The original AssayBLAST was built around a simple but powerful idea: use the well-established BLAST search engine to compare candidate primers and probes against large sequence databases, and thereby predict how they will perform in a polymerase chain reaction or related amplification assay. This approach allows researchers to screen oligonucleotides computationally against thousands or even millions of potential template sequences, flagging those that might bind to off-target sites or fail to amplify the organisms they were designed to detect. For multi-parameter assays, which combine many primer and probe pairs in a single reaction to detect numerous targets simultaneously, such computational pre-screening is not merely convenient; it is essential for keeping development costs and failure rates under control.

The new version addresses one of the most subtle and consequential failure modes in multiplex assay design: the spatial relationship between paired oligonucleotides. In a functioning amplification reaction, a forward and reverse primer must bind to opposite strands of the template DNA in the correct orientation and within a suitable distance of each other for the polymerase to generate a product. A primer pair that individually looks perfect can be rendered useless if the two primers bind to the same strand, or if their binding sites are too far apart or oriented incorrectly. AssayBLAST v2 introduces an integrated strand and proximity check that validates corresponding oligonucleotides against these geometric requirements, ensuring that predicted amplification events reflect biologically plausible configurations rather than coincidental sequence matches.

This check matters because earlier approaches could, in principle, report a match between a primer and a genomic sequence without verifying whether that match could actually support amplification. In a multiplex assay targeting dozens of pathogens or resistance genes at once, such false positives in the computational analysis can mislead researchers about the expected specificity and coverage of their design. By explicitly evaluating orientation and spacing, the updated software produces a more faithful picture of what the reaction will actually do. The developers describe this as enabling precise validation of corresponding oligonucleotides, and the improvement is backed by a comparative evaluation against the previous version of AssayBLAST, giving users a quantified sense of how much the analysis has matured.

Beyond geometry, the second major addition concerns the outcome of the reaction itself. AssayBLAST v2 does not stop at identifying where oligonucleotides bind; it uses the predicted interactions among all oligonucleotides in the assay to determine the theoretical amplification outcomes. In other words, the software constructs a computational benchmark of which template molecules should be amplified, which should be missed, and how the various primer and probe pairs in a multiplex panel are expected to behave together. This predicted outcome profile then serves as a reference point for downstream wet-laboratory validation, allowing experimentalists to compare observed assay performance against theoretical expectations and to correlate discrepancies with specific oligonucleotide interactions.

The practical implications of this benchmarking capability extend well beyond academic curiosity. Synthesizing primers and probes is a recurring expense in diagnostic development, and a poorly designed multiplex assay can burn through budgets in repeated rounds of synthesis, testing, and redesign. By catching suboptimal oligonucleotide combinations before synthesis, the software streamlines the assay development workflow and reduces the costs associated with suboptimal primer and probe synthesis. For laboratories developing diagnostic panels, particularly in fields such as infectious disease detection where panels must distinguish closely related organisms against a backdrop of host and environmental DNA, the difference between a well-screened and a poorly screened design can determine whether a product reaches the clinic at all.

The third pillar of the update is an adaptive optimization of BLAST parameters that responds dynamically to the size of the database being searched. BLAST searches are governed by numerous tunable parameters, including word size, scoring matrices, and statistical significance thresholds, and the settings that work well for a small custom database of target genomes may be poorly suited to a comprehensive repository containing billions of nucleotides. Fixed parameters force developers into a compromise: settings sensitive enough to detect weak but relevant off-target binding in large databases can become computationally expensive, while settings optimized for speed can miss biologically important interactions. The adaptive approach in AssayBLAST v2 scales its parameters with database size, improving both analytical sensitivity and computational performance simultaneously rather than trading one against the other.

This adaptive strategy reflects a broader trend in bioinformatics, where tools must increasingly operate across databases that grow at staggering rates. Sequence repositories double in size on timescales measured in years, and a screening tool with static assumptions about database scale risks becoming either obsolete or prohibitively slow. By building the scaling behavior directly into the search strategy, the AssayBLAST developers have future-proofed their tool to a degree, ensuring that the reliability of an in silico evaluation does not silently degrade as reference data expand. For users running routine re-evaluations of existing assay panels against updated databases, this consistency is a meaningful quality assurance benefit in its own right.

The team behind the software spans several Jena institutions, combining expertise in RNA bioinformatics, high-throughput analysis, and applied diagnostics. Tom Eulenfeld and Maximillian Collatz, who share first authorship, are based at Friedrich Schiller University Jena, with Collatz also affiliated with the university’s Bioinformatics Core Facility. Sascha D. Braun and Ralf Ehricht bring the diagnostic perspective from the Leibniz Institute of Photonic Technology, the InfectoGnostics Research Campus Jena, and associated translational research centers, including Jena University Hospital. This blend of computational and applied expertise is visible in the design of the update itself: the new features target precisely the points where computational predictions meet laboratory reality, from primer geometry to predicted amplification outcomes. The research was funded in part by the German Research Foundation under Germany’s Excellence Strategy, and the article is published open access under a Creative Commons Attribution license.

For the diagnostic and research communities that depend on molecular multi-parameter assays, the release of AssayBLAST v2 arrives at a moment when the stakes of in silico evaluation have never been higher. Multiplex panels now underpin syndromic testing for respiratory infections, sepsis diagnostics, food safety screening, and antimicrobial resistance surveillance, and each new panel multiplies the number of oligonucleotide interactions that must be anticipated and validated. A tool that can reliably predict amplification outcomes, verify the physical plausibility of primer binding, and adapt its search sensitivity to ever-growing databases addresses the central bottleneck in this workflow. The developers position the update as increasing the robustness and reliability of molecular diagnostics and research applications alike, and the comparative evaluation included in the publication offers users a transparent account of the gains. As computational screening continues to move from a supplementary check to a foundational step in assay design, tools of this kind are set to shape how quickly and how confidently new diagnostic panels reach the laboratory and, ultimately, the patient.

