with significantly different effect sizes or directions. Conclusions This investigation identified loci influencing lung function, COPD, and emphysema in a comprehensive genetic association meta-analysis of X chromosome genetic markers from multiple COPD-related datasets. Sex differences play an important role in the pathobiology of complex lung disease, including X chromosome variants that demonstrate differential effects by sex and variants that may be relevant through escape from X chromosome inactivation. Comprehensive interrogation of the X chromosome to better understand genetic control of COPD and lung function is important to further understanding of disease pathology. Trial registration Genetic Epidemiology of COPD Study (COPDGene) is registered at ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008). Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study (ECLIPSE), GlaxoSmithKline study code SCO104960, is registered at ClinicalTrials.gov, NCT00292552 (Active since February 16, 2006). Genetics of COPD in Norway Study (GenKOLS) holds GlaxoSmithKline study code RES11080, Genetics of Chronic Obstructive Lung Disease.

Abstract As of June 2022, the GISAID database contains more than 11 million SARS-CoV-2 genomes, including several thousand nucleotide sequences for the most common variants such as delta or omicron. These SARS-CoV-2 strains have been collected from patients around the world since the beginning of the pandemic. We start by assessing the similarity of all pairs of nucleotide sequences using the Jaccard index and principal component analysis. As shown previously in the literature, an unsupervised cluster analysis applied to the SARS-CoV-2 genomes results in clusters of sequences according to certain characteristics such as their strain or their clade. Importantly, we observe that nucleotide sequences of common variants are often outliers in clusters of sequences stemming from variants identified earlier on during the pandemic. Motivated by this finding, we are interested in applying outlier detection to nucleotide sequences. We demonstrate that nucleotide sequences of common variants (such as alpha, delta, or omicron) can be identified solely based on a statistical outlier criterion. We argue that outlier detection might be a useful surveillance tool to identify emerging variants in real time as the pandemic progresses.

BackgroundInfluenza virus is responsible for a large global burden of disease, especially in children. Multiple Organ Dysfunction Syndrome (MODS) is a life-threatening and fatal complication of severe influenza infection.MethodsWe measured RNA expression of 469 biologically plausible candidate genes in children admitted to North American pediatric intensive care units with severe influenza virus infection with and without MODS. Whole blood samples from 191 influenza-infected children (median age 6.4 years, IQR: 2.2, 11) were collected a median of 27 hours following admission; for 45 children a second blood sample was collected approximately seven days later. Extracted RNA was hybridized to NanoString mRNA probes, counts normalized, and analyzed using linear models controlling for age and bacterial co-infections (FDR q

Deaths from tuberculosis (TB) reached over 1.6 million in 2021 with 10.6 million people becoming ill. Multidrug-resistant TB, defined as the Mycobacterium tuberculosis organism having resistance to at least isoniazid and rifampicin, represented 3.9% of new TB cases and 18% of previously treated cases. While new drug regimens continue to be developed and introduced to improve treatment of drug-resistant forms of TB, diagnostic capability to identify drug resistance lags woefully behind. While significant mortality benefits exist for these newer drug regimens, implementing them without proper drug resistance diagnostic capacity could lead to development of more drug resistances and exhaust these new therapeutic tools. Moving forward, the roll-out of new TB drugs and regimens must be paired with implementation of diagnostics to ensure judicious use of resources and the best chance for improving TB worldwide.

