Early diagnosis increases the treatment success rate for active tuberculosis (ATB) and decreases mortality. MicroRNAs (miRNAs) have been studied as blood-based markers of several infectious diseases. We performed miRNA profiling to identify differentially expressed (DE) miRNAs using whole blood samples from 10 healthy controls (HCs), 15 subjects with latent tuberculosis infection (LTBI), and 12 patients with ATB, and investigated the expression of the top six miRNAs at diagnosis and over the treatment period in addition to performing miRNA-target gene network and gene ontology analyses. miRNA profiling identified 84 DE miRNAs in patients with ATB, including 80 upregulated and four downregulated miRNAs. Receiver operating characteristic curves of the top six miRNAs exhibited excellent distinguishing efficiency with an area under curve (AUC) value > 0.85. Among them, miR-199a-3p and miR-6886-3p can differentiate between ATB and LTBI. Anti-TB treatment restored the levels of miR-199b-3p, miR-199a-3p, miR-16-5p, and miR-374c-5p to HC levels. Furthermore, 108 predicted target genes were related to the regulation of cellular amide metabolism, intrinsic apoptotic signaling, translation, transforming growth factor beta receptor signaling, and cysteine-type endopeptidase activity. The DE miRNAs identified herein are potential biomarkers for diagnosis and therapeutic monitoring in ATB.

Antimicrobial resistance is a global health problem. Among various antibiotic-resistant bacteria, Staphylococcus aureus , particularly methicillin-resistant S. aureus (MRSA), is a clinically important pathogen responsible for serious infections because of its multidrug resistance (MDR) and association with high mortality rates. The MDR nature of MRSA, including resistance to macrolides, aminoglycosides, fluoroquinolones, and tetracyclines, limits therapeutic choices and poses significant challenges in clinical management. This study aimed to analyze the correlation between mutations in the quinolone resistance-determining region (QRDR) and the minimum inhibitory concentration (MIC) of fluoroquinolone drugs, such as ciprofloxacin and levofloxacin, in MRSA and methicillin-sensitive S. aureus (MSSA). A total of 63 S . aureus clinical strains were isolated from blood samples of sepsis patients. DNA sequence analysis was performed using gDNA extracted from all S. aureus clinical isolates to identify mutations in the QRDR of gyr A, gyr B, par C, and par E. The MICs of antimicrobials were determined by the broth microdilution method. Among these genes, only mutations in par C showed a statistically significant positive correlation with elevated MIC levels, underscoring the primary role of par C in mediating resistance in our clinical isolates. Notably, all isolates exhibited a substitution at serine 80 (S80) in par C, and those harboring simultaneous substitutions at both S80 and glutamic acid 84 (E84) demonstrated markedly increased MIC values for both drugs. These findings reinforce previously reported associations between dual mutations and high-level fluoroquinolone resistance, while highlighting the distinct contribution of par C among the QRDR genes analyzed in this study. Furthermore, we found that the most frequent mutation in the QRDR was the cytosine-to-thymine mutation. IMPORTANCE: Antimicrobial resistance is a growing global health crisis, making bacterial infections harder to treat. Staphylococcus aureus , especially MRSA, is a major concern due to its resistance to multiple antibiotics, including fluoroquinolones like ciprofloxacin and levofloxacin. Our study highlights how specific genetic mutations in the quinolone resistance-determining region (QRDR) influence fluoroquinolone resistance. We found that mutations in the par C gene, particularly substitutions at serine 80 (S80) and glutamic acid 84 (E84), significantly increase resistance. Understanding these mutations helps predict antibiotic resistance and may guide more effective treatment strategies. By identifying key genetic changes that drive fluoroquinolone resistance, our research contributes to developing improved diagnostic tools and targeted therapies to combat drug-resistant S. aureus infections. This knowledge is crucial for clinicians and researchers working to control the spread of antibiotic-resistant bacteria and improve patient outcomes.

Tuberculosis (TB) management is important for prompt discrimination of latent TB infection (LTBI) from active TB and proper treatment. Whole blood Interferon-gamma (IFN-γ) release assay (IGRA) is used to diagnose LTBI based on the secretion of IFN-γ by T-cells in the whole blood by using a specific antigen of Mycobacterium tuberculosis. However, the ability of IGRA to distinguish active TB from LTBI is considerably limited. Distinguishing active TB from LTBI is necessary to identify indicators that can be used to effectively manage TB and develop diagnostic methods. In the present study, we used a Luminex multiplex bead array (a bead-based antibody–antigen sandwich method). The whole blood level of acute phase proteins (APPs), such as endoglin (ENG), procalcitonin (PCT), C-reactive protein (CRP), and α1-acid glycoprotein (AGP), in active TB, LTBI, and healthy individuals were analyzed and quantified. The APP test results for the serum and whole blood samples showed that the levels of PCT, CRP, and AGP were significantly increased (p < 0.0500; area under curve = 0.955) in active TB. The level of these markers in the whole blood of active TB, LTBI, and healthy individuals could provide data for effective diagnosis and treatment of TB.