Subject of Research: In silico evaluation and design of molecular multi-parameter PCR assays using BLAST-based oligonucleotide analysis

Article Title: AssayBLAST v2: major update improving reliability and reporting of the in silico analysis of molecular multi-parameter assays

Article References: Eulenfeld, T., Collatz, M., Braun, S. D., & Ehricht, R. (2026). AssayBLAST v2: major update improving reliability and reporting of the in silico analysis of molecular multi-parameter assays. BMC Bioinformatics, 27(1), Article 205. https://doi.org/10.1186/s12859-026-06595-w

Image Credits: AI Generated

DOI: 10.1186/s12859-026-06595-w

Keywords: AssayBLAST, oligonucleotide design, molecular diagnostics, multiplex PCR, BLAST, in silico analysis, primer design, bioinformatics software, amplification prediction, diagnostic assay development, BMC Bioinformatics, computational biology

The study, published in BMC Infectious Diseases, was led by Yalin Sun and colleagues in the hospital’s Department of Pediatric Infectious Diseases. The team examined children aged eighteen years or younger who were hospitalized with acute respiratory tract infections between 5 January 2023 and 17 June 2025. Each child underwent a thirteen-target pharyngeal-swab assay covering the common respiratory pathogens, from respiratory syncytial virus and influenza to human adenovirus and Mycoplasma pneumoniae. The researchers collapsed these detections into eleven analytical groups and then asked a deceptively simple question: did the identity of the detected pathogen predict the child’s inflammatory biomarker levels or the length of their hospital stay?

The scale of the dataset lends the findings considerable weight. Of 6,093 hospitalized children included in the analysis, 2,076 tested negative on the respiratory panel, 3,343 had a single pathogen detected, and 674 carried detections of multiple targets simultaneously. Rather than treating every pathogen individually, the investigators defined three primary outcomes that map onto everyday clinical decisions: a high-sensitivity C-reactive protein value of at least 20 milligrams per liter, a procalcitonin value of at least 0.5 nanograms per milliliter, and a hospital stay lasting seven days or longer. These thresholds are commonly used at the bedside as rough markers of a bacterial process or a complicated course.

The statistical approach was deliberately conservative. Complete-case logistic regression models adjusted for age group, sex, testing year, and season, and the authors applied false discovery rate corrections to guard against spurious associations arising from the many comparisons inherent in a multi-pathogen panel. Sensitivity analyses probed the robustness of the results from several angles: biomarkers were also modeled as continuous variables, multiple-target detections were examined separately, recorded SARS-CoV-2 positivity was accounted for, and the analysis was restricted to children sampled within 24 or 48 hours of admission using both source records and chart-reviewed timing intervals.

Two pathogens stood out with sharply contrasting signatures. Human adenovirus detection was associated with roughly double the odds of an elevated inflammatory response compared with children whose panels came back negative. The adjusted odds ratio was 2.19 for a high-sensitivity C-reactive protein value of at least 20 milligrams per liter, with a 95 percent confidence interval of 1.63 to 2.96, and 1.93 for a procalcitonin value of at least 0.5 nanograms per milliliter, with a confidence interval of 1.34 to 2.77. In practical terms, a child whose swab revealed adenovirus was markedly more likely to show the kind of inflammatory surge that clinicians often associate with bacterial infection, even though adenovirus is a virus.

Mycoplasma pneumoniae told the opposite story in one respect and a striking one in another. Detection of this atypical bacterium was linked to lower odds of a procalcitonin value reaching 0.5 nanograms per milliliter, with an adjusted odds ratio of just 0.22 and a confidence interval of 0.13 to 0.37. Yet the same pathogen was the strongest predictor of a prolonged hospitalization in the entire study: children with Mycoplasma pneumoniae detections had 2.57 times the odds of staying seven days or longer, with a confidence interval of 1.99 to 3.31. The association with long stays persisted when the analysis was restricted to children sampled early, yielding adjusted odds ratios of 2.50 in the 24-hour subset and 2.76 in the 48-hour subset, suggesting that the finding was not an artifact of delayed testing after several days of illness.

Multiple detections carried their own signal. Children in whom two or more targets were identified had 2.21 times the odds of a hospital stay of at least seven days compared with panel-negative children, with a confidence interval of 1.73 to 2.82. Co-detection is increasingly recognized as common rather than exceptional in pediatric respiratory medicine, and this result adds to the evidence that a positive panel with more than one organism is not simply noise. Whether co-detected pathogens interact biologically, or whether multiple detections mark a different underlying illness severity, remains an open question that this observational design cannot resolve.

The authors are careful, and rightly so, about what these numbers do and do not mean. A retrospective cohort of routine clinical data cannot establish that a pathogen causes a longer stay or a higher biomarker value. Unmeasured bacterial infection, variation in treatment, differences in illness severity at presentation, and the clinical selection of which children get tested all could shape the observed associations. The study also relied on routinely recorded biomarkers rather than protocol-mandated sampling, and chest radiograph findings were classified from reports in a way the authors flag as unvalidated. These limitations are acknowledged explicitly in the paper, and the sensitivity analyses, while reassuring, do not convert association into causation.

Even with those caveats, the clinical implications are worth pondering. The adenovirus finding serves as a caution against over-relying on C-reactive protein and procalcitonin as bacterial discriminators: a vigorous inflammatory response in a child with a positive adenovirus swab may reflect the virus itself rather than a bacterial co-infection demanding antibiotics. Conversely, the Mycoplasma pneumoniae result suggests that a low procalcitonin does not guarantee a short or uncomplicated course. Mycoplasma infections in children are notorious for protracted coughing illness and, in some regions, rising macrolide resistance, and a biomarker pattern that looks reassuringly quiet may coexist with a hospitalization that stretches well past a week.

For researchers, the study illustrates the value of linking routine diagnostic panels to outcomes data at scale, and of stress-testing associations with early-sampling restrictions and timing reconciliation before publication. The supplementary materials document an unusually thorough audit trail, including chart-reviewed corrections of PCR timing records and analyses omitting individually corrected entries. For clinicians, the takeaway is more modest but useful: pathogen identity, inflammatory biomarkers, and hospital course each carry independent information, and none substitutes for the others. As multiplex panels become faster and cheaper, studies like this one help map which detections actually matter for the questions that keep a child in the hospital, and which are simply molecular footnotes to an illness that will resolve on its own schedule.

