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Liver cancer is the fourth most deadly cancer, and early detection and timely treatment apparently play a crucial role in it. Intestinal bacteria affect the development of liver cancer through various pathways. In this study, the gut bacteria of liver cancer patients are analysed in detail by using metagenomic sequencing technology, and some of the bacterial species and metabolic pathways that may affect the development of liver cancer have been identified. Additionally, we identified bacterial factors that may impact key clinical indicators of the tumour. The findings of this study provide a scientific foundation for understanding the mechanisms underlying liver cancer development. This study freshened insights into clinical treatment strategies for liver cancer.

Background. The novel coronavirus disease 2019 (COVID-19) has highlighted vulnerabilities in healthcare systems and has brought the world to a standstill single-handedly. Diagnostic testing for COVID-19 is critical for understanding epidemiology, contact tracing, case management and controlling the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Real-time reverse transcription PCR test, the gold standard test, involves fairly complex steps and takes nearly 24-48 h to generate the results. GeneXpert is a rapid nucleic-acid-detection-based test approved by the Indian Council of Medical Research, which can shorten the turnaround time significantly. Aim. The study aimed to compare the performance of GeneXpert against the gold standard real-time reverse transcription PCR for SARS-CoV-2. Materials and methods. This retrospective study was conducted at a tertiary care centre from 25 March 2020 to 8 December 2020. The nasopharyngeal/oropharyngeal swabs that were sent to the Viral Research and Diagnostic Laboratory for testing of SARS-CoV-2 by GeneXpert [cartridge-based nucleic acid amplification test (CBNAAT)] were included for the study. A total of 270 samples (220 samples positive and 50 samples negative for SARS-CoV-2 by GeneXpert) were simultaneously tested for real-time reverse transcription PCR. Real-time reverse transcription PCR was considered as gold standard test (reference) for calculating the sensitivity and specificity of the GeneXpert (CBNAAT) test. Results. Out of the total samples tested (n=270) for SARS-CoV-2, 220 were positive, and 50 were negative for SARS-CoV-2 by GeneXpert. Among 220 GeneXpert SARS-CoV-2-positive samples, 118 (53.64%) were also positive by real-time reverse transcription PCR, while 102 (46.36%) showed negative results by real-time reverse transcription PCR. However, 50 GeneXpert negative samples showed 100% agreement with real-time reverse transcription PCR, i.e. they were also negative by real-time reverse transcription PCR. The GeneXpert sensitivity and specificity for COVID-19 were seen to be 100% (95% CI: 96.92-100%) and 32.89% (95% CI: 25.50-40.97%), respectively, as compared to the gold standard real-time reverse transcription PCR test. The positive predictive value and negative predictive value of GeneXpert for COVID-19 were found to be 53.64% and 100%, respectively. Conclusion. This study highlights that the GeneXpert test is highly sensitive and found to be useful in emergency and challenging situations for rapidly ruling out negative cases. However, due to its relatively low specificity, positive results should be confirmed with real-time reverse transcription PCR. Therefore, it can serve as a valuable tool for patients requiring urgent care by facilitating early diagnosis and management of COVID-19, ultimately contributing to preventing morbidity and mortality.

The increasing complexity and collaborative nature of scientific research projects underscore the need to implement project management practices to manage resources and funding, ensure data quality and prevent delays in project progress. Here, we introduce three major project management methodologies, including agile, waterfall and hybrid approaches, and explore their suitability for biological and microbiological research laboratories. Variables that may influence choosing an appropriate strategy for managing projects are considered, including the size and experience of a research group. In the following article, we provide an overview of the five major stages of project planning and execution, focusing on implementing each of the discussed strategies in the research laboratory. Furthermore, we discuss the composition of the research team and outline the responsibilities assigned to each team member based on their role in the project. This paper highlights potential risks and challenges that may negatively impact research progress, underscoring the need for proper project planning. Applying proper project management methodologies is often neglected in academic research, leading to serious delays and waste of valuable resources.

Blastomycosis is a serious fungal disease affecting humans and animals. It is typically caused by the thermally dimorphic fungus, Blastomyces dermatitidis. In this report, we describe an infection caused by the cryptic fungal species, Blastomyces gilchristii, in a tiger (Panthera tigris).

