Nephroprotective potential of Polyalthia longifolia roots against vancomycin-induced renal toxicity in experimental animals

This study was done to investigate the possible nephroprotective effect of an ethanolic root extract of Polyalthia Longifolia (PL) on vancomycin-induced nephrotoxicity using curative and protective models. Vancomycin (150 mg/kg, intravenous) was given to healthy Wistar albino rats in the curative model before the start of treatment, whereas the protective group received vancomycin at the conclusion of the 10-day treatment procedure. Animals were divided into six groups for both models; group I served as the normal control, while groups II, III, IV, V, and VI were kept as toxic control, standard (selenium, 6 mg/kg), LDPL (low dose of PL 200 mg/kg), HDPL (high dose of PL 400 mg/kg), and HDPL + selenium (interactive) groups, respectively. Renal biomarkers [(uric acid, creatinine, blood urea nitrogen (BUN), serum proteins], and blood electrolyte levels were measured for all tested groups. When compared to the vancomycin group, the HDPL significantly (p < 0.01) showed greater effectiveness in lowering the BUN, potassium, and calcium levels. Additionally, in the curative model, there was a significant (p < 0.05) decrease in the blood levels of uric acid, creatinine, BUN, potassium, and calcium in the animals who received the combination of selenium and HDPL. Both LDPL and HDPL did not provide any distinguishable effect in the protective model, but groups that received HDPL with selenium did provide detectable protection by significantly lowering their levels of uric acid, BUN, serum potassium, and total serum protein in comparison to the vancomycin control group. These findings indicate that, whether administered before or after renal damage is induced, the Polyalthia longifolia root extract provided only modest protection to nephrons, which require selenium support to prevent vancomycin-induced kidney damage

A descriptive study of colorectal surgery in England using routine administrative data and a clinical database

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The Molecular Characterization of Virulence Determinants and Antibiotic Resistance Patterns in Human Bacterial Uropathogens

The high rates of bacterial infections affect the economy worldwide by contributing to the increase in morbidity and treatment costs. The present cross-sectional study was carried out to evaluate the prevalence of bacterial infection in urinary tract infection (UTI) patients and to evaluate the antimicrobial resistance rate (AMR) in a Tertiary Care Hospital in Lahore, Pakistan. The study was conducted for the period of one year from January 2020 to December 2020. A total of 1899 different clinical samples were collected and examined for bacterial cultures using standard procedures. Samples were inoculated on different culture media to isolate bacterial isolates and for identification and susceptibility testing. A total of 1107/1899 clinical samples were positive for Staphylococcus aureus (S. aureus), Pseudomonas aeruginosa (P. aeruginosa), Escherichia coli (E. coli) and other bacterial isolates. Methicillin-resistant S. aureus (MRSA) prevalence was 16.93% from these positive cases. MRSA strains were found to be highly resistant to amikacin, clindamycin, fusidic acid, gentamicin and tobramycin, while highest sensitivity was noted against vancomycin (100%) and linezolid (100%). MRSA and high rates of multidrug resistance (MDR) pose a serious therapeutic burden to critically ill patients. A systematic and concerted effort is essential to rapidly identify high-risk patients and to reduce the burden of AMR

Genotypic and Phenotypic Characterization of Erythromycin-Resistant <i>Staphylococcus aureus</i> Isolated from Bovine Mastitis and Humans in Close Contact

Staphylococcus aureus (S. aureus) is a major causative agent of mastitis and is resistant to many antibiotics. Thus, there is a need to characterize the genetic determinants of S. aureus erythromycin resistance, such as ermA, ermB and ermC. The current study aimed to determine the phenotypic and genotypic erythromycin resistance profile and relatedness of S. aureus recovered from bovine mastitis and humans in close contact. A total of 14 mastitis-infected buffalo milk samples and 16 samples from their respective milkers were collected from different farms of Lahore, Pakistan. The antibiotic resistance profile was determined through the disk diffusion test. The overall prevalence of S. aureus in mastitis-affected buffaloes was found to be 75%, of which 52.1% were resistant to erythromycin and 42.8% to clindamycin. S. aureus isolates recovered from milker nasal samples showed 56.25% resistance to erythromycin and 44% resistance to clindamycin. Genotypic antibiotic resistance profiles were determined from 14 milk samples through PCR. Overall, eight (52.1%), three (21.4%) and five (35.7%) S. aureus isolates were positive for the ermA, ermB and ermC genes, respectively. Moreover, 16 milker nasal S. aureus isolates were also tested for the presence of ermA, ermB and ermC genes. The ermA, ermB and ermC genes were observed in nine(56.7%), five (31.3%) and seven (43.7%) isolates, respectively. A significant association was shown between phenotypic and genotypic erythromycin resistance. The results indicate both that there are sufficient genetic similarities, and the actual transmission of erythromycin resistance genes between these two hosts of S. aureus.</i

