Respiratory RNA viruses such as Infectious bronchitis virus (IBV) and Avian metapneumovirus (aMPV), which are characterized by generating both respiratory damage and adverse effects on reproductive organs, affect poultry production economically due to high mortality rate and decrease in egg production and quality. Particularly, aMPV has three genotypes that have been reported with greater frequency in chickens: aMPV-A, aMPV-B, and aMPV-C. The present study proposes the design of a multiplex RT-qPCR assay for the simultaneous diagnosis of the 3 genotypes of interest of aMPV and IBV, followed by testing of 200 tracheal samples of vaccinated chickens with respiratory symptoms and finally a phylogenetic analysis of the sequences found. The assay detected up to 1 copy of each viral genome. The standard curves showed an efficiency between 90 and 100% in the multiplex assay and inter- and intra-assay coefficients of variation of 0.363 and 0.459, respectively and inter- and intra-assay coefficients of variation of 0.363 and 0.459, respectively. 69.5% of samples were found positive alone or in coinfection. 114 samples were positive for IBV, 13 for aMPV-A and 25 for aMPV-B. RNA of aMPV-C was no detected. The most commonly found combination was aMPV-B and IBV within 6 samples, and the least common was aMPV-A and aMPV-B in coinfection in 2 samples. The assay was specific for amplification of the genomes of the studied respiratory viruses (IBV, aMPV-A, aMPV-B, aMPV-C) as no amplification was shown from other viral genomes (ChPV, CAstV, ANV, and FAdV) or from the negative controls. Partial genomic Sanger sequencing enabled to identify circulating vaccine-derived and wild-type strains of IBV and vaccine and vaccine-derived strains of aMPV-B. In conclusion, this newly developed multiplex RT-qPCR was shown to be able to detect individual infections as well as co-infections among the respiratory viruses investigated. It was demonstrated to be a reliable and efficient tool for rapidly and safely diagnosing these infections. Furthermore, this study represents the first report of aMPV strains in Ecuadorian poultry and demonstrates the circulation of aMPV-A, aMPV-B, and GI-13 IBV strains in unvaccinated chicken populations in the country. Thus, it highlights the importance of simultaneously identifying these pathogens in greater detail and on a regular basis in Ecuador.

Amidst the COVID-19 pandemic, the Polytechnic University of Setúbal (IPS) used its expertise in molecular genetics to establish a COVID-19 laboratory, addressing the demand for community-wide testing. Following standard protocols, the IPS COVID Lab received national accreditation in October 2020 and was registered in February 2021. With the emergence of new SARS-CoV-2 variants and safety concerns for students and staff, the lab was further challenged to develop rapid and sensitive diagnostic technologies. Methodologies such as sample-pooling extraction and multiplex protocols were developed to enhance testing efficiency without compromising accuracy. Through Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) analysis, the effectiveness of sample pooling was validated, proving to be a clear success in COVID-19 screening. Regarding multiplex analysis, the IPS COVID Lab developed an in-house protocol, achieving a sensitivity comparable to that of standard methods while reducing operational time and reagent consumption. This approach, requiring only two wells of a PCR plate (instead of three for samples), presents a more efficient alternative for future testing scenarios, increasing its throughput and testing capacity while upholding accuracy standards. The lessons learned during the SARS-CoV-2 pandemic provide added value for future pandemic situations.

Human adenoviruses (HAdVs) are common pathogens that are associated with a variety of diseases, including respiratory tract infections (RTIs). Without reliable, fast, and cost-effective detection methods for HAdVs, patients may be misdiagnosed and inappropriately treated. To address this problem, we have developed a multiplex loop-mediated isothermal amplification (LAMP) assay for the detection of the species Human adenovirus B (HAdV-B), Human adenovirus C (HAdV-C) and Human adenovirus E (HAdV-E) that cause RTIs. This multiplexing approach is based on the melting curve analysis of the amplicons with a specific melting temperature for each HAdV species. Without the need for typing of HAdVs, the LAMP results can be visually detected using colorimetric analysis. The assay reliably detects at least 375 copies of HAdV-B and -C and 750 copies of HAdV-E DNA per reaction in less than 35 min at 60 °C. The designed primers have no in silico cross-reactivity with other human respiratory pathogens. Validation on 331 nasal swab samples taken from patients with RTIs showed a 90-94% agreement rate with our in-house multiplex quantitative polymerase chain reaction (qPCR) method. Concordance between the quantitative and visual LAMP was 99%. The novel multiplexed LAMP could be an alternative to PCR for diagnostic purposes, saving personnel and equipment time, or could be used for point-of-care testing.

