Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches

Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.

Drug-Resistant Tuberculosis, Georgia, Kazakhstan, Kyrgyzstan, Moldova, and Ukraine, 2017-2022

In 2021, the World Health Organization recommended new extensively drug-resistant (XDR) and pre-XDR tuberculosis (TB) definitions. In a recent cohort of TB patients in Eastern Europe, we show that XDR TB as currently defined is associated with exceptionally poor treatment outcomes, considerably worse than for the former definition (31% vs. 54% treatment success).

Evaluation of the synergistic potential and mechanisms of action for de novo designed cationic antimicrobial peptides

Antimicrobial peptides (AMPs) have emerged as promising candidates in combating antimicrobial resistance - a growing issue in healthcare. However, to develop AMPs into effective therapeutics, a thorough analysis and extensive investigations are essential. In this study, we employed an in silico approach to design cationic AMPs de novo, followed by their experimental testing. The antibacterial potential of de novo designed cationic AMPs, along with their synergistic properties in combination with conventional antibiotics was examined. Furthermore, the effects of bacterial inoculum density and metabolic state on the antibacterial activity of AMPs were evaluated. Finally, the impact of several potent AMPs on E. coli cell envelope and genomic DNA integrity was determined. Collectively, this comprehensive analysis provides insights into the unique characteristics of cationic AMPs.

Evaluation of aircraft deicing fluid as an external carbon source for denitrification

Water resource recovery facilities (WRRFs) performing biological nitrogen removal (BNR) often require external carbon sources for meeting nitrogen discharge permit limits. This brings an additional financial burden to the facilities considering the continuous need of these external carbon sources. This paper evaluates the utilization of airport stormwater, which in the winter season is rich in aircraft deicing fluid (ADF) as an alternative external carbon source. Denitrification and nitrification bench scale experiments were performed to assess the efficacy of external carbon sources to remove nitrogen in WRRFs. Experimental results showed that ADFs achieve denitrification rates of 0.064-0.066 d-1, higher than what achieved by a commercial carbon source, MicroC 2000A, with corresponding value of 0.058 d-1 at low temperatures, as low as 13 °C, which is considered a worst-case scenario for nitrogen removal efficiency. Furthermore, no inhibition to nitrification associated with the ADFs was observed. Subsequently a dynamic modeling study was conducted to assess the performance of ADFs as external carbon sources for denitrification and compared them to the conventional source that was being used in a full-scale BNR process. Results from the dynamic modeling study revealed that if 40 % of the spent-ADF at LaGuardia airport, New York City, could be collected with the stormwater and conveyed to a WRRF via the sewer collection system, an approximate reduction of 30 % of the commercial external carbon source could be accomplished by repurposing a waste product. This study contributes to the potential of ADF as a denitrification aid and an alternative for commercially available carbon sources with comparable nitrogen removal efficiencies.

Tuberculosis Chest X-Ray Image Retrieval System Using Deep Learning Based Biomarker Predictions

The world health organization's global tuberculosis (TB) report for 2022 identifies TB, with an estimated 1.6 million, as a leading cause of death. The number of new cases has risen since 2020, particularly the number of new drug-resistant cases, estimated at 450,000 in 2021. This is concerning, as treatment of patients with drug resistant TB is complex and may not always be successful. The NIAID TB Portals program is an international consortium with a primary focus on patient centric data collection and analysis for drug resistant TB. The data includes images, their associated radiological findings, clinical records, and socioeconomic information. This work describes a TB Portals' Chest X-ray based image retrieval system which enables precision medicine. An input image is used to retrieve similar images and the associated patient specific information, thus facilitating inspection of outcomes and treatment regimens from comparable patients. Image similarity is defined using clinically relevant biomarkers: gender, age, body mass index (BMI), and the percentage of lung affected per sextant. The biomarkers are predicted using variations of the DenseNet169 convolutional neural network. A multi-task approach is used to predict gender, age and BMI incorporating transfer learning from an initial training on the NIH Clinical Center CXR dataset to the TB portals dataset. The resulting gender AUC, age and BMI mean absolute errors were 0.9854, 4.03years and 1.67 k g m 2 . For the percentage of sextant affected by lesions the mean absolute errors ranged between 7% to 12% with higher error values in the middle and upper sextants which exhibit more variability than the lower sextants. The retrieval system is currently available from https://rap.tbportals.niaid.nih.gov/find_similar_cxr.