Abstract Background Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. Methods We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. Results The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. Conclusions By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Background A substantial proportion of tuberculosis patients remain with pulmonary symptoms and reduced physical capacity despite successful treatment. We performed a systematic review to analyse the burden of post-tuberculosis lung impairment measured by lung function testing. Methods We searched the PubMed database for articles published between database inception and November 2020 and performed meta-analyses to estimate the prevalence, type and severity of lung impairment among drug-susceptible and multidrug-resistant tuberculosis survivors. Methodological quality of included studies was assessed using the Newcastle–Ottawa scale. Results 54 articles were included in this review. For subjects with former drug-susceptible tuberculosis, the combined estimated mean was 76.6% (95% CI 71.6–81.6) of predicted for forced expiratory volume in 1 s (FEV1) and 81.8% (95% CI 77.4–86.2) for forced vital capacity (FVC). In former patients with multidrug-resistant tuberculosis, it was 65.9% (95% CI 57.1–74.7) for FEV1 and 76.0% (95% CI 66.3–85.8) for FVC, respectively. The analysis of impairment types in former patients with drug-susceptible and multidrug-resistant tuberculosis showed that 22.0% versus 19.0% had obstructive, 23.0% versus 22.0% restrictive and 15.0% versus 43.0% had mixed impairment type, respectively. In the majority of studies, at least 10–15% of tuberculosis survivors had severe lung impairment. Conclusions This systematic review showed long-term abnormal spirometry results in a significant proportion of tuberculosis survivors.

Introduction: The rapid diagnosis of tuberculosis recurrence can be challenging due to persistently positive detection of Mycobacterium tuberculosis-specific DNA from sputum and bronchopulmonary samples in the absence of active disease. Methods: We compared the diagnostic accuracy of the detection of M. tuberculosis-specific DNA by either Xpert (January 2010-June 2018) or Xpert Ultra (July 2018-June 2020) and M. tuberculosis-specific ELISPOT in bronchoalveolar lavage (BAL) samples with M. tuberculosis culture results from sputum or bronchopulmonary samples in patients with suspected recurrence of pulmonary tuberculosis. Results: Among 44 individuals with previous tuberculosis and a presumptive diagnosis of recurrent pulmonary tuberculosis, 4/44 (9.1%) were diagnosed with recurrent tuberculosis by culture. DNA of M. tuberculosis was detected by Xpert in BAL fluid in 1/4 (25%) individuals with recurrent tuberculosis and in 2/40 (5%) cases with past tuberculosis without recurrence, while BAL-ELISPOT with a cut-off of >4,000 early secretory antigenic target-6-specific or culture filtrate protein-10-specific interferon-γ-producing lymphocytes per 1 million BAL-lymphocytes was positive in 4/4 (100%) individuals with recurrent tuberculosis and in 2/40 (5%) cases of past tuberculosis without recurrence. Conclusion: M. tuberculosis-specific BAL-ELISPOT is more accurate than BAL-Xpert for the diagnosis of paucibacillary tuberculosis recurrence.

Despite being a preventable and curable disease, tuberculosis (TB) is still a major global health threat and the second leading cause of death due to an infectious agent worldwide. All the efforts invested to end TB have resulted overall in rather slow decreases in TB incidence and mortality rates, which have been further negatively affected by the ongoing coronavirus disease 2019 (COVID-19) pandemic. While the majority of targets of the End TB Strategy remain off track, and we have not yet overcome the disruptions caused by the COVID-19 pandemic, recent conflicts such as the ongoing war in Ukraine are threatening the decrease of the burden of TB even further. To get back on track and get closer to ending TB, we need urgent, global, well-structured and committed multi-sectoral actions that go beyond national and global TB programmes with the support of deep investments in research and facilitation of equitable and rapid implementation of innovation worldwide.

The antibody response to the SARS-CoV-2 Omicron variant is not well studied in children. Here, the authors provide an age-stratified analysis of SARS-CoV-2 neutralizing capacity of sera from children with acute or convalescent COVID-19 as well as children with multisystem inflammatory syndrome.

