Explore the vast range of titles available.

In recent years, traffic congestion prediction has led to a growing research area, especially of machine learning of artificial intelligence (AI). With the introduction of big data by stationary sensors or probe vehicle data and the development of new AI models in the last few decades, this research area has expanded extensively. Traffic congestion prediction, especially short-term traffic congestion prediction is made by evaluating different traffic parameters. Most of the researches focus on historical data in forecasting traffic congestion. However, a few articles made real-time traffic congestion prediction. This paper systematically summarises the existing research conducted by applying the various methodologies of AI, notably different machine learning models. The paper accumulates the models under respective branches of AI, and the strength and weaknesses of the models are summarised.

The objectives of this study were to isolate and identify Pasteurella multocida from fowl cholera (FC) suspected chicken, and to prepare and efficacy determination of formalin killed fowl cholera vaccine using the isolated P. multocida strain. A total of five suspected dead chickens were collected from Brothers Poultry Farm located at Gazipur district, Bangladesh. The samples were processed and the P. multocida was isolated through conventional bacteriological techniques, were finally confirmed by polymerase chain reaction using P. multocida specific primers targeting cap gene. The P. multocida isolate was used to develop a formalin killed fowl cholera vaccine. The efficacy of the newly prepared vaccine was determined in Starcross-579 chickens (n=30) aging 15 weeks either by injecting 1 mL (group-A; n=10) or 0.5 mL (group-B; n=10) vaccine containing approximately 3.2x108 CFU/mL P. multocida organism; 10 birds were kept as unvaccinated control. The sera from the vaccinated and control birds were collected and were subjected for antibody titre determination by enzyme-linked immunosorbent assay (ELISA). Finally the vaccinated birds were challenged using virulent strains of P. multocida to confer the protection against FC. P. multocida could be isolated from both the samples. The formalin killed vaccine prepared from the isolated bacteria was subjected for the determination of antibody titre in chicken, and found that the antibody titres in the birds of group A and group B were 4.513 and 4.07 respectively after primary vaccination, and 4.893 and 4.37 respectively after booster vaccination. Most of the vaccinated birds were found to be survived after challenging with virulent strain of P. multocida. It is concluded that the causal agent of FC (P. multocida) was successfully isolated from FC affected dead chickens. The prepared formalin killed fowl cholera vaccine induces protective immune response and conferred protection against challenge infection caused by the virulent strain of P. multocida.

Bacillus Calmette-Guérin (BCG) vaccination has recently been found to have beneficial effects among children infected other than Mycobacterium tuberculosis. Due to the paucity of data on the outcomes of children who had successful BCG vaccination following Expanded Programme on Immunization (EPI) schedule, we aimed to investigate the characteristics of such children and their outcomes who were hospitalized for severe malnutrition. A prospective observational study was conducted to determine the viral etiology of pneumonia in severely malnourished children those were admitted to the Dhaka Hospital of International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) between April 2015 and December 2017, constituted the study population. Using a case-control design for the analysis, children having BCG vaccination prior hospital admission were treated as cases (n = 611) and those without vaccination, constituted as controls (n = 83). Bi-variate analysis was conducted using socio-demographic, clinical, laboratory, and treatment characteristics on admission and outcomes during hospitalization. Finally, log-linear binomial regression analysis was done to identify independent impact of BCG vaccination. The cases more often presented with older age, have had lower proportion of maternal illiteracy, higher rate of breastfeeding, severe wasting and lower rate of hypoglycemia, compared to the controls. The cases were also found to have lower risk of severe sepsis and deaths, compared to the controls (for all, p<0.05). However, in log-linear binomial regression analysis, after adjusting for potential confounders, BCG vaccination following EPI schedule (RR:0.54; 95%CI = 0.33-0.89; p = 0.015) and breastfeeding (RR:0.53; 95%CI = 0.35-0.81; p = 0.003) were found to be protective for the development of severe sepsis. BCG vaccination and breastfeeding were found to be protective for the development of severe sepsis in hospitalized severely malnourished under-five children which underscores the importance of continuation of BCG vaccination at birth and breastfeeding up to two years of age.

The microbiota of the nasopharyngeal tract (NT) play a role in host immunity against respiratory infectious diseases. However, scant information is available on interactions of SARS-CoV-2 with the nasopharyngeal microbiome. This study characterizes the effects of SARS-CoV-2 infection on human nasopharyngeal microbiomes and their relevant metabolic functions. Twenty-two (n = 22) nasopharyngeal swab samples (including COVID-19 patients = 8, recovered humans = 7, and healthy people = 7) were collected, and underwent to RNAseq-based metagenomic investigation. Our RNAseq data mapped to 2281 bacterial species (including 1477, 919 and 676 in healthy, COVID-19 and recovered metagenomes, respectively) indicating a distinct microbiome dysbiosis. The COVID-19 and recovered samples included 67% and 77% opportunistic bacterial species, respectively compared to healthy controls. Notably, 79% commensal bacterial species found in healthy controls were not detected in COVID-19 and recovered people. Similar dysbiosis was also found in viral and archaeal fraction of the nasopharyngeal microbiomes. We also detected several altered metabolic pathways and functional genes in the progression and pathophysiology of COVID-19. The nasopharyngeal microbiome dysbiosis and their genomic features determined by our RNAseq analyses shed light on early interactions of SARS-CoV-2 with the nasopharyngeal resident microbiota that might be helpful for developing microbiome-based diagnostics and therapeutics for this novel pandemic disease.