Differences in pulmonary nodular consolidation and pulmonary cavity among drug-sensitive, rifampicin-resistant and multi-drug resistant tuberculosis patients: the Guangzhou computerized tomography study

Background

Pulmonary nodular consolidation (PN) and pulmonary cavity (PC) may represent the two most promising imaging signs in differentiating multidrug-resistant (MDR)-pulmonary tuberculosis (PTB) from drug-sensitive (DS)-PTB. However, there have been concerns that literature described radiological feature differences between DS-PTB and MDR-PTB were confounded by that MDR-PTB cases tend to have a longer history. This study seeks to further clarify this point.

Methods

All cases were from the Guangzhou Chest Hospital, Guangzhou, China. We retrieved data of consecutive new MDR cases [n=46, inclusive of rifampicin-resistant (RR) cases] treated during the period of July 2020 and December 2021, and according to the electronic case archiving system records, the main PTB-related symptoms/signs history was ≤3 months till the first computed tomography (CT) scan in Guangzhou Chest Hospital was taken. To pair the MDR-PTB cases with assumed equal disease history length, we additionally retrieved data of 46 cases of DS-PTB patients. Twenty-two of the DS patients and 30 of the MDR patients were from rural communities. The first CT in Guangzhou Chest Hospital was analysed in this study. When the CT was taken, most cases had anti-TB drug treatment for less than 2 weeks, and none had been treated for more than 3 weeks.

Results

Apparent CT signs associated with chronicity were noted in 10 cases in the DS group (10/46) and 9 cases in the MDR group (10/46). Thus, the overall disease history would have been longer than the assumed <3 months. Still, the history length difference between DS patients and MDR patients in the current study might not be substantial. The lung volume involvement was 11.3%±8.3% for DS cases and 8.4%±6.6% for MDR cases (P=0.022). There was no statistical difference between DS cases and MDR cases both in PN prevalence and in PC prevalence. For positive cases, MDR cases had more PN number (mean of positive cases: 2.63 vs. 2.28, P=0.38) and PC number (mean of positive cases: 2.14 vs. 1.38, P=0.001) than DS cases. Receiver operating characteristic curve analysis shows, PN ≥4 and PC ≥3 had a specificity of 86% (sensitivity 25%) and 93% (sensitivity 36%), respectively, in suggesting the patient being a MDR cases.

Conclusions

A combination of PN and PC features allows statistical separation of DS and MDR cases.

Viral and host mediators of non-suppressible HIV-1 viremia

Non-suppressible HIV-1 viremia (NSV) is defined as persistent low-level viremia on antiretroviral therapy (ART) without evidence of ART non-adherence or significant drug resistance. Unraveling the mechanisms behind NSV would broaden our understanding of HIV-1 persistence. Here we analyzed plasma virus sequences in eight ART-treated individuals with NSV (88% male) and show that they are composed of large clones without evidence of viral evolution over time in those with longitudinal samples. We defined proviruses that match plasma HIV-1 RNA sequences as 'producer proviruses', and those that did not as 'non-producer proviruses'. Non-suppressible viremia arose from expanded clones of producer proviruses that were significantly larger than the genome-intact proviral reservoir of ART-suppressed individuals. Integration sites of producer proviruses were enriched in proximity to the activating H3K36me3 epigenetic mark. CD4+ T cells from participants with NSV demonstrated upregulation of anti-apoptotic genes and downregulation of pro-apoptotic and type I/II interferon-related pathways. Furthermore, participants with NSV showed significantly lower HIV-specific CD8+ T cell responses compared with untreated viremic controllers with similar viral loads. We identified potential critical host and viral mediators of NSV that may represent targets to disrupt HIV-1 persistence.