Subject of Research: Associations between multiplex respiratory pathogen detections, inflammatory biomarkers, and length of stay in children hospitalized with acute respiratory tract infections

Article Title: Respiratory panel detections, inflammatory biomarkers, and length of stay in children hospitalized with acute respiratory tract infections: a retrospective cohort study

Article References: Sun, Y., Li, S., Wang, Y., Zhang, S., Teng, S., & Qi, Z. (2026). Respiratory panel detections, inflammatory biomarkers, and length of stay in children hospitalized with acute respiratory tract infections: a retrospective cohort study. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14559-x

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14559-x

Keywords: acute respiratory tract infection, children, multiplex PCR, human adenovirus, Mycoplasma pneumoniae, procalcitonin, C-reactive protein, length of stay, biomarkers, pediatrics, retrospective cohort, hospitalization

The work, led by Sunita Munda with contributions from Rahul Chandrakant Kaldate, Priyabrata Sen, Sanjay Kumar Chetia and Jyoti Lekha Borah, targets the bacterial blight resistance genes xa5, xa13 and Xa21, the blast resistance gene Pi2, and the drought tolerance quantitative trait locus qDTY2.1. These loci represent some of the most valuable tools in rice breeding. Xa21, first genetically characterized in the early 1990s, confers broad-spectrum resistance to Xanthomonas oryzae pv. oryzae, the bacterium behind bacterial leaf blight, while xa5 and xa13 contribute complementary, recessive and semi-recessive layers of defense. Pi2 belongs to a well-mapped resistance gene family that recognizes the rice blast fungus Magnaporthe oryzae, and qDTY2.1 is one of a set of quantitative trait loci shown in earlier multi-institutional work to maintain yield under reproductive-stage drought.

Gene pyramiding, the practice of combining multiple resistance or tolerance genes in one line, is the standard strategy for building durable, climate-resilient cultivars. The bottleneck is not identifying the genes but tracking them through breeding populations. In conventional marker-assisted selection, each locus is assayed separately by polymerase chain reaction, meaning a single plant carrying six target loci would need six independent reactions, six sets of reagents and six lanes of gel electrophoresis. When thousands of seedlings from a backcross or recombinant population must be genotyped, the costs of enzymes, primers, plastics and technician hours multiply rapidly, and the pace of a breeding cycle is dictated by the slowest screening step.

Multiplex PCR addresses this by amplifying several targets in a single tube, but the technique is notoriously finicky. Primers designed for separate assays can bind each other, compete for the same nucleotides, or produce bands of overlapping sizes that cannot be distinguished on a gel. Annealing temperatures that suit one primer pair may be wrong for another. The Indian team therefore began with six candidate markers, including a functional marker for the blast resistance gene Pi54 alongside those for the five target loci, and evaluated whether they could coexist in one reaction. Parental polymorphism screening, the first gatekeeping step in any marker-assisted program, revealed that the Pi54 marker showed no variation between the two parental lines, making it useless for selection in this particular cross and it was excluded from the final assay.

What emerged from the optimization were two workable multiplex combinations: one detecting xa5, xa13, Xa21 and Pi2 simultaneously, and another detecting Xa21, qDTY2.1 and Pi2 together. The researchers validated the system on the parental lines and on real breeding populations, including a BC1F4 population derived from the cross MSM × DRR Dhan 44 and an F7 population from the cross MSM × No. 29. Across these materials, the multiplex assay produced distinct, reproducible bands for all five loci, with segregation patterns among the progeny that were clear enough to classify individual plants by the alleles they carried. Band intensity and specificity remained high despite the crowded reaction environment, indicating that primer concentrations and cycling conditions had been successfully balanced.

Critical to the credibility of the new assay is its agreement with the gold standard. The genotypic profiles generated by the multiplex PCR matched the results of conventional single-locus, or monoplex, PCR for the selected breeding lines, confirming that compressing the reactions had not introduced genotyping errors. In molecular breeding, where a single misclassification can propagate a wrong allele through generations of crossing, this kind of concordance is the difference between a laboratory curiosity and a tool a breeding program can actually deploy. The authors report that the optimized system exhibited high amplification efficiency and supported the effectiveness of marker-assisted selection for accelerating the development of pyramided lines.

The economics are equally significant. By consolidating what would have been five separate reactions into fewer tubes, the multiplex system reduced reagent consumption and labor by 60 to 75 percent. For publicly funded breeding institutes in rice-growing countries of South and Southeast Asia, where budgets per marker data point are often the binding constraint, savings of this magnitude translate directly into more plants screened per season and faster delivery of improved varieties to farmers. The study builds on earlier demonstrations, including a single-tube functional marker assay for the three bacterial blight genes published in Rice Science in 2016 and a 2024 cost-effective multiplex assay covering bacterial leaf blight, blast and brown planthopper resistance, extending the concept to a combined biotic and abiotic stress panel.

The inclusion of a drought tolerance QTL alongside disease resistance genes is what makes the system genuinely climate-oriented. Drought is quantitatively inherited and environmentally sensitive, which is why major-effect QTL such as qDTY2.1, previously introgressed into varieties like Pusa 44 to produce drought-tolerant near-isogenic lines, are prized by breeders working on rainfed lowlands. Combining such loci with resistance to bacterial blight and blast in a single genotyping pipeline means a breeder can select seedlings that carry all the desired traits before they ever reach the field, collapsing what would otherwise be sequential screening rounds into one laboratory pass. The work was supported by the Department of Biotechnology, Government of India, under the DBT-NECAB Phase-III program, with field facilities provided by the AAU-Assam Rice Research Institute in Titabar.

Technically, the study illustrates the practical logic of marker system design. Sequence-tagged site markers and simple sequence repeat markers were chosen for their ability to discriminate between the parents, and the final panel was tuned so that amplicon sizes could be resolved on standard agarose gels, avoiding the need for expensive capillary instrumentation. The exclusion of the monomorphic Pi54 marker is a useful cautionary tale: a marker that performs brilliantly in one genetic background can be blind in another, and parental polymorphism screening remains an indispensable first step before any multiplex panel is locked in. The authors note that no datasets beyond those described in the study were generated or analysed, and they declare no competing interests.

For a world in which rice blast and bacterial blight continue to cause yield losses measured in millions of tonnes annually, and in which drought increasingly shapes planting decisions across Asia and Africa, tools that compress the breeding cycle carry outsized importance. This multiplex marker system does not discover new genes; its contribution is infrastructural, turning a laborious six-assay workflow into a fast, economical routine that a modestly equipped laboratory can run at scale. As gene pyramiding becomes the default strategy for climate-resilient rice, assays of this kind may well become the quiet workhorses of the breeding station, screening thousands of seedlings a season and quietly assembling the genetic armor that tomorrow’s varieties will carry into the field.

