A Review of the Resistance Mechanisms for ß-Lactams, Macrolides and Fluoroquinolones among Streptococcus pneumoniae.

Streptococcus pneumoniae (S. pneumoniae) is a bacterial species often associated with the occurrence of community-acquired pneumonia (CAP). CAP refers to a specific kind of pneumonia that occurs in individuals who acquire the infection outside of a healthcare setting. It represents the leading cause of both death and morbidity on a global scale. Moreover, the declaration of S. pneumoniae as one of the 12 leading pathogens was made by the World Health Organization (WHO) in 2017. Antibiotics like ß-lactams, macrolides, and fluoroquinolones are the primary classes of antimicrobial medicines used for the treatment of S. pneumoniae infections. Nevertheless, the efficacy of these antibiotics is diminishing as a result of the establishment of resistance in S. pneumoniae against these antimicrobial agents. In 2019, the WHO declared that antibiotic resistance was among the top 10 hazards to worldwide health. It is believed that penicillin-binding protein genetic alteration causes ß-lactam antibiotic resistance. Ribosomal target site alterations and active efflux pumps cause macrolide resistance. Numerous factors, including the accumulation of mutations, enhanced efflux mechanisms, and plasmid gene acquisition, cause fluoroquinolone resistance. Furthermore, despite the advancements in pneumococcal vaccinations and artificial intelligence (AI), it is not feasible for individuals to rely on them indefinitely. The ongoing development of AI for combating antimicrobial resistance necessitates more research and development efforts. A few strategies can be performed to curb this resistance issue, including providing educational initiatives and guidelines, conducting surveillance, and establishing new antibiotics targeting another part of the bacteria. Hence, understanding the resistance mechanism of S. pneumoniae may aid researchers in developing a more efficacious antibiotic in future endeavors.

Tools to Alleviate the Drug Resistance in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb), an acid-fast bacillus that causes Tuberculosis (TB), is a pathogen that caused 1.5 million deaths in 2020. As per WHO estimates, another 4.1 million people are suffering from latent TB, either asymptomatic or not diagnosed, and the frequency of drug resistance is increasing due to intrinsically linked factors from both host and bacterium. For instance, poor access to TB diagnosis and reduced treatment in the era of the COVID-19 pandemic has resulted in more TB deaths and an 18% reduction in newly diagnosed cases of TB. Additionally, the detection of Mtb isolates exhibiting resistance to multiple drugs (MDR, XDR, and TDR) has complicated the scenario in the pathogen's favour. Moreover, the conventional methods to detect drug resistance may miss mutations, making it challenging to decide on the treatment regimen. However, owing to collaborative initiatives, the last two decades have witnessed several advancements in both the detection methods and drug discovery against drug-resistant isolates. The majority of them belong to nucleic acid detection techniques. In this review, we highlight and summarize the molecular mechanism underlying drug resistance in Mtb, the recent advancements in resistance detection methods, and the newer drugs used against drug-resistant TB.

Unleashing the power of artificial intelligence for diagnosing and treating infectious diseases: A comprehensive review.

Infectious diseases present a global challenge, requiring accurate diagnosis, effective treatments, and preventive measures. Artificial intelligence (AI) has emerged as a promising tool for analysing complex molecular data and improving the diagnosis, treatment, and prevention of infectious diseases. Computer-aided detection (CAD) using convolutional neural networks (CNN) has gained prominence for diagnosing tuberculosis (TB) and other infectious diseases such as COVID-19, HIV, and viral pneumonia. The review discusses the challenges and limitations associated with AI in this field and explores various machine-learning models and AI-based approaches. Artificial neural networks (ANN), recurrent neural networks (RNN), support vector machines (SVM), multilayer neural networks (MLNN), CNN, long short-term memory (LSTM), and random forests (RF) are among the models discussed. The review emphasizes the potential of AI to enhance the accuracy and efficiency of diagnosis, treatment, and prevention of infectious diseases, highlighting the need for further research and development in this area.

Regulation of Host Immune Response against Enterobacter cloacae Proteins via Computational mRNA Vaccine Design through Transcriptional Modification.