Bifocal avulsion fracture and fixation of the patellar tendon: a case report

Acute distal patella tendon avulsion from the tibial tubercle (TT) is a relatively rare injury that is usually described in the adolescents or elderly population in their 7th or 8th decades. Bifocal avulsion fractures of the patella tendon from the TT and the distal pole of the patella are exceptionally rare in adults. In this case report, we present a 52-year-old healthy old male who was treated for bifocal avulsion of the patellar tendon with open reduction and internal fixation augmented with two ULTRATAPE sutures. To our knowledge, this is the first case report to describe this injury in a healthy middle-aged patient.

Predictive capabilities of baseline radiological findings for early and late disease outcomes within sensitive and multi-drug resistant tuberculosis cases

Purpose

This study compares performance of Timika Score to standardized, detailed radiologist observations of Chest X rays (CXR) for predicting early infectiousness and subsequent treatment outcome in drug sensitive (DS) or multi-drug resistant (MDR) tuberculosis cases. It seeks improvement in prediction of these clinical events through these additional observations.

Method

This is a retrospective study analyzing cases from the NIH/NIAID supported TB Portals database, a large, trans-national, multi-site cohort of primarily drug-resistant tuberculosis patients. We analyzed patient records with sputum microscopy readings, radiologist annotated CXR, and treatment outcome including a matching step on important covariates of age, gender, HIV status, case definition, Body Mass Index (BMI), smoking, drug use, and Timika Score across resistance type for comparison.

Results

2142 patients with tuberculosis infection (374 with poor outcome and 1768 with good treatment outcome) were retrospectively reviewed. Bayesian ANOVA demonstrates radiologist observations did not show greater predictive ability for baseline infectiousness (0.77 and 0.74 probability in DS and MDR respectively); however, the observations provided superior prediction of treatment outcome (0.84 and 0.63 probability in DS and MDR respectively). Estimated lung abnormal area and cavity were identified as important predictors underlying the Timika Score's performance.

Conclusions

Timika Score simplifies the usage of baseline CXR for prediction of early infectiousness of the case and shows comparable performance to using detailed, standardized radiologist observations. The score's utility diminishes for treatment outcome prediction and is exceeded by the usage of the detailed observations although prediction performance on treatment outcome decreases especially in MDR TB cases.

An explorative single-arm clinical study to assess craving in patients with alcohol use disorder using Virtual Reality exposure (CRAVE)-study protocol

BACKGROUND

Alcohol use disorder (AUD) belongs to the most burdensome clinical disorders worldwide. Current treatment approaches yield unsatisfactory long-term effects with relapse rates up to 85%. Craving for alcohol is a major predictor for relapse and can be intentionally induced via cue exposure in real life as well as in Virtual Reality (VR). The induction and habituation of craving via conditioned cues as well as extinction learning is used in Cue Exposure Therapy (CET), a long-known but rarely used strategy in Cognitive Behavioral Therapy (CBT) of AUD. VR scenarios with alcohol related cues offer several advantages over real life scenarios and are within the focus of current efforts to develop new treatment options. As a first step, we aim to analyze if the VR scenarios elicit a transient change in craving levels and if this is measurable via subjective and psychophysiological parameters.

METHODS

A single-arm clinical study will be conducted including n = 60 patients with AUD. Data on severity of AUD and craving, comorbidities, demographics, side effects and the feeling of presence in VR will be assessed. Patients will use a head-mounted display (HMD) to immerse themselves into three different scenarios (neutral vs. two target situations: a living room and a bar) while heart rate, heart rate variability, pupillometry and electrodermal activity will be measured continuously. Subjective craving levels will be assessed before, during and after the VR session.

DISCUSSION

Results of this study will yield insight into the induction of alcohol craving in VR cue exposure paradigms and its measurement via subjective and psychophysiological parameters. This might be an important step in the development of innovative therapeutic approaches in the treatment of patients with AUD.

TRIAL REGISTRATION

This study was approved by the Charité-Universitätsmedizin Berlin Institutional Review Board (EA1/190/22, 23.05.2023). It was registered on ClinicalTrials.gov (NCT05861843).