Subject of Research: Development of a multiplex PCR marker system for pyramiding disease resistance and drought tolerance loci in rice breeding

Article Title: A Multiplex Marker System for Simultaneous Pyramiding of Bacterial Blight Resistance, Blast Resistance and Drought Tolerance Loci in Rice Breeding Populations

Article References: Munda, S., Kaldate, R. C., Sen, P., Chetia, S. K., & Borah, J. L. (2026). A Multiplex Marker System for Simultaneous Pyramiding of Bacterial Blight Resistance, Blast Resistance and Drought Tolerance Loci in Rice Breeding Populations. Indian Journal of Genetics and Plant Breeding. https://doi.org/10.1007/s44489-026-00050-z

Image Credits: AI Generated

DOI: 10.1007/s44489-026-00050-z

Keywords: rice breeding, multiplex PCR, marker-assisted selection, bacterial blight, blast resistance, drought tolerance, gene pyramiding, xa5, Xa21, Pi2, qDTY2.1, quantitative trait loci

The study relied on a single multiplex fluorescence polymerase chain reaction panel coupled with capillary electrophoresis, applied uniformly to every patient in the cohort. This platform detects 13 targets simultaneously: 11 respiratory viruses and two atypical bacteria, Mycoplasma pneumoniae and Chlamydia. Standardizing the diagnostic method across all five years is a technical strength, because it removes a common source of bias in longitudinal surveillance studies, where changes in assay sensitivity can be mistaken for genuine shifts in pathogen epidemiology. Of the 9,674 patients, 5,289, or 54.67 percent, had lower respiratory tract infections, while 4,385, or 45.33 percent, had upper respiratory tract infections, reflecting the case mix of a hospital-based population rather than a community sample.

The contrast in detection rates between the two anatomical compartments was striking. Pathogens were identified in 2,939 of 5,289 lower respiratory tract infection cases, a positivity rate of 55.57 percent, compared with only 677 of 4,385 upper respiratory tract infection cases, or 15.44 percent. That difference of 40.13 percentage points, with a 95 percent confidence interval of 38.40 to 41.80 and a P value below 0.001, indicates that lower tract disease in this cohort was far more likely to have an identifiable infectious cause. The authors suggest this may partly reflect the deeper sampling and higher pathogen loads associated with lower tract disease, as well as the inclusion of atypical bacteria that preferentially involve the lung parenchyma and bronchial tree.

Within the lower respiratory tract infections, Mycoplasma pneumoniae was the leading pathogen, detected in 954 of 5,289 cases, or 18.04 percent. Rhinovirus followed at 618 cases, or 11.68 percent, and influenza A virus ranked third at 456 cases, or 8.62 percent. In the upper respiratory tract, by contrast, rhinovirus predominated, found in 224 of 4,385 cases, or 5.11 percent. The prominence of Mycoplasma pneumoniae is notable because this cell-wall-less bacterium, which lacks the outer membrane targeted by beta-lactam antibiotics, requires macrolides or other alternative agents and has been associated with periodic epidemics worldwide, including a pronounced wave in East Asia following the end of COVID-19 restrictions. Its rise to the top of the pathogen ranking in this Chinese cohort mirrors reports from several neighboring countries during the same period.

The temporal analysis forms the core of the study’s contribution. During 2021 and 2022, when stringent containment measures and mass vaccination were maintained across China, both the volume of acute respiratory infection consultations and the proportion of tests returning positive remained low. Positivity stood at 326 of 1,180 tests, or 27.63 percent, in 2021 and fell to 283 of 1,161 tests, or 24.38 percent, in 2022. After the relaxation of non-pharmaceutical interventions, the picture changed abruptly. In 2023, 1,486 of 4,292 tests were positive, a rate of 34.62 percent, and by 2024 the positivity rate had climbed to 1,046 of 1,913 tests, or 54.68 percent. In 2025 the rate remained elevated at 475 of 1,128 tests, or 42.11 percent.

Because the number of patients tested varied substantially from year to year, the researchers adjusted for age group in a logistic regression model to determine whether the apparent resurgence was confounded by shifts in the demographic composition of the tested population. It was not. Compared with 2021, the odds of pathogen detection were significantly higher in 2023, with an odds ratio of 2.85 and a 95 percent confidence interval of 2.09 to 3.88; in 2024, with an odds ratio of 4.19 and a confidence interval of 3.01 to 5.84; and in 2025, with an odds ratio of 2.19 and a confidence interval of 1.53 to 3.15. The persistence of this signal after adjustment strengthens the interpretation that the rebound reflects genuine changes in pathogen circulation rather than changes in who was being tested.

This pattern is consistent with the concept of immunity debt, a hypothesis proposed early in the pandemic suggesting that prolonged reduction in exposure to common respiratory pathogens, combined with the aging of the cohort of infants and children who never encountered them, could produce a delayed and intensified wave of infections once transmission resumed. The study cannot directly measure population immunity, and the authors are careful to frame their findings as descriptive surveillance rather than proof of any single mechanism. Nevertheless, the sharp rise in positivity after December 2022, and the dominance of Mycoplasma pneumoniae, a pathogen known for cyclical epidemics at multi-year intervals, fit the broader pattern documented across the region after restrictions ended.

Perhaps the most clinically consequential findings concern the sickest patients. Among 79 patients who required intensive care for severe lower respiratory tract infection, at least one pathogen was detected in every single case, and bacterial or fungal co-infection was documented in 72 of them, or 91.14 percent. Even more alarming, multidrug-resistant organisms were identified in 42 of these ICU patients, or 53.16 percent. Severe disease in this cohort was characterized by advanced age and a heavy burden of secondary infection, underscoring a well-recognized but persistently difficult problem in respiratory critical care: viral injury to the respiratory epithelium creates conditions in which resistant hospital-associated and community-acquired bacteria and fungi can flourish, complicating treatment and worsening outcomes.

The high rate of co-infection in severe cases also carries implications for diagnostic and antimicrobial stewardship. Because mixed infections were more frequent in lower respiratory tract infections than in upper tract disease, the authors argue that multiplex molecular panels, which can identify several pathogens from a single specimen in a few hours, are particularly valuable in hospitalized patients, where distinguishing viral pneumonia from bacterial superinfection directly affects antibiotic decisions. The detection of multidrug-resistant organisms in more than half of the intensive care cohort adds urgency, since empiric broad-spectrum therapy in such patients must be balanced against the risk of further selecting for resistance.