The kynurenine (KYN) pathway is the major catabolic pathway for tryptophan in humans, producing several metabolites that influence health. In clinical settings, KYN levels serve as a valuable biomarker for the diagnosis and prognosis of inflammatory and neurological diseases. Nevertheless, KYN detection relies on mass spectrometry analysis, which requires specialized knowledge and expertise with high operational costs. The bacterial biosensor presents as a promising tool for rapid and cost-effective targeted substance detection due to its ease of genetic modification. Therefore, this study aimed to develop an engineered bacterial biosensor by integrating a genetic module in a plasmid designed for KYN detection harboured in an Escherichia coli chassis. The KYN biosensing component in the genetic module encodes a KYN pathway regulator (KynR) from Pseudomonas aeruginosa, driven by the P_BAD arabinose-inducible promoter. Upon expression, KynR would bind to the exogenous KYN and the bacterial responding kyn promoter to express the downstream green fluorescent protein gene to emit a fluorescence signal. However, despite successful induction by arabinose and the presence of KYN, biosensors with different gene orientations and genetic components failed to produce a significant fluorescence signal. These findings suggest that the sensitivity of P. aeruginosa KynR is insufficient to detect physiological levels of KYN. Further exploration of alternative biological sensing components is warranted.

Introduction. Despite the introduction 40 years ago of effective and low-cost treatment for tuberculosis (TB), morbidity and mortality from this disease remain substantial worldwide. According to the WHO, TB is once again the leading cause of death worldwide from a single infectious agent. In 2023, TB caused ~1.25 million deaths, surpassing COVID-19. In Morocco, the number of new TB cases rose from 30,897 in 2017 to 35,000 in 2019, highlighting a concerning upward trend that underscores the persistent challenge TB poses to the country's public health system. The incidence of multidrug-resistant (MDR) or rifampicin (RIF)-resistant TB was estimated at 1.7 per 100,000 inhabitants. Isoniazid (INH) is a cornerstone of first-line TB treatment, and resistance to it, even in the absence of RIF resistance, is associated with delayed treatment response, higher rates of treatment failure or relapse and increased risk of progression to MDR-TB if not promptly identified and appropriately managed. Moreover, current diagnostic algorithms in many settings, including Morocco, may miss INH monoresistance due to their reliance on rapid molecular tests that primarily detect RIF resistance, further emphasizing the emerging threat of drug-resistant TB. Despite this, national data on INH monoresistance remain scarce. Given the increasing burden of TB and the critical importance of early detection of drug resistance, it is essential to better understand patterns of resistance beyond RIF. It is within this context that we conducted the present study, which aims to investigate INH resistance in TB cases (pulmonary or extrapulmonary, new or previously treated) over a period of 3 years. Materials and methods. This is a retrospective study conducted at the Bacteriology Department of Mohammed V Military Instruction Hospital over a period of 3 years. Data were collected via the laboratory information system. Clinical samples underwent treatment using both conventional bacteriological methods and molecular techniques. The study of resistance to major anti-TB drugs was performed using the reverse hybridization technique, specifically the HAIN method (GenoType^® MTBDR plus by Hain Lifescience). Statistical analysis was performed using IBM SPSS Statistics 19 and Microsoft Excel 2019. Results. The study involved 464 patients treated for pulmonary and extrapulmonary TB, including both new cases and those previously treated with positive cultures. The mean age of the patients was 42.2 years, with a range from 8 to 88 years. There was a predominance of males at 74%, with a sex ratio of 2.8. Pulmonary sputum samples accounted for 84.8% of the cases, whereas extrapulmonary samples represented only 15.2%, and the positivity rates for direct examination and culture across all samples were 74% and 100%, respectively. INH resistance had a prevalence of 9% (43 out of 464). Genetic mutations observed indicated that 63% of the clinical isolates resistant to

Cryptosporidium, a protozoan parasite of significant public health concern, is responsible for severe diarrhoeal disease, particularly in immunocompromised individuals and young children in resource-limited settings. Analysis of whole-genome next-generation sequencing (NGS) data is critical in improving our understanding of Cryptosporidium epidemiology, transmission and diversity. However, effective analysis of NGS data in a public health context necessitates the development of robust, validated computational tools. We present Parapipe, an ISO-accreditable bioinformatic pipeline for high-throughput analysis of NGS data from Cryptosporidium and related taxa. Built using Nextflow DSL2 and containerized with Singularity, Parapipe is modular, portable, scalable and designed for use by public health laboratories. Using both simulated and real Cryptosporidium datasets, we demonstrate the power of Parapipe's genomic analysis for generating epidemiological insights. We highlight how whole-genome analysis yields substantially greater phylogenetic resolution than conventional gp60 molecular typing in Cryptosporidium parvum. Uniquely, Parapipe facilitates the integration of mixed infection analysis and phylogenomic clustering with epidemiological metadata, representing a powerful tool in the investigation of complex transmission pathways and identification of outbreak sources. Parapipe significantly advances genomic surveillance of Cryptosporidium, offering a streamlined, reproducible analytical framework. By automating a complex workflow and delivering detailed genomic characterization, Parapipe provides a valuable tool for public health agencies and researchers, supporting efforts to mitigate the global burden of cryptosporidiosis.

