A National, County-Level Evaluation of the Association Between COVID-19 and Sexually Transmitted Infections Within the United States in 2020.

BACKGROUND: Shifts in public health infrastructure to respond to one emerging health threat may have unanticipated consequences for preexisting diseases. Previous research evaluating the impact of COVID-19 on sexually transmitted infections (STIs) has been conducted nationally, with little exploration of the impact on a granular geospatial level. This ecological study seeks to quantify the association between COVID-19 cases or deaths and chlamydia, gonorrhea, and syphilis cases for all US counties in 2020. METHODS: Separate, adjusted multivariable quasi-Poisson models with robust standard errors modeled the county-level association between 2020 COVID-19 cases and deaths per 100,000 and 2020 chlamydia, gonorrhea, or syphilis cases per 100,000. Models were adjusted for sociodemographic characteristics. RESULTS: Every 1000 additional COVID-19 cases per 100,000 was associated with a 1.80% increase in the average number of chlamydia cases ( P < 0.001) and a 5.00% increase in the average number of gonorrhea cases ( P < 0.001). Every 1000 additional COVID-19 deaths per 100,000 was associated with a 57.9% increase in the average number gonorrhea cases ( P < 0.001) and a 74.2% decrease in the average number of syphilis cases ( P = 0.004). CONCLUSIONS: Higher rates of COVID-19 cases and deaths were associated with increased rates of some STIs at the US county level. The underlying reasons for these associations could not be established by this study. The emergency response to an emerging threat may have unanticipated influence on preexisting diseases that varies by level of governance.

Rapid identification of biothreat and other clinically relevant bacterial species by use of universal PCR coupled with high-resolution melting analysis.

A rapid assay for eubacterial species identification is described using high-resolution melt analysis to characterize PCR products. Unique melt profiles generated from multiple hypervariable regions of the 16S rRNA gene for 100 clinically relevant bacterial pathogens, including category A and B biothreat agents and their surrogates, allowed highly specific species identification.

Discrimination of Bacillus anthracis and closely related microorganisms by analysis of 16S and 23S rRNA with oligonucleotide microarray.

Analysis of 16S rRNA sequences is a commonly used method for the identification and discrimination of microorganisms. However, the high similarity of 16S and 23S rRNA sequences of Bacillus cereus group organisms (up to 99-100%) and repeatedly failed attempts to develop molecular typing systems that would use DNA sequences to discriminate between species within this group have resulted in several suggestions to consider B. cereus and B. thuringiensis, or these two species together with B. anthracis, as one species. Recently, we divided the B. cereus group into seven subgroups, Anthracis, Cereus A and B, Thuringiensis A and B, and Mycoides A and B, based on 16S rRNA, 23S rRNA and gyrB gene sequences and identified subgroup-specific makers in each of these three genes. Here we for the first time demonstrated discrimination of these seven subgroups, including subgroup Anthracis, with a 3D gel element microarray of oligonucleotide probes targeting 16S and 23S rRNA markers. This is the first microarray enabled identification of B. anthracis and discrimination of these seven subgroups in pure cell cultures and in environmental samples using rRNA sequences. The microarray bearing perfect match/mismatch (p/mm) probe pairs was specific enough to discriminate single nucleotide polymorphisms (SNPs) and was able to identify targeted organisms in 5min. We also demonstrated the ability of the microarray to determine subgroup affiliations for B. cereus group isolates without rRNA sequencing. Correlation of these seven subgroups with groupings based on multilocus sequence typing (MLST), fluorescent amplified fragment length polymorphism analysis (AFLP) and multilocus enzyme electrophoresis (MME) analysis of a wide spectrum of different genes, and the demonstration of subgroup-specific differences in toxin profiles, psychrotolerance, and the ability to harbor some plasmids, suggest that these seven subgroups are not based solely on neutral genomic polymorphisms, but instead reflect differences in both the genotypes and phenotypes of the B. cereus group organisms.

National Institute of Biomedical Imaging and Bioengineering Point-of-Care Technology Research Network: Advancing Precision Medicine.

To advance the development of point-of-care technology (POCT), the National Institute of Biomedical Imaging and Bioengineering established the POCT Research Network (POCTRN), comprised of Centers that emphasize multidisciplinary partnerships and close facilitation to move technologies from an early stage of development into clinical testing and patient use. This paper describes the POCTRN and the three currently funded Centers as examples of academic-based organizations that support collaborations across disciplines, institutions, and geographic regions to successfully drive innovative solutions from concept to patient care.

Bacterial analysis by MALDI-TOF mass spectrometry: an inter-laboratory comparison.