The study’s limitations are those inherent to its retrospective, single-region design. The cohort comes from a hospital in Shijiazhuang, Hebei Province, and the 13-target panel does not cover all respiratory pathogens, notably excluding common bacteria such as Streptococcus pneumoniae and Haemophilus influenzae, so the true burden of bacterial co-infection in the wider population may differ. Hospital-based sampling also means the results describe patients ill enough to seek care rather than community transmission as a whole. Still, the five-year span, the uniform diagnostic method, and the age-adjusted analysis together offer a rigorous record of how one region’s respiratory pathogen landscape responded to the end of pandemic controls. The authors conclude that the suppression and resurgence they documented, together with the heavy burden of resistant co-infection in severe disease, argue for continued vigilance, sustained molecular surveillance, and optimized management of lower respiratory tract infections in the post-pandemic era.

Subject of Research: Respiratory pathogen epidemiology and co-infection patterns in acute respiratory infections during and after the COVID-19 pandemic

Article Title: Respiratory pathogen spectrum and co-infection patterns in patients with acute respiratory infection during and after the coronavirus COVID-19 pandemic: a five-year retrospective study, 2021–2025

Article References: Zhao, M.-W., Yang, J., Li, Y.-H., Qiu, P., Zhang, Y., Zhang, X.-W., Gao, S., Wang, J., & Zhao, P. (2026). Respiratory pathogen spectrum and co-infection patterns in patients with acute respiratory infection during and after the coronavirus COVID-19 pandemic: a five-year retrospective study, 2021–2025. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14526-6

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14526-6

Keywords: acute respiratory infection, Mycoplasma pneumoniae, rhinovirus, influenza A, co-infection, COVID-19, non-pharmaceutical interventions, lower respiratory tract infection, multidrug-resistant organisms, multiplex PCR, immunity debt, intensive care

The study, published in BMC Infectious Diseases, drew on throat swab samples collected from 34,404 pediatric patients aged 18 years or younger who presented with respiratory symptoms at the Affiliated Women and Children’s Hospital of Ningbo University. Rather than relying on a single targeted test, the laboratory team used multiplex polymerase chain reaction, a technique that amplifies and identifies the genetic material of several pathogens simultaneously, to screen every sample for 13 common viral and atypical bacterial respiratory pathogens. Demographic details, pathogen identities and the dates on which samples were collected were then retrieved from the hospital’s laboratory database and analyzed together to reveal who was infected, with what, and when.

The headline number from the surveillance effort is an overall pathogen positivity rate of 69.14 percent, meaning that roughly seven in ten children tested carried detectable genetic evidence of at least one of the pathogens on the panel. That figure underscores how densely pathogenic material circulates among symptomatic children and illustrates the value of broad molecular panels: many of these infections would be difficult to distinguish clinically, since fever, cough and wheezing can be produced by any of a dozen different agents. Multiplex detection allows epidemiologists to see the true composition of that microbial mix rather than inferring it from symptoms alone.

Within that mix, three pathogens stood out. Mycoplasma pneumoniae, an atypical bacterium that lacks a cell wall and attaches itself to the lining of the respiratory tract, was detected in 26.94 percent of the tested children, making it the leading cause of positive findings. Human rhinovirus, the virus best known as the chief culprit behind the common cold, came second at 16.29 percent. Human adenovirus, a DNA virus capable of causing everything from pharyngitis to pneumonia, ranked third at 9.00 percent. The prominence of Mycoplasma pneumoniae is particularly notable because, as an atypical bacterium, it does not respond to the beta-lactam antibiotics often prescribed empirically for respiratory complaints, so knowing that it dominates locally can shape more rational treatment decisions.

The analysis went beyond simple prevalence counts to ask whether pathogen positivity differed across patient groups. The researchers report significant differences in positivity rates between the sexes and across age groups, indicating that the burden of specific respiratory pathogens is not distributed evenly among children. Such demographic patterns matter for clinical practice: if certain age brackets carry a disproportionately high share of detections, pediatricians can calibrate their index of suspicion, and laboratories can anticipate demand for testing among particular populations. Age-structured susceptibility is also a key input for modeling how respiratory pathogens spread through households and schools, where mixing patterns differ sharply from those of adult populations.

Seasonality, a signature feature of respiratory disease that was famously disrupted during the height of the COVID-19 pandemic, re-emerges clearly in the Ningbo data. The study documents evident seasonal variation for certain pathogens, with detection rates rising and falling across the two calendar years of surveillance. Tracking these rhythms is more than an academic exercise. Hospitals can use seasonal profiles to anticipate surges in admissions, stock appropriate diagnostics and therapeutics, and time public health messaging. The post-COVID period offers a natural experiment in how respiratory pathogen ecology rebounds when masking, distancing and reduced mixing recede, and datasets like this one provide the ground truth against which such rebound theories can be tested.

Coinfection emerged as a substantial feature of the pediatric disease landscape. Among the samples that tested positive for at least one pathogen, 19.85 percent harbored more than one, with dual infections representing the most common configuration. Coinfections complicate both biology and bedside care. On the biological side, one pathogen can damage the airway epithelium in ways that facilitate the entry or proliferation of another, potentially deepening disease severity. On the clinical side, a positive result for a common, often mild virus such as rhinovirus does not rule out a concurrent bacterial infection requiring antibiotics. Multiplex panels make such mixed infections visible, which single-pathogen testing would leave hidden.

The authors, a team spanning the hospital’s clinical laboratory, pediatrics department and a municipal key laboratory, frame the findings as an epidemiological reference for managing pediatric respiratory infections in the post-COVID-19 era. Their conclusions highlight the significant roles of Mycoplasma pneumoniae, human rhinovirus and human adenovirus in children in Ningbo and underscore the need for continued surveillance. Sustained monitoring is precisely what allows health systems to detect shifts in pathogen dominance, spot unusual out-of-season activity and respond to outbreaks before they overwhelm pediatric wards. Given that respiratory pathogens can change their circulation patterns within a single season, longitudinal datasets of this scale are among the most valuable tools available to public health authorities.

Methodologically, the study’s strengths lie in its sample size and its systematic approach. More than 34,000 specimens tested over 24 consecutive months with a standardized 13-pathogen molecular panel provide a resolution that smaller, shorter studies cannot match. The retrospective design has inherent limits, of course: it captures children who presented to one hospital with respiratory symptoms, so the findings describe a clinical population rather than the community at large, and throat swabs may vary in sensitivity across pathogens and disease stages. The researchers note that the work used non-identifiable data extracted under an ethics approval and informed consent waiver from the hospital’s institutional review board, in line with the Declaration of Helsinki.

