Genetic diversity of macrolides resistant Staphylococcus aureus clinical isolates and the potential synergistic effect of vitamins, C and K3.

BACKGROUND: Macrolide antibiotics have been extensively used for the treatment of Staphylococcus aureus infections. However, the emergence of macrolide-resistant strains of S. aureus has become a major concern for public health. The molecular mechanisms underlying macrolide resistance in S. aureus are complex and diverse, involving both target site modification and efflux pump systems. In this study, we aim to overcome the molecular diversity of macrolide resistance mechanisms in S. aureus by identifying common molecular targets that could be exploited for the development of novel therapeutics. METHODS: About 300 Staphylococcus aureus different isolates were recovered and purified from 921 clinical specimen including urine (88), blood (156), sputum (264), nasal swabs (168), pus (181) and bone (39) collected from different departments in Tanta University Hospital. Macrolide resistant isolates were detected and tested for Multi Drug Resistant (MDR). Gel electrophoresis was performed after the D test and PCR reaction for erm(A), (B), (C), msr(A), and mph(C) genes. Finally, we tried different combinations of Erythromycin or Azithromycin antibiotics with either vitamin K3 or vitamin C. RESULTS: Macrolide resistance S. aureus isolates exhibited 7 major resistance patterns according to number of resistance markers and each pattern included sub patterns or subgroups. The PCR amplified products of different erm genes; analysis recorded different phenotypes of the Staphylococcus aureus isolates according to their different genotypes. In addition, our new tested combinations of Erythromycin and vitamin C, Erythromycin, and vitamin K3, Azithromycin and vitamin C and Azithromycin and vitamin K3 showed significant antibacterial effect when using every antibiotic alone. Our findings provide new insights into the molecular mechanisms of macrolide resistance in S. aureus and offer potential strategies for the development of novel protocols to overcome this emerging public health threat.

COVID-19 Antibody Seroconversion in Cancer Patients: Impact of Therapy Cessation-A Single-Center Study.

BACKGROUND: The effective development of COVID-19 vaccination has mitigated its harm. Using two laboratory methods, we investigated the efficacy of the BNT162b2 mRNA and BBIBP-CorV COVID-19 vaccines on seroconversion rates in cancer patients undergoing active cancer treatment. METHODS: SARS-CoV-2 vaccines were scheduled for 134 individuals. The consenting participants submitted three venous blood samples. Three samples: T0, T1, and T2. The ABBOTT-SARS-CoV-2 IgG II Quant and Elecsys® Anti-SARS-CoV-2 assays were used to evaluate the samples and convert the antibody titers to WHO (BAU)/mL units. RESULTS: Cancer patients exhibited a higher seroconversion rate at T2, regardless of vaccination type, and the mean antibody titers at T1 and T2 were higher than those at T0. BBIBP-CorV patients required a booster because BNT162b2 showed a higher seroconversion rate between T0 and T1. Statistics indicate that comparing Abbott and Roche quantitative antibody results without considering the sample collection time is inaccurate. CONCLUSIONS: COVID-19 vaccines can still induce a humoral immune response in patients undergoing cancer-targeted therapy. The strength of this study is the long-term monitoring of antibody levels after vaccination in cancer patients on active therapy using two different immunoassays. Further multicenter studies with a larger number of patients are required to validate these findings.

Association Between Serum Uric Acid Levels and Oxido-Inflammatory Biomarkers With Coronary Artery Disease in Type 2 Diabetic Patients.