Bacterial analysis by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry has been demonstrated in numerous laboratories, and a few attempts have been made to compare results from different laboratories on the same organism. It has been difficult to understand the causes behind the observed differences between laboratories when different instruments, matrices, solvents, etc. are used. In order to establish this technique as a useful tool for bacterial identification, additional efforts in standardizing the methods by which MALDI mass spectra are obtained and comparisons of spectra from different instruments with different operators are needed. Presented here is an extension of our previous single-laboratory reproducibility study with three different laboratories in a controlled experiment with aliquots of the same bacterial culture, matrix stock solution, and calibrant standards. Using automated spectral collection of whole-cell bacteria and automated data processing and analysis algorithms, fingerprints from three different laboratories were constructed and compared. Nine of the ions appeared reproducibly within all three laboratories, with additional unique ions observed within each of the laboratories. An initial evaluation of the ability to use a fingerprint generated within one laboratory for bacterial identification of a sample from another laboratory is presented, and strategies for improving identification rates between laboratories is discussed.

NIST gold nanoparticle reference materials do not induce oxidative DNA damage.

One primary challenge in nanotoxicology studies is the lack of well-characterised nanoparticle reference materials which could be used as positive or negative nanoparticle controls. The National Institute of Standards and Technology (NIST) has developed three gold nanoparticle (AuNP) reference materials (10, 30 and 60 nm). The genotoxicity of these nanoparticles was tested using HepG2 cells and calf-thymus DNA. DNA damage was assessed based on the specific and sensitive measurement of four oxidatively-modified DNA lesions (8-hydroxy-2´-deoxyguanosine, 8-hydroxy-2´-deoxyadenosine, (5´S)-8,5´-cyclo-2´-deoxyadenosine and (5´R)-8,5´-cyclo-2´-deoxyadenosine) using liquid chromatography/tandem mass spectrometry. Significantly elevated, dose-dependent DNA damage was not detected at concentrations up to 0.2 µg/ml, and free radicals were not detected using electron paramagnetic resonance spectroscopy. These data suggest that the NIST AuNPs could potentially serve as suitable negative-control nanoparticle reference materials for in vitro and in vivo genotoxicity studies. NIST AuNPs thus hold substantial promise for improving the reproducibility and reliability of nanoparticle genotoxicity studies.

Perceptions on Point-of-Care Tests for Sexually Transmitted Infections - Comparison between Frontline Clinicians and Professionals in Industry.

OBJECTIVES: To determine if a gap exists between sexually transmitted infection (STI) clinicians and industry professionals regarding perceptions of the ideal types and characteristics of STI point-of-care tests (POCTs). METHODS: Our online survey design contained sections on demographics; barriers of use for available STI POCTs; characteristics of an ideal POCT, including prioritizing pathogens for targets; and "building your own POCT". Practicing clinicians and academic experts from two venues, STI-related international conference attendees and U.S. STD clinic clinicians, were invited to participate in the clinician survey. Professionals from industry in the STI diagnostic field were invited to participate in the industry survey. Chi-square test and conditional logistical regression were used for data analysis. RESULTS: Clinician survey participants (n=218) identified "the time frame required" (39.9%), "complexity" (31.2%), and "interruption of work flow" (30.3%) as the top three barriers making it difficult to use STI POCTs, while the industry survey participants (n=107) identified "complexity" (65.4%), "unreliability" (53.3%), and "difficulty in reading results" (34.6%) as the top three barriers (all p values <0.05). Sensitivity was always the most important attribute to be considered for a new STI POCT by both participant groups. Participants of the clinician group chose cost as the second priority attribute, while those of the industry group chose specificity as the second priority. CONCLUSION: We identified differences in the perceptions regarding barriers and ideal attributes for STI POCTs between frontline clinical providers and industry personnel. Tailored training is warranted to inform scientists, biomedical engineers, and other industry experts about characteristics that clinicians desire for STI POCTs.

Minding the Gap: An approach to determine critical drivers in the development of Point of Care diagnostics.

INTRODUCTION: A point of care test (POCT) for Chlamydia trachomatis detection is an urgent public health need. Technology advances in diagnostics have made solutions possible. Yet no reliable POCT exist. Our goal was to address the gap between chlamydia POCT needs and successful POCT development by determining which characteristics of POCT tests are most critical and if any flexibility in the attributes assigned those characteristics exist between technology developer and end user. METHODS: We employed a process known as WALEX (Warfare Analysis Laboratory Exercise) in combination with Design of Experiment (DOE) methodology using discrete choice experiments (DCE), to describe the attributes of the most realistic, rather than the most ideal POCT. The WALEX was conducted as interactive oral and simultaneous electronic discussion among experts with differing expertise, but linked by a common interest in development of a chlamydia POCT. RESULTS: Our studies demonstrated which features of the ideal chlamydia POCT were considered critical to test acceptance by users and which were open to negotiation. In particular, end users were more lenient on the requirement for the fastest ideal test and the lowest one time instrument costs, if the requirement for higher throughput, lowest cost and vaginal sample source collection were preserved. DOE methods used in forced choice question design provided confirmation of opinions derived from oral and electronic WALEX comments CONCLUSIONS: The WALEX in combination with DCE helped us achieve our goal in identifying the gaps in the chlamydia POCT and determining the most realistic solutions to bridge those gaps.