For the wider scientific and clinical community, the Ningbo study adds a detailed post-pandemic datapoint to a growing international effort to understand how respiratory pathogen epidemiology reorganized after COVID-19. Questions remain open about whether Mycoplasma pneumoniae’s leading position reflects a genuine rebound of that bacterium after years of suppressed transmission, a shift in immunity profiles among children who grew up during the pandemic, or local factors specific to eastern China. Continued multi-season, multi-site surveillance, ideally with consistent molecular panels, will be needed to separate these explanations. In the meantime, the study offers pediatricians a clear message: in the post-COVID era, the causes of childhood respiratory infection are numerous, frequently mixed, and follow seasonal scripts that are once again worth learning by heart.

Subject of Research: Prevalence of viral and atypical bacterial respiratory pathogens in pediatric acute respiratory infections in post-COVID-19 Ningbo, China

Article Title: Prevalence of viral and atypical bacterial respiratory pathogens among pediatric patients with acute respiratory infections after COVID-19 in Ningbo, China

Article References: Zhou, C., Lu, W., Chen, Y., Hu, Q., Zhu, L., & Liu, W. (2026). Prevalence of viral and atypical bacterial respiratory pathogens among pediatric patients with acute respiratory infections after COVID-19 in Ningbo, China. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14531-9

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14531-9

Keywords: Mycoplasma pneumoniae, human rhinovirus, human adenovirus, pediatric respiratory infections, multiplex PCR, coinfections, seasonal trends, COVID-19 pandemic, Ningbo China, epidemiology, BMC Infectious Diseases, surveillance

Carbapenem-resistant Enterobacterales, commonly abbreviated CRE, represent one of the most urgent threats in modern medicine. These Gram-negative bacteria, which include Escherichia coli and Klebsiella pneumoniae among others, have acquired the ability to withstand carbapenems, a class of antibiotics often reserved as a last line of defense against serious infections. The consequences are stark: mortality rates from CRE infections can climb as high as fifty percent, leaving clinicians with vanishingly few therapeutic options. The problem is also accelerating globally, with resistance prevalence rising from just one percent in 2013 to forty-three percent in 2020 in parts of North America, a trajectory that underscores how quickly these organisms can adapt and spread.

The engine driving this resistance is the production of carbapenemase enzymes, a diverse family of beta-lactamases grouped into distinct classes by the Ambler classification system. Class A enzymes such as KPC, Class B metallo-beta-lactamases including NDM, IMP and VIM, and Class D oxacillinases such as OXA-48 each hydrolyze carbapenems through different chemical mechanisms. Because phenotypic tests alone cannot reliably distinguish between these classes, molecular techniques such as multiplex polymerase chain reaction are essential for pinpointing which resistance genes are actually present. In the Indian context, where blaNDM-1 has become widespread, identifying these determinants is critical for predicting transmissibility, constructing empirical antibiograms and strengthening hospital infection control.

Recognizing that systematic molecular data from eastern India were virtually absent, the AIIMS Patna team designed a cross-sectional study conducted between July 2021 and July 2023 in the hospital’s Microbiology laboratory. The research, approved by the Institutional Ethics Committee under approval number AIIMS/Pat/IEC/2021/578 and performed in accordance with the Declaration of Helsinki, analyzed residual clinical isolates collected during routine diagnostic work, with a formal waiver of individual patient consent and no patient-identifiable data collected. To avoid duplication bias, the investigators included only the first isolate per patient per episode of infection, ensuring that repeated cultures from the same admission did not inflate the results.

The scope of the underlying resistance problem was formidable. During the study period, a total of 3,421 Enterobacterales were isolated, drawn overwhelmingly from urine specimens, followed by pus, blood and respiratory samples. Of these, 1,128 isolates, or 32.97 percent, were phenotypically confirmed as carbapenem resistant, a figure drawn from the team’s previously published phenotypic work at the same center. Resistance was markedly higher among inpatients, at 47.74 percent, compared with only 14.48 percent among outpatients. All 213 CRE isolates characterized in detail showed complete resistance to third-generation cephalosporins, near-universal resistance of 99.4 percent to beta-lactam and beta-lactamase inhibitor combinations such as piperacillin-tazobactam, and one hundred percent resistance to aztreonam, a sobering profile that leaves almost no conventional beta-lactam therapy intact.

To confirm which isolates were producing carbapenemase enzymes, the researchers deployed a battery of phenotypic assays, including the Modified Carbapenem Inactivation Method, or mCIM, its EDTA-supplemented variant eCIM designed to identify Class B metallo-beta-lactamases, and combination inhibition tests using phenylboronic acid, cloxacillin and EDTA. Of the 213 CRE isolates, 203 were confirmed carbapenemase producers by mCIM. From this positive pool, a consecutive subset of 98 isolates with viable stored stock and sufficient DNA yield was selected for multiplex PCR-based gene profiling using validated primers originally described by Poirel and colleagues, with amplification performed on a ProFlex thermocycler and amplicons resolved on agarose gels. The authors caution that all gene-detection rates apply to this genotyped subset, which represents 48.3 percent of the mCIM-positive isolates, and should not be extrapolated as prevalence estimates for the entire CRE cohort.

The molecular results were striking. Among the 98 profiled isolates, 60 were Escherichia coli, 33 were Klebsiella pneumoniae, and the remainder comprised Citrobacter freundii and Enterobacter species. blaNDM emerged as the most prevalent gene, detected in 63.27 percent of isolates, with E. coli and K. pneumoniae as the predominant carriers. blaOXA-48 followed closely at 61.22 percent, while blaIMP appeared in 10.20 percent, blaKPC in 5.10 percent and blaVIM in 3.06 percent. Perhaps most concerning was the degree of co-carriage: half of the genotyped K. pneumoniae isolates carried both NDM and OXA-48 simultaneously, and 27.27 percent of E. coli harbored the same dual combination. Individual isolates carrying three resistance genes, such as NDM, OXA-48 and KPC together, were also documented, illustrating how bacterial genomes can accumulate layered defensive armories.

