Among the most prevalent and detrimental bacteria causing urinary tract infections (UTIs) is Klebsiella (K.) pneumoniae. A rapid determination of its antibiotic susceptibility can enhance patient treatment and mitigate the spread of resistant strains. In this study, we assessed the viability of using infrared spectroscopy-based machine learning as a rapid and precise approach for detecting K. pneumoniae bacteria and determining its susceptibility to various antibiotics directly from a patient\'s urine sample. In this study, 2333 bacterial samples, including 636 K. pneumoniae were investigated using infrared micro-spectroscopy. The obtained spectra (27996spectra) were analyzed with XGBoost classifier, achieving a success rate exceeding 95 % for identifying K. pneumoniae. Moreover, this method allows for the simultaneous determination of K. pneumoniae susceptibility to various antibiotics with sensitivities ranging between 74 % and 81 % within approximately 40 min after receiving the patient\'s urine sample.

Bacterial strains have developed an ability to resist antibiotics via numerous mechanisms. Recently, researchers conducted several studies to identify natural bioactive compounds, particularly secondary metabolites of medicinal plants, such as terpenoids, flavonoids, and phenolic acids, as antibacterial agents. These molecules exert several mechanisms of action at different structural, cellular, and molecular levels, which could make them candidates or lead compounds for developing natural antibiotics. Research findings revealed that these bioactive compounds can inhibit the synthesis of DNA and proteins, block oxidative respiration, increase membrane permeability, and decrease membrane integrity. Furthermore, recent investigations showed that some bacterial strains resist these different mechanisms of antibacterial agents. Researchers demonstrated that this resistance to antibiotics is linked to a microbial cell-to-cell communication system called quorum sensing (QS). Consequently, inhibition of QS or quorum quenching is a promising strategy to not only overcome the resistance problems but also to treat infections. In this respect, various bioactive molecules, including terpenoids, flavonoids, and phenolic acids, exhibit numerous anti-QS mechanisms via the inhibition of auto-inducer releases, sequestration of QS-mediated molecules, and deregulation of QS gene expression. However, clinical applications of these molecules have not been fully covered, which limits their use against infectious diseases. Accordingly, the aim of the present work was to discuss the role of the QS system in bacteria and its involvement in virulence and resistance to antibiotics. In addition, the present review summarizes the most recent and relevant literature pertaining to the anti-quorum sensing of secondary metabolites and its relationship to antibacterial activity.

The administration of alternative broad-spectrum antibiotics because of a suspected allergy to beta-lactam antibiotics (BLA) is one reason for the increase in bacterial resistance to antibiotics and results in further problems, such as reduced efficiency against the causative bacteria, longer hospital stays, higher prices, and more adverse events. Patients with documented BLA allergy experience Clostridium difficile infections and postoperative surgical-site infections more frequently than patients without this label. Yet, in cases of documented and even proven IgE-mediated allergy to a BLA, such as penicillin or cephalosporin, the careful application of a different BLA with dissimilar core and side chains is possible. Cefazolin, e.g., would often be a candidate for skin and soft-tissue infections (e.g., cellulitis) or for perioperative prophylaxis, because it does not share a common side chain with any other BLA and tackles most causative bacteria. In case of severe cellulitis, a carbapenem would be a candidate. After type IV-reactions (benign maculopapular rash), an infectiologist\'s choice would be to apply another narrow-spectrum BLA. In cases where a long-lasting therapy with penicillin is indicated (e.g., for late syphilis or prophylaxis of erysipelas) in presence of a proven IgE-mediated allergy, desensitization would be the infectiologist\'s choice.

Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of clinical isolates is often crucial for the optimal antimicrobial therapy. The conventional methods used in medical centers for susceptibility testing are time-consuming (>2 days). Two bacterial culture steps are needed, the first is used to grow the bacteria from urine on agar plates to determine the species of the bacteria (~24 hours). The second culture is used to determine the susceptibility by growing colonies from the first culture for another 24 hours. Here, the main goal is to examine the potential of infrared microscopy combined with multivariate analysis, to reduce the time it takes to identify Escherichia coli susceptibility to antibiotics and to determine the optimum choice of antibiotic to which the bacteria will respond. E coli colonies of the first culture from patients with urinary tract infections (UTI) were examined for the bacterial susceptibility using Fourier-transform infrared (FTIR). Our results show that it is possible to determine the optimum choice of antibiotic with better than 89% sensitivity, in the time span of few minutes, following the first culture.

The rise of bacterial resistance to antibiotics is a major Public Health concern. It is the result of two interacting processes: the selection of resistant bacterial strains under exposure to antibiotics and the dissemination of bacterial strains throughout the population by contact between colonized and uncolonized individuals. To investigate the resulting time evolution of bacterial resistance, Temime et al. (Emerg Infect Dis 9:411-417, 2003) developed a stochastic SIS model, which was structured by the level of resistance of bacterial strains. Here we study the asymptotic properties of this model when the population size is large. To this end, we cast the model within the framework of measure valued processes, using point measures to represent the pattern of bacterial resistance in the compartments of colonized individuals. We first show that the suitably normalized model tends in probability to the solution of a deterministic differential system. Then we prove that the process of fluctuations around this limit tends in law to a Gaussian process in a space of distributions. These results, which generalize those of Kurtz (CBMS-NSF regional conference series in applied mathematics, vol 36. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 1981, chap. 8) on SIR models, support the validity of the deterministic approximation and quantify the rate of convergence.

In this work we propose a system of non linear ordinary differential equations for the dynamics of Mycobacterium tuberculosis (Mtb) within the host, in order to study the role of macrophages, T cells and antibiotics in the control of sensitive and resistant Mtb. Conditions for the persistence of sensitive and resistant bacteria are given in terms of the secondary infections produced by bacteria and macrophages, the immune response, and the antibiotic treatment. Model analysis predicts backward bifurcations for certain values of the parameters. In this case, the dynamics is characterized by the coexistence of two infection states with low and high bacteria load, respectively.