Consolidative Radiotherapy for Residual PET-Avid Disease on Day +30 Post CAR T-Cell Therapy in Non-Hodgkin Lymphoma

PURPOSE/OBJECTIVE(S)

Up to30% of non-Hodgkin lymphoma (NHL) patients achieve a partial response (PR) to anti-CD19 Chimeric Antigen Receptor T-cell Therapy (CART) on day +30. Most PR patients relapse and only 30% achieve spontaneous complete response (CR) without additional therapies. This study is the first to report on the role of consolidative radiotherapy (cRT) for PR PET-avid disease on day +30 post-CART in NHL.

MATERIALS/METHODS

Aretrospective review across 3 institutions from 2018 to 2022 identified 60 patients with B-cell NHL who received CART and achieved PR (Deauville 4-5) with <5 PET-avid disease sites on day +30. Progression-free survival (PFS) was defined from CART infusion to any disease progression. Overall survival (OS) was defined from CART infusion to death. Local relapse-free survival (LRFS), calculated based on the total number of PR sites, was defined from CART infusion to local relapse (LR) in the PR site identified on day +30. cRT was defined as comprehensive (compRT) - treated all PR PET-avid sites - or focal (focRT).

RESULTS

Followingday +30 PET scan, 45 PR patients were observed and 15 received cRT. Only one patient received consolidative systemic therapy and belonged to the cRT group. Prior to CART, bridging RT was given to 13 patients (9 in observation group and 4 in cRT group). There were no significant differences in the pre-CART and day +30 baseline characteristics, including the median size and SUVmax of the PR sites, between the two groups. However, the median number of PR sites on day +30 was higher in the cRT group (2 [range 1-3] vs 1 [range 1-3], p = 0.003). The median equivalent 2 Gy dose was 39.1 (Interquartile range 36.8-41) Gy, and the most common cRT regimen was 37.5 Gy in 15 fractions. The median follow-up was 21 months. Among the observed patients, 15 (33%) achieved spontaneous CR, and 27 (60%) experienced disease progression with all relapses involving the initial PR sites. Among patients who received cRT, 10 (67%) achieved CR, and 3 (20%) had disease progression with no relapses in the radiated PR sites. None of the 10 cRT patients achieving CR relapsed or required subsequent therapies. The 2-year PFS was 80% and 37% (p = 0.012) and the 2-year OS was 78% and 43% (p = 0.12) in the cRT and observation groups, respectively. Patients consolidated with compRT (n = 12) had superior 2-year PFS (92% vs 37%, p = 0.003) and 2-year OS (86% vs 43%, p = 0.048) compared to observed or focRT patients (n = 48). There were no grade 3+ RT-related toxicities. A total of 90 PR sites were identified; 64 were observed and 26 received cRT. Fourteen (22%) observed PR sites achieved spontaneous sustained CR and 42 (66%) experienced LR. Twenty-four (92%) PR sites consolidated with cRT achieved sustained CR and none experienced LR. The 2-year LRFS was 100% in the cRT sites and 31% in the observed sites (p<0.001).

CONCLUSION

NHL patients who achieve PR by PET to CART are at high risk of local progression. cRT for residual PET-avid disease on day +30 post-CART appears to alter the pattern of relapse and improve LRFS and PFS.

The Role of Radiation Therapy in the Management of Gray Zone Lymphoma

PURPOSE/OBJECTIVE(S)

Gray zone lymphoma (GZL) is a relatively rare disease predominantly affecting young adults with purportedly poor outcomes with current treatment approaches. The role of radiation therapy (RT) in the management of GZL is not well established. This is the largest study to report on the outcomes of GZL patients treated with and without RT.

MATERIALS/METHODS

A retrospective review of 30 patients with GZL treated across 3 institutions from 2009 to 2021 was performed. Event-free survival (EFS) was defined from initiation of frontline chemotherapy (CHT) to disease progression/relapse, initiation of salvage therapy, or death. Local control (LC) was defined from RT start date to in-field recurrence.