Abstract Background Stool is an important diagnostic specimen for tuberculosis in populations who struggle to provide sputum, such as children or people living with HIV. However, the culture of Mycobacterium tuberculosis (M. tuberculosis) complex strains from stool perform poorly. This limits the opportunity for phenotypic drug resistance testing with this specimen. Therefore, reliable molecular methods are urgently needed for comprehensive drug resistance testing on stool specimens. Methods We evaluated the performance of targeted next-generation sequencing (tNGS, Deeplex® Myc-TB) for the detection of mutations associated with M. tuberculosis complex drug resistance on DNA isolated from stool specimens provided by participants from a prospective cohort of patients treated for tuberculosis in Eswatini (n = 66; 56 with and 10 participants without M. tuberculosis complex DNA detected in stool by real-time quantitative PCR), and an independent German validation cohort of participants with culture-confirmed tuberculosis (n = 21). Results The tNGS assay detected M. tuberculosis complex DNA in 38 of 56 (68%) samples; for 28 of 38 (74%) samples, a full M. tuberculosis complex drug resistance prediction report was obtained. There was a high degree of concordance with sputum phenotypic drug susceptibility results (κ = 0.82). The ability to predict resistance was concentration-dependent and successful in 7/10 (70%), 18/25 (72%), and 3/21 (14%) of samples with stool PCR concentration thresholds of > 100 femtogram per microliter (fg/μl), 1 to 100 fg/μl, and

The treatment of drug-resistant Mycobacterium tuberculosis relies on complex antibiotic therapy. Inadequate antibiotic exposure can lead to treatment failure, acquired drug resistance, and an increased risk of adverse events. Therapeutic drug monitoring (TDM) can be used to optimize the antibiotic exposure. Therefore, we aimed to develop a single-run multiplex assay using high-performance liquid chromatography–mass spectrometry (HPLC–MS) for TDM of patients with multidrug-resistant, pre-extensively drug-resistant and extensively drug-resistant tuberculosis. A target profile for sufficient performance, based on the intended clinical application, was established and the assay was developed accordingly. Antibiotics were analyzed on a zwitterionic hydrophilic interaction liquid chromatography column and a triple quadrupole mass spectrometer using stable isotope-labeled internal standards. The assay was sufficiently sensitive to monitor drug concentrations over five half-lives for rifampicin, rifabutin, levofloxacin, moxifloxacin, bedaquiline, linezolid, clofazimine, terizidone/cycloserine, ethambutol, delamanid, pyrazinamide, meropenem, prothionamide, and para-amino salicylic acid (PAS). Accuracy and precision were sufficient to support clinical decision making (≤±15% in clinical samples and ±20–25% in spiked samples, with 80% of future measured concentrations predicted to fall within ±40% of nominal concentrations). The method was applied in the TDM of two patients with complex drug-resistant tuberculosis. All relevant antibiotics from their regimens could be quantified and high-dose therapy was initiated, followed by microbiological conversion. In conclusion, we developed a multiplex assay that enables TDM of the relevant first- and second-line anti-tuberculosis medicines in a single run and was able to show its applicability in TDM of two drug-resistant tuberculosis patients.

Artificial intelligence (AI) systems are increasingly used in health and personalized care. However, the adoption of data-driven approaches in many clinical settings has been hampered due to their inability to perform in a reliable and safe manner to leverage accurate and trustworthy diagnoses. A critical and challenging usage scenario for AI is aiding the treatment of cancerous conditions. Providing accurate diagnosis for cancer is a challenging problem in precision oncology. Although machine learning (ML)-based approaches are very effective at cancer susceptibility prediction and subsequent treatment recommendations, ML models can be vulnerable to adversarial attacks. Since adversarially weak models can lead to wrong clinical recommendations, such vulnerabilities is critical – especially when AI-guided systems are used to aid medical doctors. Therefore, it is indispensable that healthcare professionals employ trustworthy AI tools for predicting and assessing disease risks and progression. In this paper, we propose an adversary-aware multimodal convolutional autoencoder (MCAE) model for cancer susceptibility prediction from multi-omics data consisting of copy number variations (CNVs), miRNA expression, and gene expression (GE). Based on different representational learning techniques, the MCAE model learns multimodal feature representations from multi-omics data, followed by classifying the patient cohorts into different cancer types on multimodal embedding space that exhibit similar characteristics in end-to-end setting. To make the MCAE model robust to adversaries and to provide consistent diagnosis, we formulate robustness as a property, such that predictions remain stable with regard to small variations in the input. We study different adversarial attacks scenarios and take both proactive and reactive measures (e.g., adversarial retraining and identification of adversarial inputs). Experiment results show that the MCAE model based on latent representation concatenation (LRC) exhibits high confidence at predicting cancer types, giving an average precision and Matthews correlation coefficient (MCC) scores of 0.9625 and 0.8453, respectively and shows higher robustness when compared with state-of-the-art approaches against different attack scenarios w.r.t. ERM and CLEVER scores. Overall, our study suggests that a well-fitted and adversarially robust model can provide consistent and reliable diagnosis for cancer.

