Search

Molecular cluster detection analyzes HIV sequences to identify rapid HIV transmission and inform public health responses. We describe changes in the capability to detect molecular clusters and in geographic variation in transmission dynamics. We examined the reporting completeness of HIV-1 polymerase sequences in quarterly National HIV Surveillance System datasets from December 2015 to December 2019. Priority clusters were identified quarterly. To understand populations recently affected by rapid transmission, we described the transmission risk and race/ethnicity of people in clusters first detected in 2018-2019. During December 2015 to December 2019, national sequence completeness increased from 26% to 45%. Of the 1212 people in the 136 clusters first detected in 2018-2019, 69% were men who have sex with men (MSM) and 11% were people who inject drugs (PWID). State-by-state analysis showed substantial variation in transmission risk and racial/ethnic groups in clusters of rapid transmission. HIV sequence reporting has increased nationwide. Molecular cluster analysis identifies rapid transmission in varied populations and identifies emerging patterns of rapid transmission in specific population groups, such as PWID, who, in 2015-2016, comprised only 1% of people in such molecular clusters. These data can guide efforts to focus, tailor, and scale up prevention and care services for these populations.

ObjectiveTo identify correlates of incident HIV infection in rapidly growing HIV molecular clusters.DesignPhylogenetic analysis of HIV public health surveillance data.MethodsHigh-priority HIV genetic transmission clusters with evidence of rapid growth in 2012 (i.e. clusters with a pairwise genetic distance ≤0.005 substitutions/site and at least three cases diagnosed in 2012) were identified using HIV-TRACE. Then, we investigated cluster growth, defined as HIV cases diagnosed in the following 5 years that were genetically linked to these clusters. For clusters that grew during the follow-up period, Bayesian molecular clock phylogenetic inference was performed to identify clusters with evidence of incident HIV infection (as opposed to diagnosis of previously infected cases) during this follow-up period.ResultsOf the 116 rapidly growing clusters identified, 73 (63%) had phylogenetic evidence for an incident HIV case during the 5-year follow-up period. Correlates of an incident HIV case arising in clusters included a greater number of diagnosed but virally unsuppressed cases in 2012, a greater number of inferred undiagnosed cases in the cluster in 2012, and a younger time of most recent common ancestor for the cluster.ConclusionThese findings suggest that incident infections in rapidly growing clusters originate equally from diagnosed but unsuppressed cases and undiagnosed infections. These results highlight the importance of promoting retention in care and viral suppression as well as partner notification and other case-finding activities when investigating and intervening on high-priority molecular transmission clusters.

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.

BackgroundDetecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States.MethodsWe analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using 2 genetic distance thresholds (0.5% and 1.5%) and 2 periods for diagnoses (all years and 2013-2015, ie, recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies.ResultsA distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5-13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years.ConclusionsOur approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.

Bovine clinical mastitis is an economically important disease in dairy industry worldwide resulting in reduction of milk yield and quality. Among mycotic mastitis, Candida spp. are commonly occurring opportunistic mycosis in immunocompromised animals. The microorganism's causing mastitis has high zoonotic potential and has been linked with rapid growth and introduction of antimicrobial resistance between animals and humans. The present study was conducted to isolate and identify the common pathogenic Candida spp. from bovine mastitis cases in India. The isolates were phenotypically characterized by culturing on Sabouraud's dextrose agar, Hichrome Candida differential agar and germ tube production test. Antibiogram was also performed to determine their antifungal activities. The phenotypically positive isolates were confirmed by polymerase chain reaction (PCR) and genetically analyzed by targeting 18S-ITS1-5.8S-ITS2-28S region specific for Candida spp. and identified the yeast at the species level. The antibiogram showed the isolates were highly sensitive with ketoconazole, clotrimazole and miconazole. The PCR assay identified C. lusitaniae and C. tropicalis based on the two distinctive amplicon sizes (592bp and 737bp) respectively. Also, the sequence analysis and phylogeny confirmed C. lusitaniae in six sequences and C. tropicalis in one sequence. It is worth noting that in this study, the species identification was consistent among PCR and genetic analysis. Therefore, the PCR based identification system of the fungal species performed in this study could be an efficient and time saving tool for early diagnosis of clinical mastitis in milch animal, which allows prompt control and application of speedy effective treatment. [ABSTRACT FROM AUTHOR]

