UNASSIGNED: Precise HDV-RNA detection and quantification are pivotal for diagnosis and monitoring of response to newly approved treatment. We evaluate the performance of three HDV RNA detection and quantification assays.
UNASSIGNED: Hepatitis Delta RT-PCR system kit, EurobioPlex HDV assay, and RoboGene HDV RNA Quantification kit 2.0 were used for testing 151 HBsAg-positive samples, 90 HDV-RNA negative and 61 HDV-RNA positive. We also evaluated serial dilutions of the WHO international standard for HDV, PEI 7657/12. All HDV-RNA positive samples were genotyped using a next-generation sequencing strategy.
UNASSIGNED: Qualitative results indicated a 100% concordance between tests. Quantitative results correlated well, r2 = 0.703 (Vircell-vs-Eurobio), r2 = 0.833 (Vircell-vs-RoboGene), r2 = 0.835 (Robogene-vs-Eurobio). Bias index was 2.083 (Vircell-vs-Eurobio), -1.283 (Vircell-vs-RoboGene), and -3.36 (Robogene-vs-Eurobio). Using the WHO IS, Vircell overestimated the viral load by 0.98 log IU/mL, Eurobio by 1.46 log IU/mL, and RoboGene underestimated it by 0.98 log IU/mL. Fifty-nine samples were successfully genotyped (Genotype 1, n=52; Genotype 5, n=7; Genotype 6, n=1), with similar results for correlation and bias.
UNASSIGNED: This study underscores the necessity of using reliable HDV-RNA detection and quantification assays, as evidenced by the high concordance rates in qualitative detection and the observed variability in quantitative results. These findings highlight the importance of consistent assay use in clinical practice to ensure accurate diagnosis and effective treatment monitoring of HDV infection.

The diagnosis of fungal infections presents several challenges and limitations, stemming from the similarities in symptomatology, diversity of underlying pathogenic species, complexity of fungal biology, and scarcity of rapid, affordable, and point-of-care approaches. In this review, we assess technological advances enabling the conversion of cutting-edge laboratory molecular diagnostic methods to cost-effective microfluidic devices. The most promising strategies toward the design of DNA sequence-based fungal diagnostic systems, capable of capturing and deciphering the highly informative DNA of the pathogen and adapted for resource-limited settings, are discussed, bridging fungal biology, molecular genetics, microfluidics, and biosensors.

Early diagnosis of infectious uveitis can lead to prompt initiation of treatment to minimize vision-threatening sequelae. As various infectious etiologies of uveitis share similar clinical features, advancements in polymerase chain reaction (PCR) and metagenomic next-generation sequencing (MDS) have shown significant promise in improving diagnostic capabilities. Various techniques of PCR, including real-time, multiplex, comprehensive, and broad-range, have increased the armamentarium for infectious uveitis diagnosis. Additionally, metagenomic deep sequencing technology has provided a methodology to identify causative pathogens as well as novel etiologies of uveitis. This review discusses the diagnostic tools available for infectious uveitis and highlights the advantages and disadvantages of the techniques.

BACKGROUND: Neonatal diabetes mellitus (NDM) is a rare non-immunological monogenic disorder characterized by hyperglycemic conditions primarily occurring within the first 6 months of life. The majority of cases are attributed to pathogenic variants in genes affecting beta-cell survival, insulin regulation, and secretion. This study aims to investigate the genetic landscape of NDM in Iran.
METHODS: We recruited a total of 135 patients who were initially diagnosed with diabetes at <12 months of age in Iran and referred to pediatric endocrinology clinics across the country. These patients underwent genetic diagnostic tests conducted by the Exeter Molecular Genetics Laboratory in the UK. The pathogenic variants identified were sorted and described based on type, pathogenicity (according to ACMG/AMP criteria), novelty, and the affected protein domain.
RESULTS: Genetic defects were identified in 93 probands, presenting various pathogenic abnormalities associated with NDM and its associated syndromes. 76% of the patients were born as a result of consanguineous marriage, and a familial history of diabetes was found in 43% of the cases. A total of 58 distinct variants in 14 different genes were discovered, including 20 variants reported for the first time. Causative variants were most frequently identified in EIF2AK3, KCNJ11, and ABCC8, respectively. Notably, EIF2AK3 and ABCC8 exhibited the highest number of novel variants.
CONCLUSIONS: These findings provide valuable insights into the genetic landscape of NDM in the Iranian population and contribute to the knowledge of novel pathogenic variants within known causative genes.