BACKGROUND: Cardiovascular disease signifies a major cause of morbidity and mortality among patients with type 2 diabetes mellitus (T2DM). Serum uric acid (SUA) levels are elevated during the initial phases of impaired glucose metabolism. This work was designed to explore the association between SUA levels, serum oxido-inflammatory biomarkers, and the risk of coronary artery disease (CAD) in T2DM patients as the primary outcome. The secondary outcome was to assess the prognostic role of SUA in the prediction of the risk of CAD in T2DM patients. METHODS: In this case-control study, we enrolled 110 patients with T2DM who were further divided into patients with CAD and without CAD. In addition, 55 control participants were stringently matched to cases by age. RESULTS: Diabetic patients with CAD had significantly higher serum levels of the inflammatory biomarkers and the oxidative malondialdehyde but significantly lower levels of serum total antioxidant capacity (TAC) compared with the controls and diabetic patients without CAD. Significant positive correlations existed between SUA levels and serum levels of the inflammatory biomarkers and malondialdehyde, while a significant negative correlation existed between SUA levels and serum TAC. SUA demonstrated an accepted discrimination ability. SUA can differentiate between T2DM patients with CAD and patients without CAD, an area under the curve of 0.759. CONCLUSIONS: Elevated serum levels of SUA and oxido-inflammatory biomarkers are associated with an increased risk of CAD in T2DM. SUA levels reflect the body's inflammatory status and oxidant injury in T2DM. SUA could be utilized as a simple biomarker in the prediction of CAD risk in T2DM.

Comparative Assessment of the Kinetics of Cellular and Humoral Immune Responses to COVID-19 Vaccination in Cancer Patients.

OBJECTIVE: The kinetics of immune responses to various SARS-CoV-2 vaccines in cancer patients were investigated. METHODS: In total, 57 cancer patients who received BNT162b2-RNA or BBIBP-CorV vaccines were enrolled. Cellular and humoral immunity were assessed at three-time points, before the first vaccine dose and 14-21 days after the first and second doses. Chemiluminescent microparticle immunoassay was used to evaluate SARS-CoV-2 anti-spike IgG response, and QuantiFERON® SARS-CoV-2 kit assessed T-cell response. RESULTS: Data showed that cancer patients' CD4+ and CD8+ T cell-median IFN-γ secretion of SARS-CoV-2 antigens increased after the first and second vaccine doses (p = 0.027 and p = 0.042). BNT162b2 vaccinees had significantly higher IFN-γ levels to CD4+ and CD8+ T cell epitopes than BBIBP-CorV vaccinees (p = 0.028). There was a positive correlation between IgG antibody titer and T cell response regardless of vaccine type (p < 0.05). CONCLUSIONS: This study is one of the first to investigate cellular and humoral immune responses to SARS-CoV-2 immunization in cancer patients on active therapy after each vaccine dose. COVID-19 immunizations helped cancer patients develop an effective immune response. Understanding the cellular and humoral immune response to COVID-19 in cancer patients undergoing active treatment is necessary to improve vaccines and avoid future SARS pandemics.

Probiotic disruption of quorum sensing reduces virulence and increases cefoxitin sensitivity in methicillin-resistant Staphylococcus aureus.

Therapies which target quorum sensing (QS) systems that regulate virulence in methicillin-resistant Staphylococcus aureus (MRSA) are a promising alternative to antibiotics. QS systems play a crucial in the regulation of MRSA antibiotic resistance, exotoxin production, antioxidant protection and immune cell evasion, and are therefore attractive therapeutic targets to reduce the virulence of a pathogen. In the present work the the effects of bioactive peptides isolated from two strains of lactic acid bacteria were tested against antibiotic resistance, carotenoid production, resistance to oxidative killing and biofilm structure in two clinical MRSA isolates. The results obtained from fractional-inhibitory concentration assays with bulk and semi-purified bioactive molecules showed a significant synergistic effect increasing cefoxitin mediated killing of MRSA. This was coupled to a six-fold decrease of the major membrane pigment staphyloxanthin, and a 99% increase in susceptibility to oxidative stress mediated killing. Real-time quantitative PCR analysis of the QS-genes agrA and luxS, showed differential expression between MRSA strains, and a significant downregulation of the hemolysin gene hla. Light microscopy and scanning electron microscopy revealed alteration in biofilm formation and clustering behavior. These results demonstrate that bioactive metabolites may be effectively applied in tandem with beta-lactam antibiotics to sensitize MRSA to cefoxitin. Moreover, these results shown that several key QS-controlled virulence mechanisms are diminished by probiotic metabolites.

Microfabrication of a micron-scale microbial-domestication pod for in situ cultivation of marine bacteria.