The comparison between phenotypic and genotypic results revealed both reassuring agreement and instructive discrepancies. All isolates carrying blaKPC were mCIM positive and displayed Class A carbapenemase phenotypes, and every isolate harboring a metallo-beta-lactamase gene, whether blaNDM, blaIMP or blaVIM, was positive on both mCIM and eCIM, confirming Class B enzyme production. However, among the 60 isolates carrying blaOXA-48, only two exhibited the phenotypic signature of Class D carbapenemase, a gap the authors attribute partly to limitations in the EUCAST-recommended temocillin zone-diameter threshold used as an indirect confirmatory test. Unexpressed genes, undetected beta-lactamase families such as blaSPM or blaGIM, and PCR inhibitors may all contribute to such mismatches, and the researchers note that amplicons were not confirmed by sequencing, meaning allelic variants cannot be entirely excluded.

These findings carry direct implications for therapy. Given the overwhelming predominance of Class B metallo-beta-lactamases, particularly NDM, the authors argue that empirical treatment of suspected CRE infections in this region should prioritize agents with proven activity against Class B enzymes, such as cefiderocol or the combination of ceftazidime-avibactam with aztreonam. They also emphasize that neither phenotypic nor genotypic testing alone is sufficient, and that balancing both approaches offers the most complete picture of resistance. International comparisons in the study highlight how sharply gene distributions vary by geography, with Thailand reporting NDM rates of ninety percent, China dominated by KPC at 53.4 percent, and Saudi Arabia led by OXA-48 at 76.11 percent, reinforcing that local surveillance data are indispensable for guiding rational antibiotic use.

Beyond its immediate clinical relevance, the study fills a critical gap in India’s national antimicrobial resistance surveillance architecture. Bihar and neighboring eastern states carry enormous infectious disease burdens yet have historically lacked the molecular diagnostic capacity to characterize circulating resistance mechanisms, undermining targeted infection control interventions. By documenting the genotypic landscape of CRE in an underrepresented setting, the AIIMS Patna team supports the objectives of India’s National Action Plan on Antimicrobial Resistance, particularly those concerning laboratory strengthening and evidence-based surveillance. The researchers acknowledge limitations, including the subset-based genotyping design and the absence of sequencing-based strain typing, and they plan future work involving blaNDM allele subtyping and whole-genome sequencing to trace clonal spread. For now, their findings stand as a clear warning and a practical guide: the superbugs of eastern India are armed with a dangerous genetic repertoire, but knowing exactly which weapons they carry is the first step toward disarming them.

Subject of Research: Genotypic profiling of carbapenemase genes in carbapenem-resistant Enterobacterales at a tertiary care hospital in Bihar, India

Article Title: Deciphering the genotypic profiles of Carbapenem-resistant Enterobacterales: A study from a tertiary care hospital in Bihar, India

Article References: Pramurtajyoti, D., Prathyusha, K., Zeeshan, F. M., Asim, S., Pati Binod, K., & Bhaskar, T. (2026). Deciphering the genotypic profiles of Carbapenem-resistant Enterobacterales: A study from a tertiary care hospital in Bihar, India. New Microbes and New Infections, 73, Article 101850. https://doi.org/10.1016/j.nmni.2026.101850

Image Credits: AI Generated

DOI: 10.1016/j.nmni.2026.101850

Keywords: carbapenem-resistant Enterobacterales, antimicrobial resistance, blaNDM, blaOXA-48, carbapenemase genes, multiplex PCR, Klebsiella pneumoniae, Escherichia coli, metallobeta-lactamases, India, hospital surveillance, infection control

The BioThreat Panel v2.5 covers 16 biothreat targets spanning bacteria, viruses and toxin-encoding genes. Its bacterial targets include Bacillus anthracis, Brucella melitensis, Burkholderia mallei/pseudomallei, Coxiella burnetii, Francisella tularensis, Rickettsia prowazekii and Y. pestis. Viral targets include Eastern equine encephalitis virus, Venezuelan equine encephalitis virus, Western equine encephalitis virus, variola virus, orthopoxviruses, Orthoebolavirus zairense and Orthomarburgvirus marburgense. The panel also seeks genes encoding botulinum toxin from Clostridium botulinum and ricin toxin from Ricinus communis. Because several targets are represented by multiple assays, the instrument software combines individual assay results into a final qualitative call: “Detected,” “Not Detected” or “Possible Detection.” In the study’s limit-of-detection analysis, “Possible Detection” was treated as equivalent to “Not Detected,” making the reported performance dependent not only on molecular amplification but also on the software’s decision rules.

Both systems use a disposable BIOFIRE pouch containing the reagents needed for sample processing and amplification. Once a sample is loaded, the instrument automatically performs nucleic-acid extraction and purification, reverse transcription when RNA is present, and a multiplex first-stage PCR. The amplified material is then diluted and distributed across a 102-well array, where target-specific primers are pre-spotted for individual nested second-stage PCR reactions. Each assay is placed in triplicate. This architecture allows DNA and RNA targets to be examined in one run while keeping hands-on manipulation low. After amplification, the systems analyze fluorescence and the melting behavior of the resulting DNA products. In melt-curve analysis, each product’s melting temperature is compared with an assay-specific expected range. An assay is considered positive when at least two of its three array wells produce positive melt curves with similar melting temperatures. The software then integrates those assay-level findings according to target-specific algorithms and reports the final result in approximately one hour.

The study evaluated performance in two sequential phases. First, the researchers estimated a preliminary limit of detection by testing analyte pools across multiple dilutions, including at least three tenfold dilution steps. Each dilution was run in three pouches on each instrument. After identifying a useful concentration range, individual analytes were tested at fivefold dilutions, with four pouches at each concentration on each platform. The lowest concentration detected in all four pouches was designated the estimated limit of detection, unless review of amplification curves suggested that the result would be unlikely to hold up in confirmation testing. The second phase tested 20 independently prepared pouches at the estimated limit and another 20 at a tenfold lower concentration. A limit of detection was confirmed when at least 19 of 20 pouches at the proposed concentration produced a “Detected” result, while fewer than 19 of 20 did so at the lower concentration. Testing used contrived samples prepared in phosphate-buffered saline rather than naturally collected environmental material, and all work was performed in a certified Biosafety Level 2 laboratory under institutional biosafety procedures.

