Global patterns of allochthony in stream-riparian meta-ecosystems.

Ecosystems that are coupled by reciprocal flows of energy and nutrient subsidies can be viewed as a single "meta-ecosystem." Despite these connections, the reciprocal flow of subsidies is greatly asymmetrical and seasonally pulsed. Here, we synthesize existing literature on stream-riparian meta-ecosystems to quantify global patterns of the amount of subsidy consumption by organisms, known as "allochthony." These resource flows are important since they can comprise a large portion of consumer diets, but can be disrupted by human modification of streams and riparian zones. Despite asymmetrical subsidy flows, we found stream and riparian consumer allochthony to be equivalent. Although both fish and stream invertebrates rely on seasonally pulsed allochthonous resources, we find allochthony varies seasonally only for fish, being nearly three times greater during the summer and fall than during the winter and spring. We also find that consumer allochthony varies with feeding traits for aquatic invertebrates, fish, and terrestrial arthropods, but not for terrestrial vertebrates. Finally, we find that allochthony varies by climate for aquatic invertebrates, being nearly twice as great in arid climates than in tropical climates, but not for fish. These findings are critical to understanding the consequences of global change, as ecosystem connections are being increasingly disrupted.

Reemergence of Bordetella parapertussis, United States, 2019-2023.

To determine changes in Bordetella pertussis and B. parapertussis detection rates, we analyzed 1.43 million respiratory multiplex PCR test results from US facilities from 2019 through mid-2023. From mid-2022 through mid-2023, Bordetella spp. detection increased 8.5-fold; 95% of detections were B. parapertussis. While B. parapertussis rates increased, B. pertussis rates decreased.

A Hierarchical Genotyping Framework Using DNA Melting Temperatures Applied to Adenovirus Species Typing.

Known genetic variation, in conjunction with post-PCR melting curve analysis, can be leveraged to provide increased taxonomic detail for pathogen identification in commercial molecular diagnostic tests. Increased taxonomic detail may be used by clinicians and public health decision-makers to observe circulation patterns, monitor for outbreaks, and inform testing practices. We propose a method for expanding the taxonomic resolution of PCR diagnostic systems by incorporating a priori knowledge of assay design and sequence information into a genotyping classification model. For multiplexed PCR systems, this framework is generalized to incorporate information from multiple assays to increase classification accuracy. An illustrative hierarchical classification model for human adenovirus (HAdV) species was developed and demonstrated ~95% cross-validated accuracy on a labeled dataset. The model was then applied to a near-real-time surveillance dataset in which deidentified adenovirus detected patient test data from 2018 through 2021 were classified into one of six adenovirus species. These results show a marked change in both the predicted prevalence for HAdV and the species makeup with the onset of the COVID-19 pandemic. HAdV-B decreased from a pre-pandemic predicted prevalence of up to 40% to less than 5% in 2021, while HAdV-A and HAdV-F species both increased in predicted prevalence.

Candida auris rates in blood culture on the rise: results of US surveillance.

Candida auris is an emerging pathogen that poses a significant public health risk. Its multidrug resistance has led to high mortality, making rapid detection crucial for effective treatment and prevention of transmission. Recent data from the Centers for Disease Control and Prevention indicate a substantial increase in C. auris cases in the United States, with a 95% rise in 2021. To provide an update on the detection rates of C. auris, we analyzed blood culture results from a near real-time cloud-based surveillance network, BioFire Trend. From January 2021 to April 2023, 34 C. auris detections were observed. The analysis showed a notable increase in detections in 2023 compared to previous years. The detection rate in 2023 was higher in all four US Census Regions, except for the Northeast, where it remained constant. The findings emphasize the continuous rise in C. auris cases and highlight the importance of near real-time surveillance systems in monitoring this emerging pathogen.

How Virtual Animal Anatomy facilitated a successful transition to online instruction and supported student learning during the coronavirus pandemic.