BACKGROUND: Accurate diagnosis of Alzheimer\'s disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 matching Control subjects in combination with demographic-clinical characteristics.
METHODS: 136 subjects (AD: n = 43, FTD: n = 33, Controls: n = 60) participated. Single-molecule array (SIMOA), glial fibrillary acidic protein (GFAP), neurofilament light (NfL), TAU, and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) in CSF were analyzed with a multiplex neuro 4plex kit. Receiver operating characteristic (ROC) curve analysis compared area under the curve (AUC), while the principal of the sparse partial least squares discriminant analysis (sPLS-DA) was used with the intent to strengthen the identification of confident disease clusters.
RESULTS: CSF exhibited increased levels of all SIMOA biomarkers in AD compared to Controls (AUCs: 0.71, 0.86, 0.92, and 0.94, respectively). Similar patterns were observed in FTD with NfL, TAU, and UCH-L1 (AUCs: 0.85, 0.72, and 0.91). sPLS-DA revealed two components explaining 19% and 9% of dataset variation.
CONCLUSIONS: CSF data provide high diagnostic accuracy among AD, FTD, and Control discrimination. Subgroups of demographic-clinical characteristics and biomarker concentration highlighted the potential of combining different kinds of data for successful and more efficient cohort clustering.

This study aimed to enhance our understanding of the agreement between two sampling methods for the detection of bovine respiratory disease (BRD) pathogens in calves using high-throughput real-time qPCR (ht-RT-qPCR). In total, 233 paired nasal swab (NS) and non-endoscopic bronchoalveolar lavage (nBAL) samples were collected from 152 calves from 12 Danish cattle herds. In 202 of the observations, the calves were examined using a standardized clinical protocol. Samples were tested for three viruses (bovine respiratory syncytial virus, bovine corona virus, and influenza D virus) and six bacteria (Histophilus somni, Mannheimia haemolytica, Mycoplasma bovis, Mycoplasma species, Pasteurella multocida, and Truepurella pyogenes). The results showed age-related differences in disease and pathogen occurrence, with the highest detection rates in calves aged 35 days or older. Poor to moderate agreement was found between the NS and nBAL results. The presence of Mannheimia haemolytica in both NS and nBAL in younger calves and in nBAL in older calves was associated with clinical BRD. There was a potential link between BRD and influenza D virus in older calves, although it was only found in one herd in a small sample size. Overall, NS was a relatively poor predictor of pathogens in the lower respiratory tract. The present study confirms the complexity of pathogen detection in BRD, with marked influences of age and the sampling method on pathogen detection and disease associations.

A Point-of-Care system for molecular diagnosis (PoC-MD) is described, combining GaN and CMOS chips. The device is a micro-system for fluorescence measurements, capable of analyzing both intensity and lifetime. It consists of a hybrid micro-structure based on a 32 × 32 matrix addressable GaN microLED array, with square LEDs of 50 µm edge length and 100 µm pitch, with an underneath wire bonded custom chip integrating their drivers and placed face-to-face to an array of 16 × 16 single-photon avalanche diodes (SPADs) CMOS. This approach replaces instrumentation based on lasers, bulky optical components, and discrete electronics with a full hybrid micro-system, enabling measurements on 32 × 32 spots. The reported system is suitable for long lifetime (>10 ns) fluorophores with a limit of detection ~1/4 µM. Proof-of-concept measurements of streptavidin conjugate Qdot™ 605 and Amino PEG Qdot™ 705 are demonstrated, along with the device ability to detect both fluorophores in the same measurement.

UNASSIGNED: Clinical significance of coagulase-negative staphylococci (CoNS) has been gradually acknowledged in both healthcare and clinical research, but approaches for their precise discrimination at the species level remain scarce. The current study aimed to evaluate the association of CoNS with orthopedic infections, where accurate and prompt identification of etiology is crucial for appropriate diagnosis and treatment decision-making.
UNASSIGNED: A 16S rRNA-based quantitative PCR (qPCR) assay was developed for the detection of Staphylococcus genus and two panels of 3-plex qPCR assays for further differentiation of six CoNS species with remarkable clinical significance, including S. epidermidis, S. haemolyticus, S. simulans, S. hominis, S. capitis, and S. caprae. All the assays exhibited excellent analytical performance. ΔCq (quantification cycle) between 16S rRNA and CoNS species-specific targets was established to determine the primary CoNS. These methods were applied to detect CoNS in wound samples from orthopedic patients with and without infection.
UNASSIGNED: Overall, CoNS were detected in 17.8% (21/118) of patients with clinically suspected infection and in 9.8% (12/123) of patients without any infection symptom (p < 0.05). Moreover, the association with infection was found to be bacterial quantity dependent. S. epidermidis was identified as the predominant species, followed by S. simulans, S. haemolyticus, and S. hominis. Male sex, open injury, trauma, and lower extremity were determined as risk factors for CoNS infections. CoNS-positive patients had significantly longer hospitalization duration (20 days (15, 33) versus 13 days (7, 22) for Staphylococcus-negative patients, p = 0.003), which could be a considerable burden for healthcare and individual patients. Considering the complex characteristics and devastating consequences of orthopedic infections, further expanding the detection scope for CoNS may be pursued to better understand the etiology of orthopedic infections and to improve therapeutic strategies.