BACKGROUND: Molecular diagnosis in allergology helps to identify multiple allergenic molecules simultaneously. The use of purified and/or recombinant allergens increases the accuracy of individual sensitization profiles in allergic patients.
OBJECTIVE: To assess the impact of molecular diagnosis through the ImmunoCAPTM ISAC 112 microarray on etiological diagnosis and specific immunotherapy (SIT) prescription. This was compared to the use of conventional diagnoses in pediatric, adolescent, and young adult patients with rhinitis or rhinoconjunctivitis and/or allergic asthma, sensitized to three or more pollen allergens of different botanical species.
METHODS: A multicenter, prospective, observational study was conducted in patients aged 3-25 years who received care at the Allergology service of 14 hospitals in Catalonia from 2017 to 2020. Allergology diagnosis was established based on the patient\'s clinical assessment and the results of the skin prick test and specific immunoglobulin E assays. Subsequently, molecular diagnosis was conducted using ImmunoCAPTM ISAC® 112 to recombinant and/or purified allergen components.
RESULTS: A total of 109 patients were included; 35 (32.1%) were pediatric patients and 74 (67.9%) were adolescents or young adults (mean age: 18 years), with 58.0% being females. A change of 51.0% was observed in SIT prescription following molecular etiological diagnosis by means of a multi-parameter microarray.
CONCLUSIONS: Molecular diagnosis by means of multi-parameter tests increases the accuracy of etiological diagnosis and helps to define an accurate composition of SIT.

BACKGROUND: Heterakis gallinarum (H. gallinarum) is a common poultry parasite that can be found in the ceca of many gallinaceous bird species, causing minor pathology and reduced weight gain. Most infections go unnoticed in commercial flocks due to the dependence on fecal egg counts, which are prone to false-negative diagnoses. Furthermore, there is a lack of research on gastrointestinal nematodes that use molecular identification methods, which could be essential for rapid diagnosis and developing efficient control approaches. As a result, the study aimed to look at the cause of mortality in layer chickens induced by H. gallinarum in Egyptian poultry farms using morphological, ultrastructural, and molecular characterization. Histopathological, immunohistochemical, and cell-mediated immune responses from damaged cecal tissues were also examined.
RESULTS: Seventy bird samples from ten-layer flocks of different breeds (Native, white, and brown layers) suffering from diarrhea, decreased egg output, and emaciation were collected. Cecal samples were collected from affected and non-affected birds and were examined for parasitic diseases using light and a scanning electron microscope. The mitochondrial cytochrome oxidase 1 (COX1) gene was used to characterize H. gallinarum. Our results showed that the collected nematodal worms were identified as H. gallinarum (male and female), further confirmed by COX1 gene amplification and sequence alignment. Gene expression analysis of the inflammatory markers in infected tissues showed a significant up-regulation of IL-2, IFN-γ, TLR-4, and IL-1β and a significant down-regulation of the anti-inflammatory IL-10. The mRNA level of the apoptotic cas-3 revealed apoptotic activity among the H. gallinarum samples compared to the control group.
CONCLUSIONS: Our results implemented the use of molecular methods for the diagnosis of Heterakis, and this is the first report showing the tissue immune response following infection in layers: upregulation of IL-1β, IFN-γ, Il-2, and TLR-4, while down-regulation of anti-inflammatory IL-10 in cecal tissue, Cas-3 apoptotic activity and Nuclear factor-κB (NF-κB)activity with immunophenotyping of T-cells in Heterakis infected tissue.

UNASSIGNED: Tuberculosis, caused by Mycobacterium tuberculosis complex (MTBC), remains a global health concern in both human and animals. However, the absence of rapid, accurate, and highly sensitive detection methods to differentiate the major pathogens of MTBC, including M. tuberculosis, M. bovis, and BCG, poses a potential challenge.
UNASSIGNED: In this study, we have established a triplex droplet digital polymerase chain reaction (ddPCR) method employing three types of probe fluorophores, with targets M. tuberculosis (targeting CFP-10-ESAT-6 gene of RD1 and Rv0222 genes of RD4), M. bovis (targeting CFP-10-ESATs-6 gene of RD1), and BCG (targeting Rv3871 and Rv3879c genes of ΔRD1), respectively.
UNASSIGNED: Based on optimization of annealing temperature, sensitivity and repeatability, this method demonstrates a lower limit of detection (LOD) as 3.08 copies/reaction for M. tuberculosis, 4.47 copies/reaction for M. bovis and 3.59 copies/reaction for BCG, without cross-reaction to Mannheimia haemolytica, Mycoplasma bovis, Haemophilus parasuis, Escherichia coli, Pasteurella multocida, Ochrobactrum anthropi, Salmonella choleraesuis, Brucella melitensis, and Staphylococcus aureus, and showed repeatability with coefficients of variation (CV) lower than 10%. The method exhibits strong milk sample tolerance, the LOD of detecting in spike milk was 5 × 103 CFU/mL, which sensitivity is ten times higher than the triplex qPCR. 60 clinical DNA samples, including 20 milk, 20 tissue and 20 swab samples, were kept in China Animal Health and Epidemiology Center were tested by the triplex ddPCR and triplex qPCR. The triplex ddPCR presented a higher sensitivity (11.67%, 7/60) than that of the triplex qPCR method (8.33%, 5/60). The positive rates of M. tuberculosis, M. bovis, and BCG were 1.67, 10, and 0% by triplex ddPCR, and 1.67, 6.67, and 0% by triplex qPCR, with coincidence rates of 100, 96.7, and 100%, respectively.
UNASSIGNED: Our data demonstrate that the established triplex ddPCR method is a sensitive, specific and rapid method for differentiation and identification of M. tuberculosis, M. bovis, and BCG.