Anatomy faculty with cadaver-based laboratory courses were presented with a significant challenge in March 2020 to create equivalent learning experiences without cadaveric access. The undergraduate domestic animal anatomy course at the Colorado State University was halfway into a 16-week semester when COVID-19 lockdown orders and the transition to remote instruction began. The new course curriculum was critically evaluated using student surveys and course outcome data. Most students (92.5%) agreed that the transition to online learning was a success; however, students who valued face-to-face lectures prior to March were less likely to perceive the transition as a success. Qualitative and quantitative analyses of survey results suggest that the resources perceived as most helpful for the transition to online learning were not the same as those that helped facilitate animal anatomy learning. Most students (92.5%) agreed that the Virtual Animal Anatomy (VAA) helped them learn anatomy, and 82.2% indicated that the VAA was a valuable resource following the transition to online learning. Additional resources associated with transition success included course instructors, weekly quizzes, written descriptions of anatomical structures and open laboratory sessions. In contrast, those resources associated with facilitating learning included guided quizzes and asynchronous lecture recordings. These findings suggest that the VAA can support online anatomy learning when used in conjunction with other best practices for online teaching.

Enhancing Anatomical Instruction: Impact of a Virtual Canine Anatomy Program on Student Outcomes.

Innovative reforms in medical education will require instructional tools to support these changes and to give students more flexibility in where and how they learn. At Colorado State University, the software program Virtual Canine Anatomy (VCA) was developed to assist student learning both inside and outside the anatomical laboratory. The program includes interactive anatomical photographs of dissected canine cadavers, dissection instructions with accompanying videos and diagrams, radiographs, and three-dimensional models. There is a need to evaluate the effectiveness of instructional tools like VCA so that decisions on pedagogical delivery can be evidence-based. To measure the impact of VCA on student outcomes in a dissection laboratory, this study compared student attitudes, quiz scores, dissection quality and accuracy, and instructor reliance between students with and without access to VCA. Students with VCA needed less time with teaching assistants (P < 0.01), asked teaching assistants fewer questions (P = 0.04), felt that the dissection was easier (P = 0.02), and were in stronger agreement that they had access to adequate resources (P = 0.02). No differences were found in the dissection quality or accuracy, quiz scores, or attitudes regarding overall enjoyment of the activity between the two groups. This study shows that VCA increases student independence and can be used to enhance anatomical instruction.

Estimating thresholds in occupancy when species detection is imperfect.

Identification of thresholds (state changes over a narrow range of values) is of basic and applied ecological interest. However, current methods of estimating thresholds in occupancy ignore variation in the observation process and may lead to erroneous conclusions about ecological relationships or to the development of inappropriate conservation targets. We present a model to estimate a threshold in occupancy while accounting for imperfect species detection. The threshold relationship is described by a break-point (threshold) and the change in slope (threshold effect). Imperfect species detection is incorporated by jointly modeling species occurrence and species detection. We used WinBUGS to evaluate the model through simulation and to fit the model to avian occurrence data for three species from 212 sites with two replicate surveys in 2007-2008. To determine if accounting for imperfect detection changed the inference about thresholds in avian occupancy in relation to habitat structure, we compared our model to results from a commonly used threshold model (segmented logistic regression). We fit this model in both frequentist and Bayesian modes of inference. Results of the simulation study showed that 95% posterior intervals contained the true value of the parameter in approximately 95% of the simulations. As expected, the simulations indicated more precise threshold and parameter estimates as sample size increased. In the empirical study, we found evidence for threshold relationships for four species by covariate combinations when ignoring species detection. However, when we included variation from the observation process, threshold relationships were not supported in three of those four cases (95% posterior intervals included 0). In general, confidence intervals for the threshold effect were larger when we accounted for species nondetection than when we ignored nondetection. This model can be extended to investigate abundance thresholds as a function of ecological and anthropogenic factors, as well as multispecies hierarchical models.

The Effects of Social Distancing Policies on Non-SARS-CoV-2 Respiratory Pathogens.

BACKGROUND: The initial focus of the US public health response to coronavirus disease 2019 (COVID-19) was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) respiratory pathogens typically circulating across multiple US states. METHODS: Linear mixed-effect models were implemented to explore the effects of 5 social distancing policies on non-SARS-CoV-2 respiratory pathogens across 9 states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week by week with historical rates to determine when the detection rates were different. RESULTS: Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. The total detection rate in April 2020 was 35% less than the historical average. Many of the pathogens driving this difference fell below the historical detection rate ranges within 2 weeks of initial policy implementation. CONCLUSIONS: This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

Performance of a Semiquantitative Multiplex Bacterial and Viral PCR Panel Compared With Standard Microbiological Laboratory Results: 396 Patients Studied With the BioFire Pneumonia Panel.