ABSTRACT The WHO has endorsed the use of stool samples for diagnosis of tuberculosis (TB) in children, and targeted next-generation sequencing (tNGS) of stool has been shown to support diagnosis and provide information about drug susceptibility (DS). Optimizing extraction of DNA from stool for sequencing is critical to ensure high diagnostic sensitivity and accurate DS information. Human stool samples were spiked with various concentrations of Mycobacterium bovis bacillus Calmette-Guérin (BCG), and DNA was extracted from the samples using four different DNA extraction kits. Each sample was subjected to quantitative PCR for identifying Mycobacterium tuberculosis complex bacteria and underwent further analysis to assess the overall DNA yield, fragment length, and purity. This same process was performed with 10 pediatric participants diagnosed with pulmonary TB, and the samples underwent tNGS. The FastDNA spin kit for soil showed the best results on model samples spiked with known quantities of BCG, compared to the other extraction methods evaluated. For clinical samples, the FastDNA and PowerFecal Pro DNA (PowerFecal) kits both showed an increase in the overall DNA quantity, M. tuberculosis-specific DNA quantity, and successful targeted sequencing when testing was performed on stool samples, compared to the two other kits. Three samples extracted via PowerFecal and three samples extracted via FastDNA (from different patients) provided successful sequencing data, with an average depth of coverage of the rpoB region for FastDNA of 298 (range, 107 to 550) and for PowerFecal of 310 (range, 182 to 474), results that were comparable to one another (P = 0.946). The PowerFecal Pro and FastDNA spin kits were superior for extracting DNA from pediatric stool samples for tNGS. IMPORTANCE This is the first study to compare Mycobacterium tuberculosis DNA extraction techniques from pediatric stool samples for use with sequencing technologies. It provides an important starting point for other researchers to isolate quality DNA for this purpose to further the field and to continue to optimize protocols and approaches.

Summary: Background: Evidence on the comparative performance of purified protein derivative tuberculin skin tests (TST) and interferon-gamma release assays (IGRA) for predicting incident active tuberculosis (TB) remains conflicting. We conducted an individual participant data meta-analysis to directly compare the predictive performance for incident TB disease between TST and IGRA to inform policy. Methods: We searched Medline and Embase from 1 January 2002 to 4 September 2020, and studies that were included in previous systematic reviews. We included prospective longitudinal studies in which participants received both TST and IGRA and estimated performance as hazard ratios (HR) for the development of all diagnoses of TB in participants with dichotomised positive test results compared to negative results, using different thresholds of positivity for TST. Secondary analyses included an evaluation of the impact of background TB incidence. We also estimated the sensitivity and specificity for predicting TB. We explored heterogeneity through pre-defined sub-group analyses (e.g. country-level TB incidence). Publication bias was assessed using funnel plots and Egger's test. This review is registered with PROSPERO, CRD42020205667. Findings: We obtained data from 13 studies out of 40 that were considered eligible (N = 32,034 participants: 36% from countries with TB incidence rate ≥100 per 100,000 population). All reported data on TST and QuantiFERON Gold in-Tube (QFT-GIT). The point estimate for the TST was highest with higher cut-offs for positivity and particularly when stratified by bacillus Calmette–Guérin vaccine (BCG) status (15 mm if BCG vaccinated and 5 mm if not [TST5/15 mm]) at 2.88 (95% CI 1.69–4.90). The pooled HR for QFT-GIT was higher than for TST at 4.15 (95% CI 1.97–8.75). The difference was large in countries with TB incidence rate