Through the hyphenation of microfabrication, microfluidics and microbiology, we report the development of a µMicrobial-Domestication Pod (µMD Pod). This in situ cultivation device facilitates cell signaling from neighbouring species and interactions with environmental stimuli for marine bacterial growth to overcome current barriers faced by standard laboratory cultivation methods.

Data-Driven Approach toward Long-Term Equipment Condition Assessment in Sterile Drug Product Manufacturing.

A two-stage data-driven methodology for long-term equipment condition assessment in drug product manufacturing is presented with a case study for a commercially operating aseptic filling line. The methodology leverages process monitoring data. Sensor measurements are partitioned using process information and maintenance schedules that are available on different databases. Data is processed to tackle heterogeneity in sources and formats. The data is cleaned to remove the effects of short-term variabilities and to enhance underlying long-term trends. Two approaches are presented for data analysis: first, anomaly detection using independent component analysis (ICA), where clusters of outliers are identified. The frequency and timing of such outliers yield important insights regarding maintenance schedules and actions. The second approach enables condition monitoring using principal component analysis (PCA). Long-term operational baselines are identified and shifts therein are linked with different process and equipment faults. This approach highlights the impact of equipment deterioration on shifting operational data baselines and shows the potential for the combined application of ICA and PCA for equipment condition monitoring. It can be applied within predictive maintenance applications where the installation of new specialized sensors is difficult, like in the pharmaceutical industry.

Comparison of the Immunogenicity and Protective Efficacy of Various SARS-CoV-2 Vaccines among Healthcare Workers: Are Our White Coat Armies Protected?

Background: The effective immunization of healthcare workers (HCWs) plays a vital role in preventing the spread of SARS-CoV-2 infection during the coronavirus disease 2019 (COVID-19) pandemic. There is limited data on the immune response to vaccination among HCWs. We aim to determine seroprevalence rates and neutralizing IgG antibody response to various immunizations among HCWs. Methods: This study was conducted between July and September 2021, in which blood samples were obtained from HCWs and SARS-CoV-2 IgG neutralizing antibodies were measured. Data regarding vaccination status with Pfizer/BioNTech, Sinopharm, or AstraZeneca vaccines, occupation, and prior COVID-19 infection were analyzed. Results: COVID-19 infection post-vaccination was associated with higher mean antibody titers, regardless of vaccine type. Pfizer/BioNTech vaccination produced higher mean antibody titers for HCWs with prior COVID-19 infection (p < 0.00001) than other types of vaccines. Although 96% of HCWs were vaccinated, 3% were seronegative. For HCWs who were seropositive, there were no significant differences between the mean antibody titers when comparing occupations and blood indices. Conclusion: Awareness of the immunity status of HCWs is key to protecting this important group against SARS-CoV-2, especially those without prior COVID-19 infection. Further public health efforts regarding booster vaccination for HCWs are crucial to provide necessary antibody protection.

A systematic techno-economic approach to decide between continuous and batch operation modes for injectable manufacturing.

A comprehensive approach is proposed to systematically determine the optimal mode of operation between continuous and batch injectable manufacturing considering product and market conditions. At the core of this approach are two integrated complete mathematical modules for discrete and continuous injectable manufacturing, which are supplemented with an economic evaluation module that can then be used to explore the impact of all relevant process parameters (e.g., lot-size, number of operators, solubility, product demand, raw material costs). When the developed approach was applied to two case studies, it was found that batch production was preferred at low to moderate solution (raw material) costs. In contrast, at higher solution costs, the preference for batch and continuous production processes changed back and forth as the annual product demand changed. The study also found that continuous production processes became increasingly preferred at medium to large final dosage volumes and a competitive alternative even at moderate solution costs. From a decision-making point of view, batch injectable manufacturing will be preferred over the novel continuous manufacturing technology unless there is a significant economic incentive to overcome the perceived technology risk. The proposed approach is intended as a decision-support tool for pharmaceutical process engineers.

Determination of critical decision points for COVID-19 measures in Japan.

