TClustVID: A Novel Machine Learning Classification Model to Investigate Topics and Sentiment inCOVID-19 Tweets

COVID-19, caused by the SARS-Cov2, varies greatly in its severity but represent serious respiratory symptoms with vascular and other complications, particularly in older adults. The disease can be spread by both symptomatic and asymptomatic infected individuals, and remains uncertainty over key aspects of its infectivity, no effective remedy yet exists and this disease causes severe economic effects globally. For these reasons, COVID-19 is the subject of intense and widespread discussion on social media platforms including Facebook and Twitter. These public forums substantially impact on public opinions in some cases and exacerbate widespread panic and misinformation spread during the crisis. Thus, this work aimed to design an intelligent clustering-based classification and topics extracting model (named TClustVID) that analyze COVID-19-related public tweets to extract significant sentiments with high accuracy. We gathered COVID-19 Twitter datasets from the IEEE Dataport repository and employed a range of data preprocessing methods to clean the raw data, then applied tokenization and produced a word-to-index dictionary. Thereafter, different classifications were employed to Twitter datasets which enabled exploration of the performance of traditional and TclustVID classification methods. TClustVID showed higher performance compared to the traditional classifiers determined by clustering criteria. Finally, we extracted significant topic clusters from TClustVID, split them into positive, neutral and negative clusters and implemented latent dirichlet allocation for extraction of popular COVID-19 topics. This approach identified common prevailing public opinions and concerns related to COVID-19, as well as attitudes to infection prevention strategies held by people from different countries concerning the current pandemic situation.

Fecal Carriage of Extended-Spectrum ß-Lactamases in Healthy Humans, Poultry, and Wild Birds in León, Nicaragua-A Shared Pool of blaCTX-M Genes and Possible Interspecies Clonal Spread of Extended-Spectrum ß-Lactamases-Producing Escherichia coli.

Antibiotic-resistant bacteria are a major concern in the healthcare of today, especially the increasing number of gram-negative bacteria producing ß-lactamases such as extended-spectrum ß-lactamases (ESBLs). However, little is known about the relationship of ESBL producers in humans and domestic and wild birds, especially in a low-income setting. Therefore, we studied the fecal carriage of ESBL-producing Escherichia coli and Klebsiella pneumoniae in healthy humans, poultry, and wild birds in the vicinity of León, Nicaragua. Three hundred fecal samples were collected during December 2012 from humans (n = 100), poultry (n = 100) and wild birds (n = 100). The samples were examined for ESBL-producing E. coli and K. pneumoniae, revealing the prevalence of 27% in humans, 13% in poultry, and 8% in wild birds. Further characterization of the ESBL-producing isolates was performed through polymerase chain reaction (PCR) (NDM, CTX-M), epidemiological typing (ERIC2-PCR), multilocus sequence typing, and sequencing. ESBL producers harbored blaCTX-M-2, blaCTX-M-15, blaCTX-M-22, and blaCTX-M-3 genotypes. The blaCTX-M-15 constituted the absolute majority of ESBL genes among all samples. ERIC-PCR demonstrated highly related E. coli clones among humans, poultry, and wild birds. Clinically relevant E. coli clone ST648 was found in humans and poultry. There is a shared pool of blaCTX-M genes between humans and domesticated and wild birds in Nicaragua, and the results suggest shared clones of ESBL-producing E. coli. The study adds to the notion that wild birds and poultry can pick up antibiotic-resistant bacteria of human origin and function as a melting pot of resistance. Structured surveillance programs of antimicrobial resistance and a more regulated prescription of antibiotics are warranted in Nicaragua.

Antimicrobial-resistant and ESBL-producing Escherichia coli in different ecological niches in Bangladesh.

INTRODUCTION: The rapid and wide-scale environmental spread of multidrug-resistant bacteria in different ecosystems has become a serious issue in recent years. OBJECTIVES: To investigate the epidemiology of antimicrobial resistance and extended spectrum beta-lactamase (ESBL) in Bangladeshi wild birds and aquatic environments, samples were taken from Open Bill Stork (Anastomus oscitans) (OBS) and the nearby water sources. METHODS: Water and fresh fecal samples were collected from several locations. All samples were processed and cultured for Escherichia coli and tested for antibiotic susceptibility against commonly used antibiotics. ESBL producers were characterized at genotypic level using polymerase chain reaction (PCR), sequencing, multilocus sequence typing, and rep-PCR. RESULTS AND DISCUSSION: A total of 76 E. coli isolates from the 170 OBS and 8 E. coli isolates from three river sources were isolated. In total, 29% of E. coli isolated from OBS and all of the E. coli isolated from water sources were resistant to at least one of the tested antimicrobials. Resistant phenotypes were observed with all antimicrobials except tigecycline, gentamicin, imipenem, and chloramphenicol. Multidrug resistance was observed in 2.6% of OBS and 37.5% of the water isolates. Also, 1.2% of the ESBL-producing E. coli were isolated from OBS, whereas 50% of the E. coli isolated from water sources were ESBL producers possessing the CTX-M-15 gene. The most concerning aspect of our findings was the presence of human-associated E. coli sequence types in the water samples, for example, ST156-complex156, ST10-complex10 and ST46. CONCLUSION: This study reports the presence of multidrug-resistant ESBL-producing E. coli in OBSs and nearby aquatic sources in Bangladesh.