Prevalence of Carbapenemase and Extended-Spectrum β-Lactamase Producing <i>Enterobacteriaceae</i>: A Cross-Sectional Study

Enterobacteriaceae have been classified as severely drug resistant bacteria by the World Health Organization due to their extensive production and dissemination of carbapenemases (CPs) and extended-spectrum β-lactamases (ESBL). The current study was conducted with the aim to determine the prevalence of CP- and ESBL-producing Enterobacteriaceae, as well as their antibiotic susceptibility profiles. For this, a hospital-based study was conducted which included 384 participants with bacterial infections. The collection and processing of specimens was conducted per standard microbiological protocol. The samples were inoculated on agar media plates to obtain the bacterial growths, and if they were positive for any bacterial growth, the antibiotic susceptibility testing was performed using disk diffusion method to check their antibiotic susceptibility patterns. The double disc diffusion as well as carbapenem inhibition techniques were used to examine the CP enzymes. Multiplex real-time PCR technique was performed to identify three distinct genetic types of CPs that have been identified in the Enterobacteriaceae (KPC, NDM, and OXA-48). A majority of participants (58.3%) in the current study were living in urban areas. A total of 227 (59.1%) patients were hospitalized. Furthermore, 26.04% of the patients were determined to be suffering from infections with Enterobacteriaceae. Escherichia coli was the most prevalent (9.1%) isolate overall, followed by Klebsiella pneumoniae (8.07%), Acinetobacter baumannii (2.6%), Pseudomonas aeruginosa (3.1%), Enterobacter cloacae (1.3%), Proteus spp. (1.3%), and Morganella spp. (0.5%). The studied patients were suffering from urinary tract infections (48.6%), blood stream infections (32.2%), wounds infection (11.9%), and respiratory infections (7.03%), confirmed with bacterial cultures. The resistance against carbapenems was seen in 31.4% of E. coli isolates, 25.8% in K. pneumoniae, 50% in P. aeruginosa, 25% in A. baumannii, and 20% in E. cloacae isolates. Such high rates of CP- and ESBL-producing Enterobacteriaceae are alarming, suggesting high spread in the study area. It is advised to implement better infection prevention and control strategies and conduct further nationwide screening of the carriers of these pathogens. This might help in reducing the burden of highly resistant bugs

Molecular Characterization of Community- and Hospital- Acquired Methicillin-Resistant <i>Staphylococcus aureus</i> Isolates during COVID-19 Pandemic

Methicillin-resistant Staphylococcus aureus (MRSA) is a drug-resistant superbug that causes various types of community- and hospital-acquired infectious diseases. The current study was aimed to see the genetic characteristics and gene expression of MRSA isolates of nosocomial origin. A total of 221 MRSA isolates were identified from 2965 clinical samples. To identify the bacterial isolates, the clinical samples were inoculated on blood agar media plates first and incubated at 37 °C for 18–24 h. For further identification, the Gram staining and various biochemical tests were performed once the colonies appeared on the inoculated agar plates. The phenotypic identification of antibiotic susceptibility patterns was carried out using Kirby–Bauer disk diffusion method by following the Clinical and Laboratory Standards Institute (CLSI) 2019 guidelines. The biofilm-producing potentials of MRSA were checked quantitatively using a spectrophotometric assay. All strains were characterized genotypically by SCCmec and agr typing using the specific gene primers. Furthermore, a total of twelve adhesion genes were amplified in all MRSA isolates. MRSA was a frequently isolated pathogen (44% community acquired (CA)-MRSA and 56% hospital acquired (HA)-MRSA), respectively. Most of the MRSA isolates were weak biofilm producers (78%), followed by moderate (25%) and strong (7%) biofilm producers, respectively. Prominent adhesion genes were clfB (100%), icaAD (91%), fib (91%), sdrC (91%) followed by eno (89%), fnbA (77%), sdrE (67%), icaBC (65%), clfA (65%), fnbB (57%), sdrD (57%), and cna (48%), respectively. The results of the current study will help to understand and manage the spectrum of biofilm-producing MRSA-associated hospital-acquired infections and to provide potential molecular candidates for the identification of biofilm-producing MRSA