BACKGROUND: Microbiologic results are critical to optimal management of patients with lower respiratory tract infection, but standard methods may take several days. The multiplex polymerase chain reaction BioFire Pneumonia (PN) panel detects 15 common bacterial species semiquantitatively as copy number/mL, 8 viral species, and 7 resistance genes in about an hour within the clinical laboratory. METHODS: We tested 396 unique endotracheal or bronchoalveolar lavage specimens with the BioFire Pneumonia panel and compared the bacterial detections to conventional gram stain and culture results. RESULTS: Of the 396 patients, 138 grew at least 1 bacterium that had a target on the PN panel, and 136/138 (98.6%) were detected by the panel. A total of 177 isolates were recovered in culture and the PN panel detected 174/177 (98.3%). A further 20% of patients had additional targets detected that were not found on standard culture (specificity 69%, positive predictive value 63%, and negative predictive value 98.9%). Copy number was strongly related to standard semiquantitative growth on plates reported by the laboratory (eg, 1+, 2+, 3+ growths) and was significantly higher in those specimens that grew a potential pathogen. Both higher copy number and bacterial detections found by the PN panel, but not found in culture, were strongly positively related to the level of white blood cells reported in the initial gram stain. CONCLUSIONS: Higher copy number and bacterial detections by the PN panel are related to the host respiratory tract inflammatory response. If laboratories can achieve a rapid turnaround time, the PN panel should have a significant impact both on patient management and on antibiotic stewardship.

Native size-exclusion chromatography-mass spectrometry: suitability for antibody-drug conjugate drug-to-antibody ratio quantitation across a range of chemotypes and drug-loading levels.

Native size-exclusion chromatography-mass spectrometry (nSEC-MS) is an analytical methodology that is appropriate for accurately quantitating the drug-to-antibody ratio (DAR) on a wide variety of interchain cysteine-linked antibody-drug conjugates (ADCs), irrespective of chemotype. In the current preclinical environment, novel ADCs conjugated with unique drug-linkers need to progress toward the clinic as quickly as possible. Platform analytical approaches can reduce time-to-clinic because key process development and optimization activities can be decoupled from the development of bespoke, molecule-specific analytical methods. In this work, we assessed the potential of nSEC-MS as a platformable, quantitative DAR method. The nSEC-MS method was evaluated according to performance characteristics and parameters described in the ICH guideline Validation of Analytical Procedures: Text and Methodology Q2(R1). In order to comprehensively assess the accuracy and bias of nSEC-MS DAR quantitation, ADCs were generated using three different drug-linker chemotypes with DARs ranging from 2 to 8. These molecules were tested by hydrophobic interaction chromatography (HIC) and nSEC-MS, and DARs obtained from both methods were compared to assess the degree to which nSEC-MS quantitation aligned with the HIC release assay. Our results indicated that there is no bias introduced by nSEC-MS quantitation of DAR and that SEC-MS data can be bridged to HIC data without the need for a correction factor or offset. nSEC-MS was also found to be suitable for unbiased DAR quantitation in the other ADC chemotypes that were evaluated. Based on the totality of our work, we conclude that, used as intended, nSEC-MS is well suited for quantitating DAR on a variety of interchain cysteine-linked ADCs in an accurate, unbiased manner.

A statistical approach to white-nose syndrome surveillance monitoring using acoustic data.

Traditional pathogen surveillance methods for white-nose syndrome (WNS), the most serious threat to hibernating North American bats, focus on fungal presence where large congregations of hibernating bats occur. However, in the western USA, WNS-susceptible bat species rarely assemble in large numbers and known winter roosts are uncommon features. WNS increases arousal frequency and activity of infected bats during hibernation. Our objective was to explore the effectiveness of acoustic monitoring as a surveillance tool for WNS. We propose a non-invasive approach to model pre-WNS baseline activity rates for comparison with future acoustic data after WNS is suspected to occur. We investigated relationships among bat activity, ambient temperatures, and season prior to presence of WNS across forested sites of Montana, USA where WNS was not known to occur. We used acoustic monitors to collect bat activity and ambient temperature data year-round on 41 sites, 2011-2019. We detected a diverse bat community across managed (n = 4) and unmanaged (n = 37) forest sites and recorded over 5.37 million passes from bats, including 13 identified species. Bats were active year-round, but positive associations between average of the nightly temperatures by month and bat activity were strongest in spring and fall. From these data, we developed site-specific prediction models for bat activity to account for seasonal and annual temperature variation prior to known occurrence of WNS. These prediction models can be used to monitor changes in bat activity that may signal potential presence of WNS, such as greater than expected activity in winter, or less than expected activity during summer. We propose this model-based method for future monitoring efforts that could be used to trigger targeted sampling of individual bats or hibernacula for WNS, in areas where traditional disease surveillance approaches are logistically difficult to implement or because of human-wildlife transmission concerns from COVID-19.