What qualities are most important to making a point of care test desirable for clinicians and others offering sexually transmitted infection testing?

BACKGROUND: To investigate the possible effects of different levels of attributes of a point-of-care test (POCT) on sexually transmitted infection (STI) professionals' decisions regarding an ideal POCT for STI(s). METHODS: An online survey was designed based on a large-scale in-depth focus discussion study among STI experts and professionals. The last section of the survey "build your own POCT" was designed by employing the discrete choice experiment approach. Practicing clinicians from two venues, STI-related international conference attendees and U.S. STD clinic clinicians were invited to participate in the survey. Conditional logistical regression modeling was used for data analysis. RESULTS: Overall, 256 subjects took the online survey with 218 (85%) completing it. Most of the participants were STD clinic clinicians who already used some POCTs in their practice. "The time frame required" was identified as a major barrier that currently made it difficult to use STI POCTs. Chlamydia trachomatis was the organism chosen as the top priority for a new POCT, followed by a test that would diagnose early seroconversion for HIV, and a syphilis POCT. Without regard to organism type selected, sensitivity of 90-99% was always the most important attribute to be considered, followed by a cost of $20. However, when the test platform was prioritized for early HIV seroconversion or syphilis, sensitivity was still ranked as most important, but specificity was rated second most important. CONCLUSIONS: STI professionals preferred C. trachomatis as the top priority for a new POCT with sensitivity over 90%, low cost, and a very short completion time.

Use of 16S rRNA, 23S rRNA, and gyrB gene sequence analysis to determine phylogenetic relationships of Bacillus cereus group microorganisms.

In order to determine if variations in rRNA sequence could be used for discrimination of the members of the Bacillus cereus group, we analyzed 183 16S rRNA and 74 23S rRNA sequences for all species in the B. cereus group. We also analyzed 30 gyrB sequences for B. cereus group strains with published 16S rRNA sequences. Our findings indicated that the three most common species of the B. cereus group, B. cereus, Bacillus thuringiensis, and Bacillus mycoides, were each heterogeneous in all three gene sequences, while all analyzed strains of Bacillus anthracis were found to be homogeneous. Based on analysis of 16S and 23S rRNA sequence variations, the microorganisms within the B. cereus group were divided into seven subgroups, Anthracis, Cereus A and B, Thuringiensis A and B, and Mycoides A and B, and these seven subgroups were further organized into two distinct clusters. This classification of the B. cereus group conflicts with current taxonomic groupings, which are based on phenotypic traits. The presence of B. cereus strains in six of the seven subgroups and the presence of B. thuringiensis strains in three of the subgroups do not support the proposed unification of B. cereus and B. thuringiensis into one species. Analysis of the available phenotypic data for the strains included in this study revealed phenotypic traits that may be characteristic of several of the subgroups. Finally, our results demonstrated that rRNA and gyrB sequences may be used for discriminating B. anthracis from other microorganisms in the B. cereus group.

Microorganism identification by matrix-assisted laser/desorption ionization mass spectrometry and model-derived ribosomal protein biomarkers.

An improved data analysis method is described for rapid identification of intact microorganisms from MALDI-TOF-MS data. The method makes no use of mass spectral fingerprints. Instead, a microorganism database is automatically generated that contains biomarker masses derived from ribosomal protein sequences and a model of N-terminal Met loss. We quantitatively validate the method via a blind study that seeks to identify microorganisms with known ribosomal protein sequences. We also include in the database microorganisms with incompletely known sets of ribosomal proteins to test the specificity of the method. With an optimal MALDI protocol, and at the 95% confidence level, microorganisms represented in the database with 20 or more biomarkers (i.e., those with complete or nearly completely sequenced genomes) are correctly identified from their spectra 100% of the time, with no incorrect identifications. Microorganisms with seven or less biomarkers (i.e., incompletely sequenced genomes) are either not identified or misidentified. Robustness with respect to variations in sample preparation protocol and mass analysis protocol is demonstrated by collecting data with two different matrixes and under two different ion-mode configurations. Statistical analysis suggests that, even without further improvement, the method described here would successfully scale up to microorganism databases with roughly 1000 microorganisms. The results demonstrate that microorganism identification based on proteome data and modeling can perform as well as methods based on mass spectral fingerprinting.