Determination of minimum bactericidal concentration, in single or combination drugs, against Mycobacterium tuberculosis

Injectable isoniazid-loaded bone cement based on hydrazone bonds achieving long-term release and decent mechanical properties

A robust and easily manufactured high-strength and long-term release hydrazone-based isoniazid acrylic (HIA) bone cement is reported. The mechanical strength of HIA bone cement is similar to that of normal polymethyl methacrylate (PMMA) bone cement, far surpassing that of traditional isoniazid-containing antibiotic-loaded bone cement (INH bone cement). Isoniazid is connected to the bone cement through bioorthogonal hydrazone chemistry, and it possesses release properties superior to those of INH bone cement, allowing for the sustained release of isoniazid for up to 12 weeks. In vivo and in vitro studies also indicate that HIA cement exhibits better biocompatibility than INH bone cement. The results of this study not only signify progress in the realm of antimicrobial bone cement for addressing bone tuberculosis but also enhance our capacity to create and comprehend high-performing antimicrobial bone cement.

Silicon versus Superbug: Assessing Machine Learning's Role in the Fight against Antimicrobial Resistance

In his 1945 Nobel Prize acceptance speech, Sir Alexander Fleming warned of antimicrobial resistance (AMR) if the necessary precautions were not taken diligently. As the growing threat of AMR continues to loom over humanity, we must look forward to alternative diagnostic tools and preventive measures to thwart looming economic collapse and untold mortality worldwide. The integration of machine learning (ML) methodologies within the framework of such tools/pipelines presents a promising avenue, offering unprecedented insights into the underlying mechanisms of resistance and enabling the development of more targeted and effective treatments. This paper explores the applications of ML in predicting and understanding AMR, highlighting its potential in revolutionizing healthcare practices. From the utilization of supervised-learning approaches to analyze genetic signatures of antibiotic resistance to the development of tools and databases, such as the Comprehensive Antibiotic Resistance Database (CARD), ML is actively shaping the future of AMR research. However, the successful implementation of ML in this domain is not without challenges. The dependence on high-quality data, the risk of overfitting, model selection, and potential bias in training data are issues that must be systematically addressed. Despite these challenges, the synergy between ML and biomedical research shows great promise in combating the growing menace of antibiotic resistance.

Isoniazid-N-acylhydrazones as promising compounds for the anti-tuberculosis treatment

Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis complex, still presents significant numbers of incidence and mortality, in addition to several cases of drug resistance. Resistance, especially to isoniazid, which is one of the main drugs used in the treatment, has increased. In this context, N-acylhydrazones derived from isoniazid have shown important anti-Mycobacterium tuberculosis activity. Hence, this work aimed to determine the anti-TB potential of 11 isoniazid-N-acylhydrazones (INH-acylhydrazones). For this purpose, the determination of minimum inhibitory concentration (MIC) against M. tuberculosis H37Rv and clinical isolates was carried out. Drug combination, minimum bactericidal concentration, cytotoxicity, and in silico parameters were also performed. INH-acylhydrazones (2), (8), and (9) had MIC for M. tuberculosis H37Rv similar to or lower than isoniazid, and bactericidal activity was observed. In addition, these compounds showed low cytotoxicity, with a selectivity index greater than 3,000. Interesting results were also obtained in the drug combination assay, with synergistic combinations with isoniazid, ethambutol, and rifampicin. In the in silico study, INH-acylhydrazones behaved similarly to INH, but with improvements in some aspects. Based on these findings, it is concluded that compounds (2), (8), and (9) are considered promising scaffolds and warrant further investigation for designing future antimicrobial drugs.

Expert consensus statement on therapeutic drug monitoring and individualization of linezolid

Linezolid is an oxazolidinone antibacterial drug, and its therapeutic drug monitoring and individualized treatment have been challenged since its approval. With the in-depth clinical research of linezolid, we have changed our attitude toward its therapeutic drug monitoring and our view of individualized treatment. On the basis of summarizing the existing clinical studies, and based on the practical experience of each expert in their respective professional fields, we have formed this expert consensus. Our team of specialists is a multidisciplinary team that includes pharmacotherapists, clinical pharmacology specialists, critical care medicine specialists, respiratory specialists, infectious disease specialists, emergency medicine specialists and more. We are committed to the safe and effective use of linezolid in patients in need, and the promotion of its therapeutic drug monitoring.

In vitro Synergism of Six Antituberculosis Agents Against Drug-Resistant Mycobacterium tuberculosis Isolated from Retreatment Tuberculosis Patients

Background

Retreatment tuberculosis (TB) has become a major source of drug-resistant TB. In contrast to the combination of isoniazid (INH) and rifampicin (RIF), that of pasiniazid (Pa) and rifabutin (RFB) or rifapentine (RFP) appears to have better activity in vitro against drug-resistant Mycobacterium tuberculosis (MTB), especially when combined with moxifloxacin (MXF). However, there has been limited study of potential synergism among Pa, RFB, RFP, and MXF, or simultaneous comparison with the standard INH and RIF combination.

Methods

In vitro synergism of four two-drug combinations (INH and RIF, Pa and RFB, Pa and RFP, MXF and Pa) and two three-drug combinations (MXF and Pa combined with RFB or RFP) was evaluated against 90 drug-resistant MTB strains isolated from retreatment TB patients by the checkerboard method. The fractional inhibitory concentration index (FICI) was calculated for each combination.

Results

The synergistic activity of the combination of Pa with RFB or RFP was higher than that of INH and RIF or MXF and Pa, and the synergistic activity of Pa in combination with RFP was even higher than that of RFB, although RFP yielded an MIC₉₀ of 64 mg/liter, higher than that of RFB of 8 mg/liter against 90 drug-resistant MTB strains. Meanwhile, for three-drug combinations, the synergistic effects of MXF and Pa combined with RFB or RFP were similar. Further stratification analysis showed that, for XDR-MTB strains, the synergistic effect of the Pa and RFP combination was also better than those of other two-drug combinations.

Conclusion

The combination of Pa with RFP shows better in vitro synergism than Pa with RFB and standard INH with RIF combinations, which can provide a reference for new regimens for retreatment TB patients.