Spatial relations between tumor cells and host-infiltrating cells are increasingly important in both basic science and clinical research. In this study, we have tested the feasibility of using standard methods of immunohistochemistry (IHC) in a multiplex staining system using a newly developed set of chromogenic substrates for the peroxidase and alkaline phosphatase enzymes. Using this approach, we have developed a set of chromogens characterized by (1) providing fine cellular detail, (2) non-overlapping spectral profiles, (3) an absence of interactions between chromogens, (4) stability when stored, and (5) compatibility with current standard immunohistochemistry practices. When viewed microscopically under brightfield illumination, the chromogens yielded the following colors: red, black, blue, yellow, brown, and green. By selecting compatible color combinations, we have shown feasibility for four-color multiplex staining. Depending on the particular type of analysis being performed, visual analysis, without the aid of computer-assisted image analysis, was sufficient to differentiate up to four different markers.

BACKGROUND: The concurrent circulation of SARS-CoV-2 with other respiratory viruses is unstoppable and represents a new diagnostic reality for clinicians and clinical microbiology laboratories. Multiplexed molecular testing on automated platforms that focus on the simultaneous detection of multiple respiratory viruses in a single tube is a useful approach for current and future diagnosis of respiratory infections in the clinical setting.
METHODS: Two time periods were included in the study: from February to April 2022, an early 2022 period, during the gradual lifting of COVID-19 prevention measures in the country, and from October 2022 to April 2023, the 2022/23 respiratory infections season. We analysed a total of 1,918 samples in the first period and 18,131 respiratory samples in the second period using a multiplex molecular assay for the simultaneous detection of Influenza A (Flu-A), Influenza B (Flu-B), Human Respiratory Syncytial Virus (HRSV) and SARS-CoV-2.
RESULTS: The results from early 2022 showed a strong dominance of SARS-CoV-2 infections with 1,267/1,918 (66.1%) cases. Flu-A was detected in 30/1,918 (1.6%) samples, HRSV in 14/1,918 (0.7%) samples, and Flu-B in 2/1,918 (0.1%) samples. Flu-A/SARS-CoV-2 co-detections were observed in 11/1,267 (0.9%) samples, and HRSV/SARS-CoV-2 co-detection in 5/1,267 (0.4%) samples. During the 2022/23 winter respiratory season, SARS-CoV-2 was detected in 1,738/18,131 (9.6%), Flu-A in 628/18,131 (3.5%), Flu-B in 106/18,131 (0.6%), and HRSV in 505/18,131 (2.8%) samples. Interestingly, co-detections were present to a similar extent as in early 2022.
CONCLUSIONS: The results show that the multiplex molecular approach is a valuable tool for the simultaneous laboratory diagnosis of SARS-CoV-2, Flu-A/B, and HRSV in hospitalized and outpatients. Infections with Flu-A/B, and HRSV occurred shortly after the COVID-19 control measures were lifted, so a strong reoccurrence of various respiratory infections and co-detections in the post COVID-19 period was to be expected.

Multiplex Immunohistochemistry (mIHC) is a cost-effective and accessible method for in situ labeling of multiple protein biomarkers in a tissue sample. By assigning a different stain to each biomarker, it allows the visualization of different types of cells within the tumor vicinity for downstream analysis. However, to detect different types of stains in a given mIHC image is a challenging problem, especially when the number of stains is high. Previous deep-learning-based methods mostly assume full supervision; yet the annotation can be costly. In this paper, we propose a novel unsupervised stain decomposition method to detect different stains simultaneously. Our method does not require any supervision, except for color samples of different stains. A main technical challenge is that the problem is underdetermined and can have multiple solutions. To conquer this issue, we propose a novel inversion regulation technique, which eliminates most undesirable solutions. On a 7-plexed IHC images dataset, the proposed method achieves high quality stain decomposition results without human annotation.