Tuberculosis (TB) is one of the deadliest infectious diseases in the world with more than a million people dying of TB each year. Accurate and timely TB diagnosis has the potential to alleviate the global TB burden; therefore, one of the pillars of the End TB Strategy developed by the World Health Organization (WHO) is the early diagnosis of TB, including universal drug-susceptibility testing (DST). The WHO emphasises the importance of DST before treatment initiation, using molecular WHO-recommended rapid diagnostic tests (mWRDs). Currently available mWRDs are nucleic acid amplification tests, line probe assays, whole genome sequencing, and targeted next-generation sequencing. However, implementing the sequencing mWRDs in routine laboratories in low-income countries is constrained by the existing infrastructure, high cost, the specialised skills needed, data storage, and the current delay in results compared with other routine methods. These limitations are pronounced in resource-limited settings, which often have a high TB burden and need for innovative TB diagnostic technologies. In this article we propose several possible solutions, like adapting infrastructure capacity to needs, advocating for lowering costs, building bioinformatics and laboratory capacity, and increasing the use of open-access resources for software and publications.

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since a.) statistical power is often limited and b.) modeling of environmental effects is nontrivial and such model misspecifications can lead to false positive interaction findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy can increase the power to detect interactions, identifying contributing genes and pathways is difficult based on these relatively global results. Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate sets of genetic variants and/or multiple environmental factors. Based on the user's choice of statistical/machine learning approaches, a screening step selects and combines potential interactions into scores with improved interpretability. In the testing step, the application of robust statistics minimizes the susceptibility to main effect misspecifications. Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios, and we show how the screening strategy influences statistical power. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified highly significant interactions based on subcomponents of genetic risk scores. While the contributing single variant interaction signals are weak, our results indicate interaction patterns that result in strong aggregated effects, providing potential insights into underlying gene-environment interaction mechanisms.

During the 1930 Lübeck Mycobacterium bovis bacille Calmette–Guérin (BCG) disaster, 251 neonates received three oral BCG doses accidentally contaminated by virulent Mycobacterium tuberculosis; 67 (26.7%) infants died of tuberculosis. BCG reversion to pathogenicity did not occur. Detailed post mortem examinations clarified contested aspects of tuberculosis pathogenesis. Gastrointestinal infection was seldom “silent” and did not cause typical primary pulmonary lesions. In 15 infants, primary pulmonary foci were found but these resulted from vaccine ingestion and aspiration and were not caused by gastrointestinal infection spreading to the lungs without trace of its journey, as claimed by prominent researchers such as Calmette and von Behring. Further, among 60 infants in whom post mortem evaluation was completed, a “silent” gastrointestinal infection without an intestinal primary focus was found in only one. Lymphohaematogenous-disseminated tuberculosis caused death in 24/67 (35.8%) infants and tuberculous meningitis in a further 17/67 (25.4%). Gastrointestinal tuberculosis complications caused death in 26/67 (38.8%) infants. Half of the tuberculosis-attributed deaths had occurred by 3 months, 93% by 6 months and 100% by 12 months; remarkably no further deaths or tuberculosis recurrences occurred within 5 years post-vaccination/infection. These findings provide graphic confirmation that the early introduction of chemoprophylaxis in recently M. tuberculosis-infected young children is critical and urgent.

Persistent identification of entities plays a major role in the progress of digitization of many fields. In the scholarly publishing realm there are already persistent identifiers (PID) for papers (DOI), people (ORCID), organisation (GRID, ROR), books (ISBN) but there is no generally accepted PID system for scholarly events such as conferences or workshops yet. This article describes the relevant use cases that motivate the introduction of persistent identifiers for conferences. The use cases were mainly derived from interviews, discussions with experts and their previous work. As primary stakeholders who are involved in the typical conference event life cycle researchers, conference organizers, and data consumers were identified. The resulting list of use cases illustrates how PIDs for conference events will improve the current situation for these stakeholders and help with problems they are facing today.