Enterovirus D68 outbreak detection through a syndromic disease epidemiology network.

BACKGROUND: In 2014, enterovirus D68 (EV-D68) was responsible for an outbreak of severe respiratory illness in children, with 1,153 EV-D68 cases reported across 49 states. Despite this, there is no commercial assay for its detection in routine clinical care. BioFire® Syndromic Trends (Trend) is an epidemiological network that collects, in near real-time, deidentified. BioFire test results worldwide, including data from the BioFire® Respiratory Panel (RP). OBJECTIVES: Using the RP version 1.7 (which was not explicitly designed to differentiate EV-D68 from other picornaviruses), we formulate a model, Pathogen Extended Resolution (PER), to distinguish EV-D68 from other human rhinoviruses/enteroviruses (RV/EV) tested for in the panel. Using PER in conjunction with Trend, we survey for historical evidence of EVD68 positivity and demonstrate a method for prospective real-time outbreak monitoring within the network. STUDY DESIGN: PER incorporates real-time polymerase chain reaction metrics from the RPRV/EV assays. Six institutions in the United States and Europe contributed to the model creation, providing data from 1,619 samples spanning two years, confirmed by EV-D68 gold-standard molecular methods. We estimate outbreak periods by applying PER to over 600,000 historical Trend RP tests since 2014. Additionally, we used PER as a prospective monitoring tool during the 2018 outbreak. RESULTS: The final PER algorithm demonstrated an overall sensitivity and specificity of 87.1% and 86.1%, respectively, among the gold-standard dataset. During the 2018 outbreak monitoring period, PER alerted the research network of EV-D68 emergence in July. One of the first sites to experience a significant increase, Nationwide Children's Hospital, confirmed the outbreak and implemented EV-D68 testing at the institution in response. Applying PER to the historical Trend dataset to determine rates among RP tests, we find three potential outbreaks with predicted regional EV-D68 rates as high as 37% in 2014, 16% in 2016, and 29% in 2018. CONCLUSIONS: Using PER within the Trend network was shown to both accurately predict outbreaks of EV-D68 and to provide timely notifications of its circulation to participating clinical laboratories.

Disulfide connectivity of human immunoglobulin G2 structural isoforms.

In this communication we present the detailed disulfide structure of IgG2 molecules. The consensus structural model of human IgGs represents the hinge region positioned as a flexible linker connecting structurally isolated Fc and Fab domains. IgG2 molecules are organized differently from that model and exhibit multiple structural isoforms composed of (heavy chain-light chain-hinge) covalent complexes. We describe the precise connection of all the disulfide bridges and show that the IgG2 C H1 and C-terminal C L cysteine residues are either linked to each other or to the two upper hinge cysteine residues specific to the IgG2 subclass. A defined arrangement of these disulfide bridges is unique to each isoform. Mutation of a single cysteine residue in the hinge region eliminates these natural complexes. These results show that IgG2 structure is significantly different from the conventionally accepted immunoglobulin structural model and may help to explain some of the unique biological activity attributed only to this subclass.

Laboratory clinical effectiveness: pathologists improving clinical outcomes.

This article calls on pathologists to take a larger role in improving the performance of the American health care system. To improve outcomes for populations and individuals require that pathologists increase their activities outside of the traditional laboratory in interdisciplinary collaborations, outcomes research, health care systems development, and clinical care.

Ultraviolet Raman spectra and cross-sections of the G-series nerve agents.

Ultraviolet (UV) Raman spectroscopy is being applied to the detection of chemical agent contamination of natural and man-made surfaces. In support of these efforts, we have measured the UV Raman signatures of the G-series nerve agents GA (tabun), GB (sarin), GD (soman), GF (cyclosarin), and the agent simulant diisopropyl methylphosphonate (DIMP) at 248 nm and 262 nm, as well as taking their UV Raman and UV absorption cross-sections. Of these chemicals, only GA exhibits any significant pre-resonance enhancement. We also show that reduction of the excitation wavelength from 262 nm to 248 nm effectively shifts the Raman spectrum away from a substantial sample fluorescence background, implying a significant improvement in detection capability.