In total, the investigators examined 18 representative analytes corresponding to the panel’s 16 targets. All analytes were quantified in-house with digital PCR before testing. Where possible, the researchers used live or inactivated organisms suitable for work in the Biosafety Level 2 setting. When those materials were unavailable, they used genomic nucleic acid; for Eastern equine encephalitis virus, variola virus, C. botulinum and C. burnetii, they used synthetic templates based on reference-organism sequences. The study included both Ames and Sterne 34F2 strains of B. anthracis, whose different genetic content was expected to produce different software interpretations, and the Ravn and Voege virus types of O. marburgense. Variola testing used three nucleic-acid templates together to represent the four assay signals required for a “Variola virus Detected” interpretation. These substitutions allowed the researchers to evaluate the panel’s analytical behavior without introducing all of the relevant high-consequence organisms into the laboratory, but they also mean that the results do not constitute a direct assessment of every possible field sample or strain.

The confirmed results showed that seven analytes had the same limit of detection on both instruments: the Ames and Sterne 34F2 strains of B. anthracis, B. melitensis, B. pseudomallei, C. burnetii, F. tularensis and the German Voege type of O. marburgense. Eight additional analytes displayed similar sensitivity, defined in the study as limits of detection within fivefold between platforms. This group included R. prowazekii, O. zairense, the Ravn type of O. marburgense, modified Vaccinia Ankara virus, variola virus, Venezuelan equine encephalitis virus, Western equine encephalitis virus and ricin-associated sequences. Two analytes, Eastern equine encephalitis virus and C. botulinum toxin-encoding sequences, showed more than fivefold improved sensitivity on SPOTFIRE. These findings do not establish that SPOTFIRE is universally more sensitive; rather, they show that its performance was similar or better for nearly all analytes examined under the study conditions.

The exception was Y. pestis, the bacterium associated with plague. The panel uses two assays for this target, called YPT1 and YPT3, which detect sequences on distinct plasmids. On FILMARRAY 2.0, a positive result from either assay can produce a “Y. pestis Detected” interpretation. On SPOTFIRE, the YPT3 assay must be positive for that final call. The difference was introduced to increase stringency and specificity because the genetic locus targeted by YPT1, the pla gene on the pPCP1 plasmid, has been reported in bacterial species other than Y. pestis. The pPCP1 plasmid is generally more abundant than pMT1, which is targeted by YPT3. As a result, a sample containing enough material to trigger YPT1 but not YPT3 may be called positive on FILMARRAY 2.0 but not on SPOTFIRE. The reduced apparent sensitivity was therefore expected by the investigators and reflects a trade-off between analytical detection and confidence that the detected sequence is specific to the intended organism.

The researchers place the comparison in the context of operational testing, where speed, portability and logistics can be as important as molecular performance. FILMARRAY 2.0 has supported automated biothreat and infectious-disease testing, but it requires an external computer for control. SPOTFIRE integrates its interface into the instrument, occupies less benchtop space and can be configured with up to four vertically stacked modules. Both platforms automate the complete pouch workflow and have a run time of approximately one hour, while the consumables include internal process controls made from lyophilized Schizosaccharomyces pombe cells and a synthetic control incorporated into the final PCR stage. Those controls help indicate whether sample preparation, reverse transcription, amplification and the final reaction have worked as expected. The study concludes that BioThreat Panel v2.5 users can expect similar sensitivity and functionality on the two systems, with special attention to the platform-specific Y. pestis calling rule. The work was funded internally by BioFire Defense, the panel’s legal manufacturer, and all listed authors were company employees; the authors state that the underlying data are available from the corresponding author on reasonable request.

A limit of detection is an analytical measure rather than a guarantee that every field sample will be identified. In this study, the threshold was defined through repeated testing at a proposed concentration and at a tenfold lower concentration. Confirmation required at least 19 of 20 pouches to produce a final “Detected” call at the proposed level, while the lower concentration had to fall below that criterion. This approach incorporates run-to-run variability, but it remains tied to the particular sample preparation, reagent lots, templates and calling algorithms used in the experiment. A fivefold difference between platforms should therefore be interpreted as a comparison under controlled conditions, not as a universal ranking of instrument performance.

The distinction is especially important for environmental surveillance. The investigators used contrived material in phosphate-buffered saline, whereas real samples can contain substances that interfere with nucleic-acid purification, reverse transcription or PCR. Environmental material may also contain unevenly distributed targets, degraded nucleic acids or organisms at concentrations near the assay threshold. The use of genomic nucleic acid and synthetic templates further enabled testing of high-consequence targets under the laboratory’s biosafety arrangements, but it does not reproduce every feature of intact organisms, complex matrices or naturally collected specimens. Additional evaluations would be needed to characterize those factors across the settings in which the instruments might be deployed.

The pouch design places several quality checks inside an otherwise automated workflow. Lyophilized Schizosaccharomyces pombe cells function as an internal process control because they accompany sample handling, purification, reverse transcription and amplification. A separate synthetic control is incorporated into the final PCR stage, helping assess that the downstream reaction and detection components are functioning. These controls can distinguish a technically valid negative result from a failed process, although they do not establish that a particular environmental sample is free of a biothreat agent. Likewise, a positive molecular signal indicates the presence of a target sequence or toxin-associated gene, not necessarily organism viability, infectiousness or toxin activity. Such distinctions are important when laboratory results are incorporated into decisions about confirmatory testing, containment and public-health or security responses.

Subject of Research: Analytical sensitivity of an automated multiplex PCR biothreat panel on two BIOFIRE instrument platforms

Article Title: The BIOFIRE BioThreat Panel v2.5 demonstrates comparable sensitivity on the FILMARRAY 2.0 and SPOTFIRE systems

Article References: Nielson, J., Wright, K., Poloncic, K., Duclos, N., Sanchez, D., Pop, S., Pack, R., Genin, C., Kress, E., Bates, A., Brownlee, W., Lakman, K., & Kim, M. (2026). The BIOFIRE BioThreat Panel v2.5 demonstrates comparable sensitivity on the FILMARRAY 2.0 and SPOTFIRE systems. Discover Biotechnology, 3(1), Article 11. https://doi.org/10.1007/s44340-026-00058-x

Image Credits: AI Generated

DOI: 10.1007/s44340-026-00058-x

Keywords: biothreat detection, multiplex PCR, BIOFIRE, SPOTFIRE, FILMARRAY 2.0, limit of detection, pathogen diagnostics, environmental surveillance, BioThreat, Panel, demonstrates, comparable