Structures that can enhance the capabilities of quantum cascade lasers are highly sought after to improve their practicality for a range of applications. Here the authors demonstrate such a structure in a saturable absorber that takes advantage of intersubband polaritons in the terahertz range and study coherent nonlinear dynamics in the system.

To increase power and minimize bias in statistical analyses, quantitative outcomes are often adjusted for precision and confounding variables using standard regression approaches. The outcome is modeled as a linear function of the precision variables and confounders; however, for many complex phenotypes, the assumptions of the linear regression models are not always met. As an alternative, we used neural networks for the modeling of complex phenotypes and covariate adjustments. We compared the prediction accuracy of the neural network models to that of classical approaches based on linear regression. Using data from the UK Biobank, COPDGene study, and Childhood Asthma Management Program (CAMP), we examined the features of neural networks in this context and compared them with traditional regression approaches for prediction of three outcomes: forced expiratory volume in one second (FEV1), age at smoking cessation, and log transformation of age at smoking cessation (due to age at smoking cessation being right-skewed). We used mean squared error to compare neural network and regression models, and found the models performed similarly unless the observed distribution of the phenotype was skewed, in which case the neural network had smaller mean squared error. Our results suggest neural network models have an advantage over standard regression approaches when the phenotypic distribution is skewed. However, when the distribution is not skewed, the approaches performed similarly. Our findings are relevant to studies that analyze phenotypes that are skewed by nature or where the phenotype of interest is skewed as a result of the ascertainment condition.

BackgroundThe AID line probe assay has shown promising evaluation data on the detection of Mycobacterium tuberculosis as well as 1st- and 2nd-line drug resistance, using isolates and selected clinical samples in previous studies.MethodsThe diagnostic performance of three AID-modules (AID INH/RIF, AID FQ/EMB and AID AG) was analyzed in sputum samples from patients with presumed tuberculosis against culture methods and phenotypic drug resistance as reference standards.Results59 patients had culture-confirmed tuberculosis. All AID modules showed moderate sensitivity (46/59, 78.0%, 65.3-87.7) and very good specificity (100%, 95.5%, 93.7%). There was a high proportion of invalid tests, resulting in 32.6%, 78.3% and 19.6% of 46 AID-positive tuberculosis cases, who could not be assessed for drug resistance by the AID INH/RIF-, AID FQ/EM- and AID AG-module, respectively. A small number of patients showed drug resistance by reference standards: Three MDR-TB cases plus three, one and one patients with resistance to streptomycin, fluoroquinolones and aminoglycosides, respectively. The AID-assay detected all MDR-TB cases, two of three streptomycin-resistant TB cases, one of one of fluoroquinolone-resistant and missed one aminoglycoside-resistant TB case.DiscussionThe high proportion of invalid results precludes the use of the AID-assay from direct sputum-based tuberculosis and drug-resistance testing.

This paper presents the concept, a system-overview, and the evaluation of EnArgus, the central information system for energy research funding in Germany. Initiated by the German Federal Ministry for Economic Affairs and Energy (BMWi), EnArgus establishes a one-stop information system about all recent and ongoing energy research funding projects in Germany. Participants ranging from laypersons to experts were surveyed in three workshops to evaluate both the public and expert interfaces of the EnArgus system in comparison to peer systems. The results showed that the EnArgus system was predominantly evaluated positively by the various participants. It contributes to making the energy sector more transparent and offers clear advantages for professional use compared to similar systems. The system’s semantic processing enables more precise hits and better coverage by including semantically related terms in search results; its intelligence makes it fail-safe, rendering it suitable for areas where poor results can have dire consequences. Reporting on an actual real-world system, the paper also provides a roadmap-view of how electronic filing of administrative project data can be semantically enhanced and opened-up to provide the basis for new ways into the data that are key for future breakthrough AI interfaces.