RESULTS

The median age was 32 (range: 18-86) years, and 16 (53%) patients had early stage (I-II) disease. Bulky mediastinal disease was present in 63% of patients, and the median tumor diameter was 10 (range: 1.5-18) cm. Patients received ABVD (20%), RCHOP (33%), or REPOCH (47%) as frontline CHT. Among 25 patients with interim PET/CT scan, there were 6 rapid early responders and 14 slow early responders (SER), with 2-year EFS of 33% and 24%, respectively (p = 0.13). After the completion of CHT, 15 (50%) patients achieved complete response (CR) and 10 (33%) achieved partial response (PR), with 2-year EFS of 46% and 10%, respectively (p = 0.004). RT was given to 9 patients in CR (n = 3) or in PR (n = 6). The median RT dose was 36 (30.6-48.6) Gy, at 1.8-2 Gy/fraction. Those receiving RT had bulkier disease at diagnosis (p = 0.049) and lower rates of CR following CHT (p = 0.03). After RT, 3/6 (50%) PR patients converted to CR. At a median follow-up of 4 years, the 2-year EFS was 26% for all patients, 33% for RT and 23% for noRT (p = 0.44). Among patients who did not receive upfront RT and experienced progression (n = 17), 16 (94%) relapsed in pre-existing sites. The 5-year OS was 80% for all patients, 88% for RT and 78% for no RT (p = 0.63). Patients who achieved PR to CHT and received RT had better 2-year EFS (17% vs 0%, p = 0.007) compared to patients who did not receive RT. Similarly, patients with SER who received RT had superior 2-year EFS (33% vs 13%, p = 0.038). Patients with bulky mediastinal disease had a 2-year EFS of 43% with RT and 11% without RT (p = 0.08). After 1st line treatment, 22 (73%) patients relapsed and 18 were successfully salvaged with a sustained CR. The most common salvage regimen involved high dose CHT followed by hematopoietic cell transplantation (HCT) (n = 15). RT was given for 7 patients in the relapsed/refractory setting (consolidative peri-HCT n = 4; definitive salvage n = 3) and 5 (71%) achieved a sustained CR. Among the 16 patients who received RT in the upfront (n = 9) or salvage (n = 7) setting, 3 patients experienced in-field recurrence translating to 2-year LC of 79%.

CONCLUSION

GZL patients have high risk of relapse and maximal upfront combined modality therapy should be considered. RT provides good local control and improves EFS particularly for SER, PR, and bulky mediastinal disease.

Lineage classification and antitubercular drug resistance surveillance of Mycobacterium tuberculosis by whole-genome sequencing in Southern India

Whole-genome sequencing has created a revolution in tuberculosis management by providing a comprehensive picture of the various genetic polymorphisms with unprecedented accuracy. Studies mapping genomic heterogeneity in clinical isolates of Mycobacterium tuberculosis using a whole-genome sequencing approach from high tuberculosis burden countries are underrepresented. We report whole-genome sequencing results of 242 clinical isolates of culture-confirmed M. tuberculosis isolates from tuberculosis patients referred to a tertiary care hospital in Southern India. Phylogenetic analysis revealed that the isolates in our study belonged to five different lineages, with Indo-Oceanic (lineage 1, n = 122) and East-African Indian (lineage 3, n = 80) being the most prevalent. We report several mutations in genes conferring resistance to first and second line antitubercular drugs including the genes rpoB, katG, ahpC, inhA, fabG1, embB, pncA, rpsL, rrs, and gyrA. The majority of these mutations were identified in relatively high proportions in lineage 1. Our study highlights the utility of whole-genome sequencing as a potential supplemental tool to the existing genotypic and phenotypic methods, in providing expedited comprehensive surveillance of mutations that may be associated with antitubercular drug resistance as well as lineage characterization of M. tuberculosis isolates. Further larger-scale whole-genome datasets with linked minimum inhibition concentration testing are imperative for resolving the discrepancies between whole-genome sequencing and phenotypic drug sensitivity testing results and quantifying the level of the resistance associated with the mutations for optimization of antitubercular drug and precise dose selection in clinics. IMPORTANCE Studies mapping genetic heterogeneity of clinical isolates of M. tuberculosis for determining their strain lineage and drug resistance by whole-genome sequencing are limited in high tuberculosis burden settings. We carried out whole-genome sequencing of 242 M. tuberculosis isolates from drug-sensitive and drug-resistant tuberculosis patients, identified and collected as part of the TB Portals Program, to have a comprehensive insight into the genetic diversity of M. tuberculosis in Southern India. We report several genetic variations in M. tuberculosis that may confer resistance to antitubercular drugs. Further wide-scale efforts are required to fully characterize M. tuberculosis genetic diversity at a population level in high tuberculosis burden settings for providing precise tuberculosis treatment.