Heat shock protein expression is highly sensitive to ischemia-reperfusion injury in rat kidneys.

Renal injury is known to trigger upregulation of many intracellular signal proteins, but those most sensitive in responding to renal injury remain debatable. We used gene microarray analysis to compare gene expression in rat kidneys subjected to early ischemia-reperfusion injury (30 min of renal ischemia and 3 hr of reperfusion) with non-ischemic kidneys as controls. Among 31,100 genes analyzed, microarray analysis revealed 21 genes with >3-fold increase in expression in ischemic kidneys compared to control non-ischemic kidneys. These upregulated genes included heat shock protein 70 (43-fold), heat shock protein 27 (12-fold), heme oxygenase-1 (10-fold), kidney injury molecule-1 (8-fold), and several subtypes of S100 calcium-binding proteins (3.1- to 7.5-fold). Following a prolonged reperfusion period (48 hr) after 30 min of ischemia, acute tubular necrosis was obvious in the S3 segment of proximal tubules of ischemic kidneys. Injured proximal tubules showed upregulated expression of heat shock protein 70 by immunohistochemistry and by Western blotting. These data suggest that heat shock proteins (eg, heat shock protein 70, heat shock protein 27, and heme oxygenase-1) are crucial for renal cell response to ischemic injury and that heat shock protein 70 is a highly sensitive intracellular marker of ischemia-reperfusion injury.

Evidence for Brassinosteroid-Mediated PAT During Germination of Spathoglottis plicata (Orchidaceae).

Polar auxin transport (PAT) is facilitated by polar localization of PIN-FORMED (PIN) efflux carriers, which direct auxin flow and regulate developmental events. Brassinosteroids (BRs) and auxin work synergistically to promote growth, and in root geotropisms this cross-talk involves BR-directed polarization of PIN through the mobilization of F-actin. However, the role of BR in PAT during shoot growth, hair formation, and embryogenesis has not been well studied. Orchid seed are mature at a point in development that is analogous to the globular-stage of embryogenesis in typical angiosperms. Thus, this system provided a unique opportunity to study the effects of BR on PAT during embryogenesis-like events, including meristem/first leaf formation and protocorm/stem development, which is followed by protocorm hair formation. In this work, the degree to which BRs rescued embryo-like protocorms from the impact of PAT-disrupting agents, such as PAT inhibitors or high auxin levels, was determined based on growth responses. This study first established that auxin and BRs work together synergistically to promote seedling elongation in Spathoglottis. Repressed seedling growth caused by the PAT-disrupting agents was alleviated with eBL, suggesting that BRs enhance PAT in embryogenesis-like stages of young protocorms. However, similar responses were not evident in seed embryos. Results from this study also suggested that BRs may enhance orchid protocorm elongation by regulating auxin transport through an F-actin-mediated mechanism. With regard to protocorm hairs, increased eBL levels inhibited formation, whereas reduced BR biosynthesis altered hair patterning, and prevented outgrowth of auxin-stimulated hairs. Moreover, PAT inhibitors and repression of BR biosynthesis caused hair bud formation without hair outgrowth, suggesting a role for BR in PAT during protocorm hair development.

Automated Real-Time Collection of Pathogen-Specific Diagnostic Data: Syndromic Infectious Disease Epidemiology.

BACKGROUND: Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. OBJECTIVE: The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. METHODS: We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. RESULTS: The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. CONCLUSIONS: Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks.

Using Sigma Quality Control to Verify and Monitor Performance in a Multi-Instrument, Multisite Integrated Health Care Network.

The authors developed a system-wide integrated network of instrumentation and Sigma-based quality control for fundamental chemistry, coagulation, and hematology analysis. The authors have based selection of Westgard rules for run management on a straightforward, Sigma-driven selection process. The network includes multiple hospitals and large regional clinic laboratories. Most hospitals have multiple instruments; overall there are at least four distinct instrument models active from each manufacturer. The authors have measured and monitored Sigma values in this network for more than five years, to verify and validate performance and to provide ongoing justification for rules selection and rules changes when necessary.