Brown root rot disease (BRRD) is a highly destructive tree disease. Early diagnosis of BRRD has been challenging because the first symptoms and signs are often observed after extensive tissue colonization. Existing molecular detection methods, all based on the internal transcribed spacer (ITS) region, were developed without testing against global Phellinus noxius isolates, other wood decay fungi, or host plant tissues. This study developed SYBR Green real-time quantitative PCR (qPCR) assays for P. noxius. The primer pair Pn_ITS_F/Pn_ITS_R targets the ITS, and the primer pair Pn_NLR_F/Pn_NLR_R targets a P. noxius-unique group of homologous genes identified through a comparative genomics analysis. The homologous genes belong to the nucleotide-binding-oligomerization-domain-like receptor (NLR) superfamily. The new primer pairs and a previous primer pair G1F/G1R were optimized for qPCR conditions and tested for specificity using 61 global P. noxius isolates, five other Phellinus species, and 22 non-Phellinus wood decay fungal species. While all three primer pairs could detect as little as 100 fg (about 2.99 copies) of P. noxius genomic DNA, G1F/G1R had the highest specificity and Pn_NLR_F/Pn_NLR_R had the highest efficiency. To avoid false positives, the cutoff Cq values were determined as 34 for G1F/G1R, 29 for Pn_ITS_F/Pn_ITS_R, and 32 for Pn_NLR_F/Pn_NLR_R. We further validated these qPCR assays using Ficus benjamina seedlings artificially inoculated with P. noxius, six tree species naturally infected by P. noxius, rhizosphere soil, and bulk soil. The newly developed qPCR assays provide sensitive detection and quantification of P. noxius, which is useful for long-term monitoring of BRRD status.

Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the origin site is important. Here, we developed an image-based deep-learning model that utilizes a vision transformer algorithm for predicting the origin of CUP. Using DNA methylation dataset of 8,233 primary tumors from The Cancer Genome Atlas (TCGA), we categorized 29 cancer types into 18 organ classes and extracted 2,312 differentially methylated CpG sites (DMCs) from non-squamous cancer group and 420 DMCs from squamous cell cancer group. Using these DMCs, we created organ-specific DNA methylation images and used them for model training and testing. Model performance was evaluated using 394 metastatic cancer samples from TCGA (TCGA-meta) and 995 samples (693 primary and 302 metastatic cancers) obtained from 20 independent external studies. We identified that the DNA methylation image reveals a distinct pattern based on the origin of cancer. Our model achieved an overall accuracy of 96.95 % in the TCGA-meta dataset. In the external validation datasets, our classifier achieved overall accuracies of 96.39 % and 94.37 % in primary and metastatic tumors, respectively. Especially, the overall accuracies for both primary and metastatic samples of non-squamous cell cancer were exceptionally high, with 96.79 % and 96.85 %, respectively.

Risk stratification and molecular targeting have been key to increasing cure rates for pediatric cancers in high-income countries. In contrast, precise diagnosis in low-resource settings is hindered by insufficient pathology infrastructure. The Global HOPE program aims to improve outcomes for pediatric cancer in Sub-Saharan Africa (SSA) by building local clinical care and diagnostic capacity. This study aimed to assess the feasibility of implementing molecular assays to improve leukemia diagnoses in SSA. Custom NanoString nCounter gene fusion assays, previously validated in the US, were used to test samples from suspected leukemia patients. The NanoString platform was chosen due to relatively low cost, minimal technical and bioinformatics expertise required, ability to test sub-optimal RNA, and rapid turnaround time. Fusion results were analyzed blindly, then compared to morphology and flow cytometry results. Of 117 leukemia samples, 74 were fusion-positive, 30 were negative, 7 were not interpretable, and 6 failed RNA quality. Nine additional samples were negative for leukemia by flow cytometry and negative for gene fusions. All 74 gene fusions aligned with the immunophenotype determined by flow cytometry. Fourteen samples had additional information available to further confirm the accuracy of the gene fusion results. The testing provided a more precise diagnosis in >60% of cases, and 9 cases were identified that could be treated with an available tyrosine kinase inhibitor, if detected at diagnosis. As risk-stratified and targeted therapies become more available in SSA, implementing this testing in real-time will enable the treatment of pediatric cancer to move toward incorporating risk stratification for optimized therapy.