Combining Radiological and Genomic TB Portals Data for Drug Resistance Analysis

Tuberculosis (TB) drug resistance is a worldwide public health problem. It decreases the likelihood of a positive outcome for the individual patient and increases the likelihood of disease spread. Therefore, early detection of TB drug resistance is crucial for improving outcomes and controlling disease transmission. While drug-sensitive tuberculosis cases are declining worldwide because of effective treatment, the threat of drug-resistant tuberculosis is growing, and the success rate of drug-resistant tuberculosis treatment is only around 60%. The TB Portals program provides a publicly accessible repository of TB case data with an emphasis on collecting drug-resistant cases. The dataset includes multi-modal information such as socioeconomic/geographic data, clinical characteristics, pathogen genomics, and radiological features. The program is an international collaboration whose participants are typically under a substantial burden of drug-resistant tuberculosis, with data collected from standard clinical care provided to the patients. Consequentially, the TB Portals dataset is heterogenous in nature, with data representing multiple treatment centers in different countries and containing cross-domain information. This study presents the challenges and methods used to address them when working with this real-world dataset. Our goal was to evaluate whether combining radiological features derived from a chest X-ray of the host and genomic features from the pathogen can potentially improve the identification of the drug susceptibility type, drug-sensitive (DS-TB) or drug-resistant (DR-TB), and the length of the first successful drug regimen. To perform these studies, significantly imbalanced data needed to be processed, which included a much larger number of DR-TB cases than DS-TB, many more cases with radiological findings than genomic ones, and the sparse high dimensional nature of the genomic information. Three evaluation studies were carried out. First, the DR-TB/DS-TB classification model achieved an average accuracy of 92.4% when using genomic features alone or when combining radiological and genomic features. Second, the regression model for the length of the first successful treatment had a relative error of 53.5% using radiological features, 25.6% using genomic features, and 22.0% using both radiological and genomic features. Finally, the relative error of the third regression model predicting the length of the first treatment using the most common drug combination varied depending on the feature type used. When using radiological features alone, the relative error was 17.8%. For genomic features alone, the relative error increased to 19.9%. The model had a relative error of 19.0% when both radiological and genomic features were combined. Although combining radiological and genomic features did not improve upon the use of genomic features when classifying DR-TB/DS-TB, the combination of the two feature types improved the relative error of the predictive model for the length of the first successful treatment. Furthermore, the regression model trained on radiological features achieved the best performance when predicting the treatment length of the most common drug combination.

Viral and Host Mediators of Non-Suppressible HIV-1 Viremia

Non-suppressible HIV-1 viremia (NSV) can occur in persons with HIV despite adherence to combination antiretroviral therapy (ART) and in the absence of significant drug resistance. Here, we show that plasma NSV sequences are comprised primarily of large clones without evidence of viral evolution over time. We defined proviruses that contribute to plasma viremia as "producer", and those that did not as "non-producer". Compared to ART-suppressed individuals, NSV participants had a significantly larger producer reservoir. Producer proviruses were enriched in chromosome 19 and in proximity to the activating H3K36me3 epigenetic mark. CD4+ cells from NSV participants demonstrated upregulation of anti-apoptotic genes and downregulation of pro-apoptotic and type I/II interferon-related pathways. Furthermore, NSV participants showed no elevation in HIV-specific CD8+ cell responses and producer proviruses were enriched for HLA escape mutations. We identified critical host and viral mediators of NSV that represent potential targets to disrupt HIV persistence and promote viral silencing.

