16 research outputs found
Assessment of Seroprevalence and Associated Risk Factors for Anaplasmosis in Camelus dromedarius
(1) Background: Anaplasmosis is an infectious disease in camels caused by an obligate intracellular bacterium that is transmitted by ticks. (2) Methods: A cross-sectional study was conducted during 2020 to study the seroprevalence of Anaplasma spp. among Camelus dromedarius in three governorates in Egypt and assess the associated risk factors. Serum samples from 365 camels were examined by a competitive enzyme-linked immunosorbent assay (cELISA) test. (3) Results: Overall, the seroprevalence of anaplasmosis among camels was 18.6%. Multivariable logistic regression was performed, and it was discovered that tick infestation, application of acaricides, grooming practice and body condition were potential risk factors for Anaplasma spp. infection (odds ratio > 1) in dromedary camels. In contrast, the locality in which the camels lived and their age were not significant effects with regard to the occurrence of anaplasmosis. (4) Conclusions: The current findings suggest that improvement of protective measures to limit the effects of the identified risk factors can help to reduce the spread of anaplasmosis among camels in Egypt
Susceptibility pattern of multi-drug resistance Pseudomonas aeruginosa isolates from tertiary care hospital in Riyadh, KSA
Objectives: Pseudomonas aeruginosa is important pathogens commonly cause nosocomial infections. The occurrence of multi-resistant organisms (MROs) of Pseudomonas aeruginosa strains have been increased worldwide and limiting the therapeutic options. The MRO of Pseudomonas aeruginosa phenotype can be mediated by a variety of resistance mechanisms and highly versatile property to mutate. Therefore the our study aimed to evaluate the resistance pattern of Pseudomonas aeruginosa collected from Riyadh tertiary care hospital, Kingdom of Saudi Arabia. Methods: During the period from 2019 to 2021 clinical samples were collected from microbiology lab at King Khalid University Hospital and analysed for the antibiotic susceptibility pattern. Results: Suggested that the rates of resistance for the three years were higher for isolates collected from patients older than 50 years if its compared with the strains collected from young age. A total of 1024 Pseudomonas aeruginosa isolates were collected during the last three years, the prevalence rate were 44.6%, 32.6% and 22.7% during the period of 2019, 2020, and 2021 respectively. Meanwhile, the highest percentages of multi drug resistance Pseudomonas aeruginosa strains were recovered from body fluids; about 38 (47.5%) out of 80 Pseudomonas aeruginosa isolates were MRO Pseudomonas aeruginosa. The rate of resistances showed that Imipenem was significantly higher in resistant among the clinical isolates (77.8%), then Meropenem (61%), Aztreonam (42%) and Ceftazidime (36%) than other antibiotics. Most of isolates were sensitive to colistin except (2.7%) were resistance. Moreover, antibiotic resistant bacteria have been observed with increasing frequency over the past three years. Conclusions: The current study reports that the susceptibility among P. aeruginosa isolates have been decreased in KSA, perhaps due to the massive use of antibiotics, the lack of adherence to approved infection control practices by hospitals, or due to the changes to the public health infrastructure
Monocyte–Lymphocyte Ratio and Dysglycemia: A Retrospective, Cross-Sectional Study of the Saudi Population
Background: Abnormalities in fasting blood glucose (FBG) resulting in hypoglycemia (OG), impaired fasting glycemia (IFG), or hyperglycemia (HG) arise from disordered metabolic regulation caused in part by inflammation. To date, there is a dearth of evidence regarding the clinical utility of the monocyte–lymphocyte ratio (MLR), an emerging inflammatory index, in the management of dysglycemia. Methods: This retrospective, cross-sectional study explored MLR fluctuations as a function of glycemic control in 14,173 Saudi subjects. Data collected from 11 August 2014 to 18 July 2020 were retrieved from Al-Borg Medical Laboratories. Medians were compared by Mann–Whitney U or Kruskal–Wallis tests and the prevalence, relative risk (RR), and odds ratio (OR) were calculated. Results: MLR was significantly elevated in IFG (p < 0.0001) and HG (p < 0.05) groups compared to the normoglycemia (NG) group, and individuals with elevated MLR (>0.191) had significantly increased FBG (p < 0.001). The risk of IFG (RR = 1.12, 95% CI: 1.06–1.19, p < 0.0002) and HG (RR = 1.10, 95% CI: 1.01–1.20, p < 0.0216) was significantly increased if MLR was elevated, and individuals with elevated MLR were 1.17 times more likely to have IFG (OR = 1.17, 95% CI: 1.08–1.26, p < 0.0002) and 1.13 times more likely to have HG (OR = 1.13, 95% CI: 1.02–1.24, p < 0.0216). Conclusion: Elevated MLR is correlated with and carries a greater risk for IFG and HG. However, large prospective cohort studies are needed to establish the temporal relationship between MLR and FBG and to examine the prognostic value of this novel marker