Enterobacter cloacae is mainly responsible for sepsis, urethritis, and respiratory tract infections. These bacteria may affect the transcription of the host and particularly their immune system by producing changes in their epigenetics. In the present study, four proteins of Enterobacter cloacae were used to predict the epitopes for the construction of an mRNA vaccine against Enterobacter cloacae infections. In order to generate cellular and humoral responses, various immunoinformatic-based approaches were used for developing the vaccine. The molecular docking analysis was performed for predicting the interaction among the chosen epitopes and corresponding MHC alleles. The vaccine was developed by combining epitopes (thirty-three total), which include the adjuvant Toll-like receptor-4 (TLR4). The constructed vaccine was analyzed and predicted to cover 99.2% of the global population. Additionally, in silico immunological modeling of the vaccination was also carried out. When it enters the cytoplasm of the human (host), the codon is optimized to generate the translated mRNA efficiently. Moreover, the peptide structures were analyzed and docked with TLR-3 and TLR-4. A dynamic simulation predicted the stability of the binding complex. The assumed construct was considered to be a potential candidate for a vaccine against Enterobacter cloacae infections. Hence, the proposed construct is suitable for in vitro analyses to validate its effectiveness.

Immune and Oxidative Response against Sonicated Antigen of Mycoplasma capricolum subspecies capripneumonia-A Causative Agent of Contagious Caprine Pleuropneumonia.

Vaccines are vital for prevention and control of mycoplasma diseases. The exploration of a vaccine candidate for the development of a vaccine is imperative. The present study envisages the evaluation of immune and oxidative response against an adjuvanted, sonicated antigen of Mycoplasma capricolum subsp. capripneumonia in male Angora rabbits (1 year old, 2 kg) divided in four groups, each having six animals. Group 1 was the healthy control and received 1 mL PBS via subcutaneous route. Group 2 was administered 1 mL of saponin-adjuvanted and -sonicated antigen, Group 3 was given 1 mL of montanide ISA 50-adjuvanted and-sonicated antigen, and Group 4 was given 1 mL of standard vaccine via subcutaneous route. Animals were evaluated for cellular and humoral immune response and oxidative parameters at 0, 7, 14, 21, and 28 days of the study. Total leukocytic, neutrophilic, and basophilic counts showed a significant (p < 0.05) increase in vaccinated groups compared to the healthy group on most of the intervals. TNF-α levels were significantly (p < 0.05) higher in the Group 2 than the Group 1 at all the time intervals and more comparable to Group 4 than Group 3. IL-10 levels were significantly (p < 0.05) higher in vaccinated groups compared to the healthy group on days 14, 21, and 28, but were lower in Group 3 than in Group 2 and Group 4. More hypersensitivity as inflammation and histopathological cellular infiltration in the ear was produced in Group 2 and Group 4 than in Group 3. IgG levels were significantly (p < 0.05) higher in Group 2 and Group 4 than in Group 3 on days 14 and 21. Antibody titers were comparatively higher in Group 4, followed by Group 2 and 3, than Group 1. Significantly (p < 0.05) higher oxidant and lower antioxidant values were noted in Group 2 and 4 compared to Group 3 and Group 1 on most of the intervals. The TLC and antibody titer showed increasing trend throughout the trial, whereas TNF-α, IgG, L, M and E started decreasing from day 14, and IL-10, N and B started decreasing from day 21. This study concludes that the saponin-adjuvanted and-sonicated antigen induces comparatively higher immune response than montanide but is associated with oxidative and inflammatory reactions.

Monkeypox and Its Possible Sexual Transmission: Where Are We Now with Its Evidence?

Monkeypox is a rare disease but is increasing in incidence in different countries since the first case was diagnosed in the UK by the United Kingdom (UK) Health Security Agency on 6 May 2022. As of 9 August, almost 32,000 cases have been identified in 89 countries. In endemic areas, the monkeypox virus (MPXV) is commonly transmitted through zoonosis, while in non-endemic regions, it is spread through human-to-human transmission. Symptoms can include flu-like symptoms, rash, or sores on the hands, feet, genitalia, or anus. In addition, people who did not take the smallpox vaccine were more likely to be infected than others. The exact pathogenesis and mechanisms are still unclear; however, most identified cases are reported in men who have sex with other men (MSM). According to the CDC, transmission can happen with any sexual or non-sexual contact with the infected person. However, a recent pooled meta-analysis reported that sexual contact is involved in more than 91% of cases. Moreover, it is the first time that semen analysis for many patients has shown positive monkeypox virus DNA. Therefore, in this review, we will describe transmission methods for MPXV while focusing mainly on potential sexual transmission and associated sexually transmitted infections. We will also highlight the preventive measures that can limit the spread of the diseases in this regard.