Genomic Sequence of Five New Intronic Variants of HLA-DQB1*03 Characterised by Next-Generation Sequencing.
Genomic sequences of the HLA-DQB1*03:01:01:70, -DQB1*03:01:01:77, -DQB1*03:02:01:28, -DQB1*03:02:01:29, and -DQB1*03:03:02:19 alleles.
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Genomic sequences of the HLA-DQB1*03:01:01:70, -DQB1*03:01:01:77, -DQB1*03:02:01:28, -DQB1*03:02:01:29, and -DQB1*03:03:02:19 alleles.
The HLA-DPA1*02:02:02:22 allele differs from HLA-DPA1*02:02:02:01 by a single nucleotide substitution in intron 1.
The novel HLA-A*03:01:133 allele differs from A*03:01:01:01 by a change of C ➔ T in exon 4.
HLA-DPB1*1469:01 shows a non-synonymous mutation in codon 205 within Exon 4 compared with HLA-DPB1*25:01.
HLA-DQA1*03:63 differs from HLA-DQA1*03:02:01:01 by a single nucleotide substitution at position 722 G>A.
The HLA-C*15:02:01:66 allele differs from HLA-C*15:02:01:01 by a single-nucleotide substitution in Intron 6.
The HLA-C*12:72 allele, differs from HLA-C*12:02:02:01, by one nonsynonymous substitution, c.312C>A in exon 2.
Compared with the HLA-B*55:04 allele, HLA-B*55:135 shows two nucleotide substitutions in exon 2 (codon 63 AAC>GAG).
HLA-B*08:01:80 differs from HLA-B*08:01:01:01 by one nucleotide substitution in exon 2-437 G>A.
HLA-C*08:01:37 differs from HLA-C*08:01:01:01 by one single nucleotide substitution at position 927 G>A in exon 5.
HLA-C*07:1193 differs from HLA-C*07:02:01:03 in exon 5 codon 292 (GCT>GTT).
HLA-A*02:540:02N differs from A*02:01:01:01 by one nucleotide substitution in codon 99 in exon 3.
HLA-A*23:163 differs from HLA-A*23:01:01:03 by a single nucleotide substitution at position 925 of the cDNA.
HLA-DQB1*06:03:60 differs from HLA-DQB1*06:03:01:01 by a single synonymous nucleotide substitution at position 174 in Exon 2.
HLA-DQB1*02:02:41 differs from HLA-DQB1*02:02:01:01 by one synonymous nucleotide substitution at Codon 39 in Exon 2.
HLA-A*02:1229 differs from HLA-A*02:07:01:01 by a single nucleotide substitution at position 1014 T>A.
BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.
OBJECTIVES: Traditional periodontal therapy primarily focuses on bacterial biofilm control; however, recent evidence also suggests a critical role for the oral mycobiome. This study evaluated the clinical and ecological impact of a novel mouthwash formulation containing hyaluronic acid (HA), hydrogen peroxide (H2O2), and glycine on periodontal patients METHODS: This prospective, randomized split-mouth trial included 13 adult participants with periodontitis treated with HA-H2O2-glycine formula (BMG0703A) used twice a day for seven days. Subgingival plaque samples were collected from periodontal pocket and healthy control sites at baseline (T0) and one-week post-treatment (T1). Microbial and fungal communities were characterized using Next-Generation Sequencing (NGS) of the 16S rRNA and ITS2 regions. Linear Mixed Models (LMM) and Spearman correlation were used to assess taxonomic shifts and cross-kingdom relationships. RESULTS: Sequencing revealed a promising ecological shift: the bacteriome shifted from anaerobic dominance (Olsenella, Peptostreptococcus) toward a health-associated aerobic profile, with Rothia near-doubling (11.91% to 22.68%). The mycobiome underwent a "normalization" effect: Candida abundance decreased significantly (22.8% to 9.1%), while fungal Shannon diversity in pockets returned to healthy-site levels. Inter-kingdom analysis identified antagonistic relationships between expanding commensal bacteria and opportunistic fungi, suggesting that the intervention may help re-establish a protective bacterial niche. CONCLUSIONS: The HA-H2O2-glycine formulation seems to facilitate a rapid, cross-kingdom modulation of the subgingival niche. By reducing anaerobic pathogens and normalizing the mycobiome it appear to induce short-term changes, suggesting potential as adjunctive strategy in periodontal management. CLINICAL SIGNIFICANCE: The present work underlines the possible cross-Kingdom effects of a novel compound.