Hemophagocytic lymphohistiocytosis (HLH) is a disorder of uncontrolled immune activation with distinct clinical features including fever, cytopenia, splenomegaly, and sepsis-like symptoms. In a young adolescent patient a novel germline GATA2 variant (NM_032638.5 (GATA2): c.177C>G, p.Tyr59Ter) was discovered and had resulted in non-tuberculous mycobacterial (NTM) infection and aggressive HLH. Strikingly, impaired degranulation of cytotoxic T-lymphocytes (CTL) and natural killer (NK)-cells was detected in CD107a-analyses. The affected patient was treated with HLA-matched unrelated alloHSCT, and subsequently all hematologic and infectious abnormalities including HLH and NTM resolved. This case supports early alloHSCT in GATA2 deficiencies as curative approach regardless of active NTM infection. Future studies on GATA2 c.177C>G, p.Tyr59*Ter might unravel its potential role in cytotoxic effector cell function and its contribution to HLH pathogenesis.

[This corrects the article DOI: 10.1371/journal.pone.0238619.].

Tuberculosis is a bacterial infectious disease that is mainly transmitted from human to human via infectious aerosols. Currently, tuberculosis is the leading cause of death by an infectious disease world-wide. In the past decade, the number of patients affected by tuberculosis has increased by ~20 percent and the emergence of drug-resistant strains of Mycobacterium tuberculosis challenges the goal of elimination of tuberculosis in the near future. For the last 50 years, management of patients with tuberculosis has followed a standardized management approach. This standardization neglects the variation in human susceptibility to infection, immune response, the pharmacokinetics of drugs, and the individual duration of treatment needed to achieve relapse-free cure. Here we propose a package of precision medicine-guided therapies that has the prospect to drive clinical management decisions, based on both host immunity and M. tuberculosis strains genetics. Recently, important scientific discoveries and technological advances have been achieved that provide a perspective for individualized rather than standardized management of patients with tuberculosis. For the individual selection of best medicines and host-directed therapies, personalized drug dosing, and treatment durations, physicians treating patients with tuberculosis will be able to rely on these advances in systems biology and to apply them at the bedside.

PurposeLong-term non-invasive ventilation (NIV) is recommended for patients with stable chronic obstructive lung disease (COPD) and chronic hypercapnia. High inspiratory pressure NIV (hiNIV) and a significant reduction of arterial pCO2 have been shown to prolong survival. Often, patients on hiNIV describe severe respiratory distress, known as "deventilation syndrome", after removal of the NIV mask in the morning. Mechanical pursed lips breathing ventilation (PLBV) is a new non-invasive ventilation mode that mimics the pressure-curve of pursed lips breathing during expiration. The clinical impact of switching patients from standard NIV to PLBV has not been studied so far.Patients and methodsIn this hypothesis generating study, we retrospectively analysed the effects of switching COPD patients (stage GOLD III-IV) from conventional NIV to PLBV. Medical records of all patients who had an established NIV and were switched to PLBV between March 2016 and October 2017 were screened. Patients were included if they complained of shortness of breath on mask removal, used their conventional NIV regularly, and had a documented complete diagnostic workup including lung function testing, blood gas analysis and 6-minute walk test (6MWT) before and after 3-7 days of PLBV.ResultsSix male and 10 female patients (median age 65.4 years; IQR 64.0-71.3) with a previous NIV treatment duration of 38 months (median; IQR 20-42) were analysed. After PLVB initiation, the median inspiratory ventilation pressure needed to maintain the capillary pre-switch pCO2 level was reduced from 19.5 mbar (IQR 16.0-26.0) to 13.8 mbar (IQR 12.5-14.9; pConclusionBased on this small retrospective analysis, we hypothesise that switching patients with COPD GOLD III-IV and chronic hypercapnia from conventional NIV to PLBV may increase exercise tolerance and FVC in the short term.

