Ophthalmic manifestations of tuberculosis.

PURPOSE OF REVIEW: To evaluate the epidemiology, microbiology, and pathology of Mycobacterium Tuberculosis (MTB). Utilizing these basic science concepts, the reader will discover how MTB can cause disease in any part of ophthalmic system. This article will aid clinicians in establishing the difficult diagnosis and management strategies for ophthalmic tuberculosis (OTB). RECENT FINDINGS: Recently, expert panels have reached a consensus on naming conventions and treatment strategies for the variety of ocular tuberculosis (TB). This consensus helps individual clinicians decide when to recommend full anti-TB treatment. SUMMARY: Globally, TB is nearly ubiquitous in the human population. It is most recognized for its pulmonary disease, but pathology of nearly every structure of the ophthalmic system has been identified. This heterogeneity makes establishing a diagnosis difficult, but recent improvements in expert panel naming consensus and nucleic acid amplification tests are improving diagnostic abilities. Clinicians are now feeling more confident with prescribing anti-TB regimens, but ongoing questions regarding the use of oral steroids and risk of medication-induced ocular toxicity remain.

SARS-CoV-2 serology: Validation of high-throughput chemiluminescent immunoassay (CLIA) platforms and a field study in British Columbia.

BACKGROUND: SARS-CoV-2 antibody testing is required for estimating population seroprevalence and vaccine response studies. It may also increase case identification when used as an adjunct to routine molecular testing. We performed a validation study and evaluated the use of automated high-throughput assays in a field study of COVID-19-affected care facilities. METHODS: Six automated assays were assessed: 1) DiaSorin LIAISONTM SARS-CoV-2 S1/S2 IgG; 2) Abbott ARCHITECTTM SARS-CoV-2 IgG; 3) Ortho VITROSTM Anti-SARS-CoV-2 Total; 4) VITROSTM Anti-SARS-CoV-2 IgG; 5) Siemens SARS-CoV-2 Total Assay; and 6) Roche ElecsysTM Anti-SARS-CoV-2. The validation study included 107 samples (42 known positive; 65 presumed negative). The field study included 296 samples (92 PCR positive; 204 PCR negative or not PCR tested). All samples were tested by the six assays. RESULTS: All assays had sensitivities >90% in the field study, while in the validation study, 5/6 assays were >90% sensitive and DiaSorin was 79% sensitive. Specificities and negative predictive values were >95% for all assays. Field study estimated positive predictive values at 1-10% disease prevalence were 100% for Siemens, Abbott and Roche, while DiaSorin and Ortho assays had lower PPVs at 1% prevalence, but PPVs increased at 5-10% prevalence. In the field study, addition of serology increased diagnoses by 16% compared to PCR testing alone. CONCLUSIONS: All assays evaluated in this study demonstrated high sensitivity and specificity for samples collected at least 14 days post-symptom onset, while sensitivity was variable 0-14 days after infection. The addition of serology to the outbreak investigations increased case detection by 16%.

Influence of Music Style and Rate on Repetitive Finger Tapping.

Auditory cues, including music, are commonly used in the treatment of persons with Parkinson's disease. Yet, how music style and movement rate modulate movement performance in persons with Parkinson's disease have been neglected and remain limited in healthy young populations. The purpose of this study was to determine how music style and movement rate influence movement performance in healthy young adults. Healthy participants were asked to perform repetitive finger movements at two pacing rates (70 and 140 beats per minute) for the following conditions: (a) a tone only, (b) activating music, and (c) relaxing music. Electromyography, movement kinematics, and variability were collected. Results revealed that the provision of music, regardless of style, reduced amplitude variability at both pacing rates. Intermovement interval was longer, and acceleration variability was reduced during both music conditions at the lower pacing rate only. These results may prove beneficial for designing therapeutic interventions for persons with Parkinson's disease.

Diversity of bacteria at healthy human conjunctiva.

PURPOSE: Ocular surface (OS) microbiota contributes to infectious and autoimmune diseases of the eye. Comprehensive analysis of microbial diversity at the OS has been impossible because of the limitations of conventional cultivation techniques. This pilot study aimed to explore true diversity of human OS microbiota using DNA sequencing-based detection and identification of bacteria. METHODS: Composition of the bacterial community was characterized using deep sequencing of the 16S rRNA gene amplicon libraries generated from total conjunctival swab DNA. The DNA sequences were classified and the diversity parameters measured using bioinformatics software ESPRIT and MOTHUR and tools available through the Ribosomal Database Project-II (RDP-II). RESULTS: Deep sequencing of conjunctival rDNA from four subjects yielded a total of 115,003 quality DNA reads, corresponding to 221 species-level phylotypes per subject. The combined bacterial community classified into 5 phyla and 59 distinct genera. However, 31% of all DNA reads belonged to unclassified or novel bacteria. The intersubject variability of individual OS microbiomes was very significant. Regardless, 12 genera-Pseudomonas, Propionibacterium, Bradyrhizobium, Corynebacterium, Acinetobacter, Brevundimonas, Staphylococci, Aquabacterium, Sphingomonas, Streptococcus, Streptophyta, and Methylobacterium-were ubiquitous among the analyzed cohort and represented the putative "core" of conjunctival microbiota. The other 47 genera accounted for <4% of the classified portion of this microbiome. Unexpectedly, healthy conjunctiva contained many genera that are commonly identified as ocular surface pathogens. CONCLUSIONS: The first DNA sequencing-based survey of bacterial population at the conjunctiva have revealed an unexpectedly diverse microbial community. All analyzed samples contained ubiquitous (core) genera that included commensal, environmental, and opportunistic pathogenic bacteria.