Zoonotic risk and public health hazards of companion animals in the transmission of Helicobacter species
Objective: Helicobacteriosis is worldwide infection caused by Helicobacter species that affects both humans and animals. The current work correlated the zoonotic and public health repertoire of Helicobacter species in companion animals (dogs and cats). Methods: Samples were collected from apparently healthy dogs (70), cats (65), and 70 human patients who had been in contact with these animals in the Cairo and Giza governorates. The samples included serum, feces, and stool samples and biopsies of gastric fundus fragments (~5Â mm). All samples were examined by culture, biochemical analysis, serology, and molecular identification. Results: Helicobacter species were detected at a rate of 43.4% by PCR. H. heilmannii was more predominant, with a rate of 16%, whereas H. pylori was detected at 6%. H. pylori and H. heilmannii were isolated from both human and companion samples, whereas all samples were negative for H. felis. Conclusion: Dogs and cats were reservoirs and played a major source in human helicobacters infection
Prediction of Putative Epitope Peptides against BaeR Associated with TCS Adaptation in <i>Acinetobacter baumannii</i> Using an In Silico Approach
Background and Objectives: The BaeR protein is involved in the adaptation system of A. baumannii and is associated with virulence factors responsible for systemic infections in hospitalized patients. This study was conducted to characterize putative epitope peptides for the design of vaccines against BaeR protein, using an immune-informatic approach. Materials and Methods: FASTA sequences of BaeR from five different strains of A. baumannii were retrieved from the UNIPROT database and evaluated for their antigenicity, allergenicity and vaccine properties using BepiPred, Vaxijen, AlgPred, AntigenPro and SolPro. Their physio-chemical properties were assessed using the Expasy Protparam server. Immuno-dominant B-cell and T-cell epitope peptides were predicted using the IEDB database and MHC cluster server with a final assessment of their interactions with TLR-2. Results: A final selection of two peptide sequences (36aa and 22aa) was made from the 38 antigenic peptides. E1 was considered a soluble, non-allergenic antigen, and possessed negative GRAVY values, substantiating the hydrophilic nature of the proteins. Further analysis on the T-cell epitopes, class I immunogenicity and HLA allele frequencies yielded T-cell immuno-dominant peptides. The protein–peptide interactions of the TLR-2 receptor showed good similarity scores in terms of the high number of hydrogen bonds compared to other protein-peptide interactions. Conclusions: The two epitopes predicted from BaeR in the present investigation are promising vaccine candidates for targeting the TCS of A. baumannii in systemic and nosocomial infections. This study also demonstrates an alternative strategy to tackling and mitigating MDR strains of A. baumannii and provides a useful reference for the design and construction of novel vaccine candidates against this bacteria
Updates on Measles Incidence and Eradication: Emphasis on the Immunological Aspects of Measles Infection
Measles is an RNA virus infectious disease mainly seen in children. Despite the avail-ability of an effective vaccine against measles, it remains a health issue in children. Although it is a self-limiting disease, it becomes severe in undernourished and immune-compromised individuals. Measles infection is associated with secondary infections by opportunistic bacteria due to the immunosuppressive effects of the measles virus. Recent reports highlight that measles infection erases the already existing immune memory of various pathogens. This review covers the incidence, pathogenesis, measles variants, clinical presentations, secondary infections, elimination of measles virus on a global scale, and especially the immune responses related to measles infection
Updated Insights into the T Cell-Mediated Immune Response against SARS-CoV-2: A Step towards Efficient and Reliable Vaccines