Prevalence of Bacterial Pathogens among Symptomatic-SARS-CoV-2 PCR-Negative Patients

The epidemiological and clinical aspects of coronavirus disease-2019 (COVID-19) have been subjected to several investigations, but little is known about symptomatic patients with negative SARS-CoV-2 PCR results. The current study investigated patients who presented to the hospital with respiratory symptoms (but negative SARS-CoV-2 RT-PCR results) to determine the prevalence of bacterial pathogens among these patients. A total of 1246 different samples were collected and 453 species of bacterial pathogens were identified by culture. Antibiotic susceptibility testing was performed via the Kirby Bauer disc diffusion test. Patients showed symptoms, such as fever (100%), cough (83%), tiredness (77%), loss of taste and smell (23%), rigors (93%), sweating (62%), and nausea (81%), but all tested negative for COVID-19 by PCR tests. Further examinations revealed additional and severe symptoms, such as sore throats (27%), body aches and pain (83%), diarrhea (11%), skin rashes (5%), eye irritation (21%), vomiting (42%), difficulty breathing (32%), and chest pain (67%). The sum of n = 1246 included the following: males, 289 were between 5 and 14 years, 183 (15–24 years), 157 (25–34 years), 113 (35–49 years), and 43 were 50+ years. Females: 138 were between 5 and 14 years, 93 (15–24 years), 72 (25–34 years), 89 (35–49 years), and 68 were 50+ years. The Gram-positive organisms isolated were Staphylococcus aureus (n = 111, 80.43%, MRSA 16.6%), E. faecalis (n = 20, 14.49%, VRE: 9.4%), and Streptococcus agalactiae (n = 7, 5.07%), while, Gram-negative organisms, such as E. coli (n = 135, 42.85%, CRE: 3.49%), K. pneumoniae (n = 93, 29.52%, CRE: 1.58%), P. aeruginosa (n = 43, 13.65%), C. freundii (n = 21, 6.66%), Serratia spp. (n = 8, 2.53%), and Proteus spp. (n = 15, 4.76%) were identified

Heavy Metal (Arsenic) Induced Antibiotic Resistance among Extended-Spectrum &beta;-Lactamase (ESBL) Producing Bacteria of Nosocomial Origin

Antimicrobial resistance (AMR) is a leading cause of treatment failure for many infectious diseases worldwide. Improper overdosing and the misuse of antibiotics contributes significantly to the emergence of drug-resistant bacteria. The co-contamination of heavy metals and antibiotic compounds existing in the environment might also be involved in the spread of AMR. The current study was designed to test the efficacy of heavy metals (arsenic) induced AMR patterns in clinically isolated extended-spectrum &beta;-lactamase (ESBL) producing bacteria. A total of 300 clinically isolated ESBL-producing bacteria were collected from a tertiary care hospital in Lahore, Pakistan, with the demographic characteristics of patients. After the collection of bacterial isolates, these were reinoculated on agar media for reidentification purposes. Direct antimicrobial sensitivity testing (AST) for bacterial isolates by disk diffusion methods was used to determine the AST patterns with and without heavy metal. The heavy metal was concentrated in dilutions of 1.25 g/mL. The collected bacterial isolates were isolated from wounds (n = 63, 21%), urine (n = 112, 37.3%), blood (n = 43, 14.3%), pus (n = 49, 16.3%), and aspirate (n = 33, 11%) samples. From the total 300 bacterial isolates, n = 172 were Escherichia coli (57.3%), 57 were Klebsiella spp. (19%), 32 were Pseudomonas aeruginosa (10.6%), 21 were Proteus mirabilis (7%) and 18 were Enterobacter spp. (6%). Most of the antibiotic drugs were found resistant to tested bacteria. Colistin and Polymyxin-B showed the highest sensitivity against all tested bacteria, but when tested with heavy metals, these antibiotics were also found to be significantly resistant. We found that heavy metals induced the resistance capability in bacterial isolates, which leads to higher AMR patterns as compared to without heavy metal tested isolates. The results of the current study explored the heavy metal as an inducer of AMR and may contribute to the formation and spread of AMR in settings that are contaminated with heavy metals

Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI’s applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor’s prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains