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  1. Paton NI, Gurumurthy M, Lu Q, Leek F, Kwan P, Koh HWL, et al.
    J Infect Dis, 2024 Mar 25.
    PMID: 38527849 DOI: 10.1093/infdis/jiae104
    BACKGROUND: Interleukin-4 (IL-4), increased in tuberculosis infection, may impair bacterial killing. Blocking IL-4 confers benefit in animal models. We evaluated safety and efficacy of pascolizumab (humanised anti-IL-4 monoclonal antibody) as adjunctive tuberculosis treatment.

    METHODS: Participants with rifampicin-susceptible pulmonary tuberculosis received a single intravenous infusion of pascolizumab or placebo; and standard 6-month tuberculosis treatment. Pascolizumab dose increased in successive cohorts: [1] non-randomised 0.05 mg/kg (n = 4); [2] non-randomised 0.5 mg/kg (n = 4); [3] randomised 2.5 mg/kg (n = 9) or placebo (n = 3); [4] randomised 10 mg/kg (n = 9) or placebo (n = 3). Co-primary safety outcome was study-drug-related grade 4 or serious adverse event (G4/SAE); in all cohorts (1-4). Co-primary efficacy outcome was week-8 sputum culture time-to-positivity (TTP); in randomised cohorts (3-4) combined.

    RESULTS: Pascolizumab levels exceeded IL-4 50% neutralising dose for 8 weeks in 78-100% of participants in cohorts 3-4. There were no study-drug-related G4/SAEs. Median week-8 TTP was 42 days in pascolizumab and placebo groups (p = 0.185). Rate of TTP increase was greater with pascolizumab (difference from placebo 0.011 [95% Bayesian credible interval 0.006 to 0.015] log10TTP/day.

    CONCLUSIONS: There was no evidence to suggest blocking IL-4 was unsafe. Preliminary efficacy findings are consistent with animal models. This supports further investigation of adjunctive anti-IL-4 interventions for tuberculosis in larger phase 2 trials.

  2. Trimarsanto H, Amato R, Pearson RD, Sutanto E, Noviyanti R, Trianty L, et al.
    Commun Biol, 2022 Dec 23;5(1):1411.
    PMID: 36564617 DOI: 10.1038/s42003-022-04352-2
    Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.
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