The emergence of novel variants of SARS-CoV-2 and their abilities to evade the immune response elicited through presently available vaccination makes it essential to recognize the mechanisms through which SARS-CoV-2 interacts with the human immune response. It is essential not only to comprehend the infection mechanism of SARS-CoV-2 but also for the generation of effective and reliable vaccines against COVID-19. The effectiveness of the vaccine is supported by the adaptive immune response, which mainly consists of B and T cells, which play a critical role in deciding the prognosis of the COVID-19 disease. T cells are essential for reducing the viral load and containing the infection. A plethora of viral proteins can be recognized by T cells and provide a broad range of protection, especially amid the emergence of novel variants of SARS-CoV-2. However, the hyperactivation of the effector T cells and reduced number of lymphocytes have been found to be the key characteristics of the severe disease. Notably, excessive T cell activation may cause acute respiratory distress syndrome (ARDS) by producing unwarranted and excessive amounts of cytokines and chemokines. Nevertheless, it is still unknown how T-cell-mediated immune responses function in determining the prognosis of SARS-CoV-2 infection. Additionally, it is unknown how the functional perturbations in the T cells lead to the severe form of the disease and to reduced protection not only against SARS-CoV-2 but many other viral infections. Hence, an updated review has been developed to understand the involvement of T cells in the infection mechanism, which in turn determines the prognosis of the disease. Importantly, we have also focused on the T cells’ exhaustion under certain conditions and how these functional perturbations can be modulated for an effective immune response against SARS-CoV-2. Additionally, a range of therapeutic strategies has been discussed that can elevate the T cell-mediated immune response either directly or indirectly
Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer
As medical science and technology progress towards the era of “big data”, a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC’s diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process
Recent Trends and Developments in Multifunctional Nanoparticles for Cancer Theranostics
Conventional anticancer treatments, such as radiotherapy and chemotherapy, have significantly improved cancer therapy. Nevertheless, the existing traditional anticancer treatments have been reported to cause serious side effects and resistance to cancer and even to severely affect the quality of life of cancer survivors, which indicates the utmost urgency to develop effective and safe anticancer treatments. As the primary focus of cancer nanotheranostics, nanomaterials with unique surface chemistry and shape have been investigated for integrating cancer diagnostics with treatment techniques, including guiding a prompt diagnosis, precise imaging, treatment with an effective dose, and real-time supervision of therapeutic efficacy. Several theranostic nanosystems have been explored for cancer diagnosis and treatment in the past decade. However, metal-based nanotheranostics continue to be the most common types of nonentities. Consequently, the present review covers the physical characteristics of effective metallic, functionalized, and hybrid nanotheranostic systems. The scope of coverage also includes the clinical advantages and limitations of cancer nanotheranostics. In light of these viewpoints, future research directions exploring the robustness and clinical viability of cancer nanotheranostics through various strategies to enhance the biocompatibility of theranostic nanoparticles are summarised
Epigenetic Targets and Pathways Linked to SARS-CoV-2 Infection and Pathology
The scale at which the SARS-CoV-2/COVID-19 pandemic has spread remains enormous. Provided the genetic makeup of the virus and humans is readily available, the quest for knowing the mechanism and epidemiology continues to prevail across the entire scientific community. Several aspects, including immunology, molecular biology, and host-pathogen interaction, are continuously being dug into for preparing the human race for future pandemics. The exact reasons for vast differences in symptoms, pathophysiological implications of COVID-infections, and mortality differences remain elusive. Hence, researchers are also looking beyond traditional genomics, proteomics, and transcriptomics approach, especially entrusting the environmental regulation of the genetic landscape of COVID–human interactions. In line with these questions lies a critical process called epigenetics. The epigenetic perturbations in both host and parasites are a matter of great interest to unravel the disparities in COVID-19 mortalities and pathology. This review provides a deeper insight into current research on the epigenetic landscape of SARS-CoV-2 infection in humans and potential targets for augmenting the ongoing investigation. It also explores the potential targets, pathways, and networks associated with the epigenetic regulation of processes involved in SARS-CoV-2 pathology