Background: Chronic pulmonary aspergillosis (CPA) is a life-threatening sequel in patients with pulmonary tuberculosis (PTB). Aspergillus-specific IgG antibody is a useful diagnostic biomarker supporting CPA diagnosis, especially in countries with limited health recourses. Methods: We conducted a prospective pilot study to assess the seroprevalence of Aspergillus-specific IgG antibodies among 61 Mozambican tuberculosis patients before, during, and after the end of TB treatment. Aspergillus-specific IgG antibody levels were measured using the ImmunoCAP®. Results: In this study, 3 out of 21 HIV-negative PTB patients had a positive Aspergillus-specific IgG antibody level before, during, and after the end of TB treatment. Antibody levels were 41.1, 45.5, and 174 mg/L at end of treatment (EOT), respectively. Additionally, two HIV-negative PTB patients with negative Aspergillus-specific IgG antibody levels at baseline became seropositive at EOT (41.9 and 158 mg/L, respectively). Interestingly, none of the HIV-positive PTB patients (40/61) had a positive Aspergillus-specific IgG antibody level at any time, neither at baseline nor at EOT. Probable CPA was diagnosed in one HIV-negative patient (5%; 1/20). Conclusion: Seroprevalence of Aspergillus-specific IgG antibody may differ between HIV-negative and HIV-positive Mozambican PTB patients. Future studies evaluating post-tuberculosis lung disease should integrate CPA as a life-threatening sequel to PTB.

Despite global efforts to control tuberculosis (TB) the estimated number of people who developed TB worldwide increased to an all-time record of more than 10 million in 2015. The goal of the World Health Organization (WHO) to reduce the global incidence of TB to less than 100 cases per million by 2035, cannot be reached unless TB prevention is markedly improved. There is a need for an improved vaccine that better protects individuals who are exposed to Mycobacterium tuberculosis from infection and active disease compared to the current M. bovis Bacille Calmette Guérin (BCG) vaccine. In the absence of such a vaccine, prevention relies on infection control measures and preventive chemotherapy for people with latent infection with M. tuberculosis (LTBI), who have the highest risk of progression to active TB. During the past decade, interferon-γ release assays (IGRAs) have increasingly replaced the tuberculin skin test as screening tools for the diagnosis of LTBI in countries with a low incidence of TB. Despite recent WHO guidelines on the management of LTBI, the definition of groups at risk for TB remains controversial, and the role of IGRAs for TB prevention in low-incidence countries remains uncertain. We reviewed the scientific literature and provide recommendations for the use of IGRAs for LTBI diagnosis in low-incidence countries. These recommendations are based on the number of patients needing treatment in order to prevent one case of TB. As the positive predictive value of IGRAs for the development of TB is sub-optimal, research must focus on the identification of alternative biomarkers that offer better predictive ability in order to substantially reduce the number needing treatment while improving the prevention of TB and improving the effectiveness of targeted preventive chemotherapy.

Family-based designs have been shown to be powerful in detecting the significant rare variants associated with human diseases. However, very few significant results have been found owing to relatively small sample sizes and the fact that statistical analyses often suffer from high false-negative error rates. These limitations can be avoided by combining results from multiple studies via meta-analysis. However, statistical methods for meta-analysis with rare variants are limited for family-based samples. In this report, we propose a tool for the meta-analysis of family-based rare variant associations, metaFARVAT. metaFARVAT is based on a quasi-likelihood score for each variant. These scores are combined to generate burden test, variable-threshold test, sequence kernel association test (SKAT), and optimal SKAT statistics. The proposed method tests homogeneous and heterogeneous effects of variants among different studies and can be applied to both quantitative and dichotomous phenotypes. Simulation results demonstrated the robustness and efficiency of the proposed method in different scenarios. By applying metaFARVAT to data from a family-based study and a case-control study, we identified a few promising candidate genes, including DLEC1, which is associated with chronic obstructive pulmonary disease.

We report a community-acquired bloodstream infection with Acinteobacter ursingii in an HIV-negative woman who injected drugs. The infection was successfully treated with meropenem. Species identification was performed by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Improved identification of Acinetobacter spp. by using this method will help identify clinical effects of this underdiagnosed pathogen.