Aim: The study aims to assess the efficacy of rose bengal (RB)-mediated antimicrobial photodynamic therapy (a-PDT) as an adjunct to scaling and root planing in the management of chronic periodontitis patients in terms of clinical parameters like gingival index (GI), probing pocket depth (PPD), clinical attachment level (CAL), and microbiological parameters like total microbial count, total red complex organism count, Porphyromonas gingivalis count, Treponema denticola count, and Tannerella forsythia count. Materials and Methods: In this randomized controlled clinical trial, a total of 30 patients were recruited who met the inclusion criteria. The participants were randomly allocated into group A with scaling and root planning (SRP) alone and group B with SRP + a-PDT. The clinical and microbiological parameters were measured at baseline and at 3-month follow-up. Intergroup and intragroup comparisons were performed using independent t test and paired t test, respectively. Value of p < 0.05 was considered as statistically significant. Results: At 3-month follow-up, group B treated with SRP + a-PDT showed statistically significant reduction in GI (0.58 - 0.20) and PPD (1.81 - 0.32 mm), gain in CAL (0.73 - 0.04 mm), and reduction in total microbial count [2.80 - 0.08 · 104 colony forming unit (CFU)], total red complex count (0.29 0.14 · 10² CFU), P. gingivalis count (0.43 0.13 · 10² CFU), T. denticola count (0.61 0.04 · 10² CFU), and T. forsythia count (0.59 - 0.04 · 102 CFU) as compared with group A (p < 0.05). Conclusion: RB-mediated a-PDT as an adjunct to SRP was significantly more effective in improving GI, PPD, and CAL and in reducing microbial count as compared with SRP alone in the management of chronic periodontitis. [ABSTRACT FROM AUTHOR]

key Clinical Message: Constrictive Pericarditis is a rare fibrotic conversion of the pericardium that results in non‐specific clinical symptoms such as hepatomegaly, ascites, pleural effusions, and lower extremity edema. A multi‐modal diagnostic approach with cardiac imaging tools, cardiac hemodynamic measurements, and tissue biopsy can be used to diagnose Constrictive Pericarditis. Constrictive Pericarditis is a rare complication resulting in the fibrotic conversion of the pericardium secondary to idiopathic, infective, post‐surgical, or post‐radiation etiologies. The rigid and restrictive nature of the pericardium can result in non‐specific symptoms of volume overload that can mimic liver cirrhosis or congestive heart failure. We present the case of a 73‐year‐old female with constrictive pericarditis who presented with vague symptoms of abdominal pain, abdominal bloating, and bilateral lower extremity edema. This case report highlights the clinical manifestation, invasive, and non‐invasive diagnostic work‐up, and management of constrictive pericarditis. [ABSTRACT FROM AUTHOR]

Anti-carbohydrate monoclonal antibodies (mAbs) hold great promise as cancer therapeutics and diagnostics. However, their specificity can be mixed, and detailed characterization is problematic, because antibody-glycan complexes are challenging to crystallize. Here, we developed a generalizable approach employing high-throughput techniques for characterizing the structure and specificity of such mAbs, and applied it to the mAb TKH2 developed against the tumor-associated carbohydrate antigen sialyl-Tn (STn). The mAb specificity was defined by apparent KD values determined by quantitative glycan microarray screening. Key residues in the antibody combining site were identified by site-directed mutagenesis, and the glycan-antigen contact surface was defined using saturation transfer difference NMR (STD-NMR). These features were then employed as metrics for selecting the optimal 3D-model of the antibody-glycan complex, out of thousands plausible options generated by automated docking and molecular dynamics simulation. STn-specificity was further validated by computationally screening of the selected antibody 3D-model against the human sialyl-Tn-glycome. This computational-experimental approach would allow rational design of potent antibodies targeting carbohydrates.