Coronavirus disease 2019 (COVID-19) has spread throughout the world. The prediction of the number of cases has become essential to governments' ability to define policies and take countermeasures in advance. The numbers of cases have been estimated using compartment models of infectious diseases such as the susceptible-infected-removed (SIR) model and its derived models. However, the required use of hypothetical future values for parameters, such as the effective reproduction number or infection rate, increases the uncertainty of the prediction results. Here, we describe our model for forecasting future COVID-19 cases based on observed data by considering the time delay (tdelay). We used machine learning to estimate the future infection rate based on real-time mobility, temperature, and relative humidity. We then used this calculation with the susceptible-exposed-infectious-removed (SEIR) model to forecast future cases with less uncertainty. The results suggest that changes in mobility affect observed infection rates with 5-10 days of time delay. This window should be accounted for in the decision-making phase especially during periods with predicted infection surges. Our prediction model helps governments and medical institutions to take targeted early countermeasures at critical decision points regarding mobility to avoid significant levels of infection rise.

Polymorphisms of interleukin 4 and interleukin 4 receptor genes and bronchial asthma risk among Egyptian children.

BACKGROUND: Interleukin 4 (IL4) is a key cytokine that regulates the inflammatory cascade in bronchial asthma. We investigated the association between the IL4 and IL4R polymorphisms and the susceptibility for bronchial asthma among Egyptian children. METHODS: IL4 VNTR and IL4R c.1902 A>G p.(Q576R) polymorphisms were investigated among 100 children with bronchial asthma and 100 healthy controls using PCR method. Serum levels of IL4 and immunoglobulin E (IgE) were assessed by ELISA. RESULTS: The frequencies of (A1A2 + A2A2) genotypes and A2-allele of the IL4 VNTR variant were significantly higher among asthmatic patients than controls (p = 0.01, OR = 2.34, 95% CI = 1.24-4.44; p = 0.01, OR = 2.27, 95% CI = 1.29-3.99, respectively). The frequencies of (AG + GG) genotypes and G-allele of the IL4R (A1902G) variant were significantly higher among asthmatic patients than controls (p = 0.003, OR = 2.52, 95% CI = 1.39-4.58; p = 0.002, OR = 2.25, 95% CI = 1.35-3.76, respectively). There was a significant association between (A1A2 + A2A2) genotypes of the IL4 VNTR variant and high serum IL4 level among asthmatic patients (p < 0.001). The (AG + GG) genotypes of the IL4R (A1902G) variant were significantly associated with exposure to triggers, atopic dermatitis and higher serum IgE level in asthmatic patients (p = 0.02, 0.04 and 0.01, respectively). CONCLUSION: IL4 VNTR and IL4R (A1902G) polymorphisms could be associated with higher risks of bronchial asthma among Egyptian children.

Cystic fibrosis lung environment and Pseudomonas aeruginosa infection.

BACKGROUND: The airways of patients with cystic fibrosis (CF) are highly complex, subject to various environmental conditions as well as a distinct microbiota. Pseudomonas aeruginosa is recognized as one of the most important pulmonary pathogens and the predominant cause of morbidity and mortality in CF. A multifarious interplay between the host, pathogens, microbiota, and the environment shapes the course of the disease. There have been several excellent reviews detailing CF pathology, Pseudomonas and the role of environment in CF but only a few reviews connect these entities with regards to influence on the overall course of the disease. A holistic understanding of contributing factors is pertinent to inform new research and therapeutics. DISCUSSION: In this article, we discuss the deterministic alterations in lung physiology as a result of CF. We also revisit the impact of those changes on the microbiota, with special emphasis on P. aeruginosa and the influence of other non-genetic factors on CF. Substantial past and current research on various genetic and non-genetic aspects of cystic fibrosis has been reviewed to assess the effect of different factors on CF pulmonary infection. A thorough review of contributing factors in CF and the alterations in lung physiology indicate that CF lung infection is multi-factorial with no isolated cause that should be solely targeted to control disease progression. A combinatorial approach may be required to ensure better disease outcomes. CONCLUSION: CF lung infection is a complex disease and requires a broad multidisciplinary approach to improve CF disease outcomes. A holistic understanding of the underlying mechanisms and non-genetic contributing factors in CF is central to development of new and targeted therapeutic strategies.