Establishing a centralized data mart from the Rakai community cohort study to improve HIV research in Rakai, Uganda

To improve timely access to quality HIV research data, the Rakai Health Sciences Program (RHSP) Data Mart was developed to store cohort study data from a legacy database platform in a modernized system using standard data management processes. The RHSP Data Mart was developed on a Microsoft SQL Server platform using Microsoft SQL Server Integration Services with custom data mappings and queries. The data mart stores 20+ years of longitudinal HIV research data and includes standard processes for managing data, data dictionary, training materials, and a library of queries to fulfill data requests and load new data from completed survey rounds. The RHSP Data Mart enables efficient querying and analysis of multidimensional research data by simplifying data integration and processing. A sustainable database platform with well-defined data management processes promotes data accessibility and reproducibility, enabling researchers to advance their understanding and management of infectious diseases.

P-251 Cumulus cell analysis as a non-invasive oocyte selection strategy to reduce the number of oocytes/embryos cultured and increase pregnancy rates

Study question

Can non-invasive gene expression analysis of cumulus cells (CC) improve efficiency in ART by prioritizing oocytes for further culture and fresh single embryo transfer?

Summary answer

CC analysis can be used for the selective processing of oocytes. This may reduce culture work and improve the outcome in ICSI elective SETs (eSET).

What is known already

In an interventional, blinded, prospective cohort study (Van Vaerenbergh et al. 2021), 113 patients underwent a fresh Day3 eSET with embryos ranked and transferred based on morphology and CC gene expression (Aurora Test), while 520 control patients underwent a Day3 eSET without the Aurora Test. This resulted in a significant higher clinical pregnancy of 61% in the patients with eSET based on CC ranking applied on good morphology embryos, compared to 29% in the controls with eSET based on embryo morphology only. Live birth rate was also significantly increased, while time-to-pregnancy was significantly reduced with 3 transfer cycles.

Study design, size, duration

In a retrospective analysis, in a subset of patients with at least 6 growing follicles and at least five 2PN oocytes (n = 80), it was investigated whether the Aurora Test, used to select transferrable Day3-embryos, could also be applied to select oocytes on Day0/1. The effect of processing only the three highest ranked oocytes (based on the Aurora Test) on embryo development and clinical pregnancy was studied compared to processing all oocytes.

Participants/materials, setting, methods

Patients included in this single centre study had their first or second GnRH-antagonist ICSI cycle, were younger than 40y, had normal BMI, were stimulated with HP-hMG and scheduled for Day3 eSET. Two-sided statistical analysis (p &lt; 0,05) was performed between a strategy of processing only the top 3 Aurora ranked oocytes, according to CC gene expression, and a strategy of processing all available oocytes.

Main results and the role of chance

On average, 8 MII oocytes were obtained per patient and the average fertilization rate was 83%. In total, 407 good quality embryos (GQE) on Day3 were generated from these 80 patients when utilising all 639 oocytes. Processing the three top-ranked oocytes only (240/639 oocytes) would have reduced the number of embryos to 169 GQE and would have resulted in 2.1 GQE on average on Day3 per patient; 75/80 (94%) patients would have had a fresh Day3 transfer resulting in a 63% clinical pregnancy rate. Processing all 639 available 2PN oocytes (standard of care) resulted in a fresh Day3 transfer in all 80 patients and a similar 64% clinical pregnancy rate (ns). However, 399 more oocytes would need to be processed. The strategy of restricting the number of oocytes to be processed would not have compromised cumulative cycle outcome. Considering all subsequent freeze/thawing cycles the cumulative clinical pregnancy rate calculated per all 80 patients would increase to 90%.

Limitations, reasons for caution

The limitation of this approach is that the Aurora Test requires individual oocyte denudation and individual oocyte vitrification. Secondly, this new strategy should be validated in a prospective study.

Wider implications of the findings

By applying this oocyte selection strategy patients would benefit from a high pregnancy rate in the fresh transfer cycle, while the lab would see reduction in embryo culture work, because freeze/thawing cycles and culture of embryos with lower competence would be prevented.