Coronavirus disease 2019 (COVID-19) remains a major global health concern, with emerging evidence highlighting the role of the human microbiome in influencing disease severity. While extensive research has been conducted on COVID-19, studies examining host-pathogen interactions at the transcriptomic level remain limited. In this study, we investigated the metatranscriptomic profiles of forty nasopharyngeal samples collected from COVID-19 patients across different Bangladeshi cohorts. Sequencing data were processed to analyze taxonomic composition, microbial diversity, and antimicrobial resistance gene (ARG) patterns using multiple bioinformatic pipelines. COVID-19 positive and asymptomatic patients exhibited a higher abundance of pathogenic and multidrug-resistant bacteria, whereas COVID-19 negative individuals showed increased fungal diversity. Differential gene expression analysis revealed significant upregulation of immune response related genes, including pro-inflammatory cytokines, in COVID-19 positive cases. Notably, asymptomatic patients demonstrated reduced TLR4 expression, suggesting a potential reducing of innate immune activation, which may contribute to asymptomatic clinical outcomes. Additionally, functional enrichment highlighted active ARG expression in positive cases, indicating potential links between the respiratory microbiome and host immune modulation. These findings provide insights into the host-microbiome interplay underlying COVID-19 severity and highlight the need for further validation in larger, ethnically diverse cohorts with comprehensive clinical metadata.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID -19, is constantly evolving, requiring continuous genomic surveillance. In this study, we used whole-genome sequencing to investigate the genetic epidemiology of SARS-CoV-2 in Bangladesh, with particular emphasis on identifying dominant variants and associated mutations. We used high-throughput next-generation sequencing (NGS) to obtain DNA sequences from COVID-19 patient samples and compared these sequences to the Wuhan SARS-CoV-2 reference genome using the Global Initiative for Sharing All Influenza Data (GISAID). Our phylogenetic and mutational analyzes revealed that the majority (88%) of the samples belonged to the pangolin lineage B.1.1.25, whereas the remaining 11% were assigned to the parental lineage B.1.1. Two main mutations, D614G and P681R, were identified in the spike protein sequences of the samples. The D614G mutation, which is the most common, decreases S1 domain flexibility, whereas the P681R mutation may increase the severity of viral infections by increasing the binding affinity between the spike protein and the ACE2 receptor. We employed molecular modeling techniques, including protein modeling, molecular docking, and quantum mechanics/molecular mechanics (QM/MM) geometry optimization, to build and validate three-dimensional models of the S_D614G-ACE2 and S_P681R-ACE2 complexes from the predominant strains. The description of the binding mode and intermolecular contacts of the referenced systems suggests that the P681R mutation may be associated with increased viral pathogenicity in Bangladeshi patients due to enhanced electrostatic interactions between the mutant spike protein and the human ACE2 receptor, underscoring the importance of continuous genomic surveillance in the fight against COVID -19. Finally, the binding profile of the S_D614G-ACE2 and S_P681R-ACE2 complexes offer valuable insights to deeply understand the binding site characteristics that could help to develop antiviral therapeutics that inhibit protein–protein interactions between SARS-CoV-2 spike protein and human ACE2 receptor.

In recent years, the research on Coronavirus disease 2019 (COVID-19) has surged rapidly due to its infectious nature and epidemiological importance as a pandemic. Association of other pathogenic microbes or different human microbiomes with COVID-19 severity is well established. While much is known about COVID-19, studies exploring how host-pathogen interactions at the transcriptomic level influence disease severity are still limited. This research focuses on metatranscriptomic perspective of COVID-19 patients from different Bangladeshi cohorts. Metatranscriptomic sequencing was performed using the extracted RNA of forty different nasopharyngeal samples. After preprocessing and assembly of the genome sequence data, taxonomic identification and diversity along with antibiotic resistance pattern was analyzed using different bioinformatic pipelines. COVID-19 positive and asymptomatic positive patients had a higher abundance of pathogenic and multidrug resistant bacteria whereas the Healthy or recovered patients had higher fungal population. Differential gene expression analysis was also performed to identify the upregulated and downregulated genes responsible for different biological and immunological pathways of humans. Here, immunological response related genes were mostly upregulated in positive cases which was also evident in the proinflammatory cytokines upregulation. Moreover, asymptomatic positive cases showed low TLR-4 expression, which is key to recognizing pathogen-associated molecular patterns (PAMPs) and triggering pro-inflammatory immune responses. This study can clarify the gene expression and signaling pattern of COVID-19 patients with different severity. This may also suggest that some populations exhibit reduced basal expression of TLR-4, which may suppress innate immune activation following infection and contribute to asymptomatic clinical outcomes; however, this hypothesis requires further investigation. Future studies should aim to validate these associations using larger, ethnically diverse cohorts with comprehensive clinical and demographic data.