Large-scale skin microbiome studies are often restricted due to the need for participants to visit a research centre to have their skin swabbed by a trained individual. If samples taken by participants at home returned high-quality data, similar to that generated from samples taken by trained experts under controlled conditions, it would provide the potential for studies to have larger cohorts, include participants from multiple locations and facilitate longitudinal sample collection. Here, we describe the development of a novel unsupervised skin microbiome sample collection method and compare the data quality with that of supervised, in-lab sample collection. We enrolled 57 participants to collect skin swabs from their axillae, forearms, cheeks and scalps. Initially, samples were collected in our research centre under strict supervision by a trained expert. Participants then collected swabs from the same body sites 24 h later, unsupervised, at home, which they returned to the research centre within 3-5 days. All samples then underwent bacterial DNA extraction and 16S rRNA gene sequencing. Yield of extracted bacterial DNA was different depending on body site, with the dry swabs from the forearm producing the lowest amount. There were no significant differences in alpha and beta-diversities between supervised and unsupervised sampling methods, regardless of body site. Taxonomic analysis of bacterial genera also did not differ for axilla, cheek or scalp. Our data suggest that self-sampling skin microbiome methods can produce data that are comparable to samples collected under the supervision of a trained expert in lab settings. These findings should encourage the scalability of future research and allow for greater representative population diversity in genomic and microbiome research.

Rapid and accurate detection of vancomycin-resistant enterococci (VREs) can aid in the early application of appropriate antimicrobial treatment and the implementation of infection prevention measures. The VIASURE real-time PCR assay (Certest Biotec) is a multiplex nucleic acid-based in vitro diagnostic test intended for the detection of vanA and vanB, and geneLEAD VIII (Precision System Science) is a customizable, fully automated molecular detection platform. We evaluated the performance of the VIASURE assay on the geneLEAD VIII platform against 200 clinical enterococcal isolates consisting of 151 VREs and 49 vancomycin-susceptible enterococci collected in Japan, primarily in the Kinki region, and compared it to that of the in-house reference multiplex PCR assay. The performance of the VIASURE assay for the detection of vanA and vanB was comparable to that of the reference multiplex PCR assay, with both a sensitivity and specificity of 100%. Compared with the reference PCR assay, the VIASURE assay reduced the turn-around time by ~3 h 40 min (5 h 34 min vs. 1 h 54 min) and the hands-on time by 46 min per four samples. Fully automated molecular detection of vanA and vanB using the VIASURE assay and geneLEAD VIII for bacterial isolates can enable fast and reliable testing while reducing labour and is a promising tool for clinical laboratories and nosocomial infection control.

Background. Human immunodeficiency virus (HIV) is the major cause of failure to reach targets of tuberculosis (TB) control in settings with high HIV loads. TB, on the other hand, enhances the progression of HIV infection to AIDS. This study was done to understand the epidemiological and clinical profile of HIV-TB co-infected patients and to study the impact of TB on the recovery of CD4 counts. Methodology. An observational study was conducted in which of the 573 patients newly diagnosed with HIV infection and enrolled at the antiretroviral therapy (ART) centre, King George's Medical University, Lucknow, between May 2021 and June 2022, 80 patients who also had newly diagnosed TB were included. These HIV-TB co-infected patients were analysed for demographic factors. Also, clusters of differentiation 4 (CD4) counts were done at the time of enrolment on ART and then later, ~6 to 8 months of recieving ART and anti-tubercular treatment (ATT) initiation. For comparison, of the 493 HIV-only patients, 50 age- and gender-matched consecutive patients for whom baseline and follow-up CD4 counts were available were enrolled as controls. The change from baseline CD4 count was calculated using a paired t-test and Wilcoxon signed rank test. Results. In the present study, among HIV-TB co-infected patients, baseline CD4 levels were 194.52±162.27, and follow-up CD4 levels were 285.09±170.33. A statistically significant increment of 90.57±165.60 in mean CD4 levels was observed (t=4.019; P<0.001). Likewise, in only HIV-positive patients, a statistically significant increment of 125.26±191.48 (35.75%) cells in mean CD4 levels was observed (t=4.626; P<0.001). The increase in CD4 counts in HIV only population was significantly higher than that observed in HIV-TB co0infected patients. Conclusion. Though significant rise in CD4 counts was observed in both HIV-TB co-infected patients and HIV-only patients after 6 to 8 months of appropriate therapy, the rise was significantly higher among the HIV-only group as compared to the HIV-TB co-infected group.