Tuberculosis (TB), which is caused by Mycobacterium tuberculosis (MTB), is a serious infectious disease with high infection and mortality rates and is a public health problem around the world. According to the World Health Organization (WHO) report, one-third of the world's population is latently infected with MTB, and 5 to 10% of those with latent TB infection (LTBI) have the potential to develop active TB once in their lifetime. Therefore, TB management for promptly distinguishing LTBI from active TB and for proper treatment is important. LTBI is currently diagnosed using the tuberculin skin test (TST) and interferon gamma (IFN-γ) release assay (IGRA). However, this test is substantially limited by its inability to distinguish active TB from LTBI. It is necessary to discover indicators that can be used for effective TB management and to develop diagnostic methods. In the present study, we used IGRA and complete blood count (CBC) analysis for discrimination of active TB, LTBI, and healthy control groups. The results showed that the number of WBC was significantly increased in the group with active TB (p < 0.0100) and level of hemoglobin (Hb) was significantly decreased (p < 0.0010) in the CBC than those of the healthy control and LTBI groups. In the WBC differential count, the number of neutrophils and monocytes were increased (p < 0.0010) in active TB group, where as those of lymphocytes were significantly decreased (p < 0.0100) in active TB group compared healthy control group. Results verified that the levels of total WBC, Hb, neutrophils, lymphocytes and monocytes were statistically significant (p < 0.0500) and the AUC was approximately 0.8613. In addition, receiver operating characteristic (ROC) curve analysis was performed to confirm the clinical usefulness between active TB and healthy control groups. In conclusion, based on these data demonstrated that the usefulness of these potential indicators for differential diagnosis, according to the result can be provided for effective diagnosis and treatment by comparing the expression patterns of the markers in the whole blood of the active TB, LTBI, and healthy control groups. Furthermore, this study needs to investigate a larger number of clinical specimens later to develop biomarkers according to the state of infection with MTB such as LTBI and active TB, as well as after treatment.

The present study aimed to clinically evaluate the effect of T-cell dysfunction in hemodialysis (HD) patients with latent tuberculosis (TB) infection (LTBI) who were false-negatives in the QuantiFERON-TB Gold In-Tube (QFT-GIT) test. Whole blood samples from a total of 20 active TB patients, 83 HD patients, and 52 healthy individuals were collected, and the QFT-GIT test was used for measuring Mycobacterium tuberculosis (MTB)-specific interferon gamma (IFN-γ) level. The positive rate of the IFN-γ release assays (IGRAs) in HD patients was lower than the negative rate. The mean value of MTB-specific IFN-γ level, which determines the positive rate of the IGRA test, was highest in active TB, followed by HD patients and healthy individuals. Among HD patients, phytohemagglutinin A (PHA)-stimulated IFN-γ levels of approximately 40% were 10.00 IU/mL or less. However, there was no low level of PHA-stimulated IFN-γ in the healthy individuals. This reveals that T-cell function in HD patients was reduced compared to healthy individuals, which leads to the possibility that QFT-GIT results in HD patients are false-negative. The clinical manifestations of TB in patients on HD are quite non-specific, making timely diagnosis difficult and delaying the initiation of curative treatment, delay being a major determinant of outcome.

Post-mortem interval (PMI) analysis plays a crucial role in forensic investigations, providing essential insights into the time since death. This study examined histological changes and ribonucleic acid (RNA) quantification across major organs to identify molecular indicators for PMI estimation. Because RNA gradually degrades after death, understanding its stability under different tissue, temperature, and PMI conditions provides valuable forensic insights. We analyzed post-mortem changes in total RNA from the heart, kidney, liver, and lung tissues of Sprague Dawley rats stored at 4 °C and 26 °C. Tissue samples were collected at various PMIs and evaluated histologically for cellular integrity. Total RNA concentration and purity were measured, and complementary DNA (cDNA) was synthesized for molecular analysis. Expression levels of 5S rRNA, B2m, Gapdh, and Sort1 were quantified using reverse transcription quantitative PCR (RT-qPCR). The results showed that PMI and organ type significantly affected total RNA concentration, whereas temperature exerted only a minor effect. Among the four target genes, 5S rRNA exhibited the lowest Ct values, indicating the highest stability. Notably, RNA degradation patterns varied with temperature, particularly in kidney and liver tissues. These findings suggest that RNA-based molecular markers, particularly 5S rRNA, may serve as promising indicators for accurate PMI estimation.