Trial registration number

NA

Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction

The evolution of drug-resistant pathogenic microbial species is a major global health concern. Naturally occurring, antimicrobial peptides (AMPs) are considered promising candidates to address antibiotic resistance problems. A variety of computational methods have been developed to accurately predict AMPs. The majority of such methods are not microbial strain specific (MSS): they can predict whether a given peptide is active against some microbe, but cannot accurately calculate whether such peptide would be active against a particular MS. Due to insufficient data on most MS, only a few MSS predictive models have been developed so far. To overcome this problem, we developed a novel approach that allows to improve MSS predictive models (MSSPM), based on properties, computed for AMP sequences and characteristics of genomes, computed for target MS. New models can perform predictions of AMPs for MS that do not have data on peptides tested on them. We tested various types of feature engineering as well as different machine learning (ML) algorithms to compare the predictive abilities of resulting models. Among the ML algorithms, Random Forest and AdaBoost performed best. By using genome characteristics as additional features, the performance for all models increased relative to models relying on AMP sequence-based properties only. Our novel MSS AMP predictor is freely accessible as part of DBAASP database resource at http://dbaasp.org/prediction/genome.

Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome

MOTIVATION

Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.

RESULTS

Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms.

AVAILABILITY AND IMPLEMENTATION

All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Patterns of genomic interrelatedness of publicly available samples in the TB portals database

The TB Portals program is an international collaboration for the collection and dissemination of tuberculosis data from patient cases focused on drug resistance. The central database is a patient-oriented resource containing both patient and pathogen clinical and genomic information. Herein we provide a summary of the pathogen genomic data available through the TB Portals and show one potential application by examining patterns of genomic pairwise distances. Distributions of pairwise distances highlight overall patterns of genome variability within and between Mycobacterium tuberculosis phylogenomic lineages. Closely related isolates (based on whole-genome pairwise distances and time between sample collection dates) from different countries were identified as potential evidence of international transmission of drug-resistant tuberculosis. These high-level views of genomic relatedness provide information that can stimulate hypotheses for further and more detailed research.

Abstract P5-14-07: Financial toxicity in BRCA1 and BRCA2 carriers: A pilot study

Objective: Financial toxicity (FT), the cumulative financial burden experienced by patients due to medical care, is a well-established phenomenon. BRCA mutation carriers have increased cancer risk, require frequent screening, and often undergo prophylactic surgery, all risk factors for FT. Our primary aim in this study was to describe rates of FT among BRCA carriers. Methods: We performed a novel, cross-sectional study of FT in patients with BRCA1/2 mutations. Patients were recruited via phone and/or email; patients who agreed to participate completed consents and surveys on RedCap. The COST tool, a validated measure, was used for assessment of FT; scores were divided into tertiles, with high FT defined as COST score ≤ 24. Results: 265 BRCA positive female patients met enrollment criteria; 76 (28.7%) had responded at time of this analysis. Respondents were primarily non-Hispanic White (97.4%), privately insured (82.9%), employed full time (67.1%) with an annual income of $50,000-$99,000 (40.8%) and a mean age of 46.4 years. Fifty-nine patients (77.6%) reported undergoing prophylactic surgery related to their BRCA status. On chart review, 26 patients (34.2% of all respondents) had a confirmed prophylactic mastectomy and 44 patients (57.9%) had a confirmed bilateral salpingo-oophorectomy, with some patients undergoing both procedures. Cost concerns were widespread among respondents; 22.7% of participants reported delaying or avoiding care secondary to finances. Fifty-eight percent of patients wanted to know about the out-of-pocket costs of treatments before receiving them, but only 7.7% reported that costs were discussed. No statistically significant association was seen amongst the high FT and low/medium FT groups re: annual income, insurance type, marital status, or race. Patients with high FT were more likely to engage in all cost-saving measures, with a striking 41.7% of patients reporting delays/avoidance of care due to cost (p=0.02). High FT patients also were more likely to borrow money (16.7%, p=0.01), use savings for care (54.2%, p=0.04), and reduce spending on both necessities (37.5%, p=0.03) and leisure activities (58.3%, p=0.01). Conclusion: This study of financial toxicity in BRCA carriers shows that many patients desire information about the costs of their care and that financial toxicity is an existing issue in this unique patient population. This work serves as the first description of FT in BRCA carriers and supports efforts to incorporate routine counseling on cost in the clinical care of these high-risk patients.

Citation Format: Ellie M Proussaloglou, Alex Rosenthal, Christina Raker, Jennifer Scalia Wilbur, Katrin E Eurich, Ashley Stuckey, Katina Robison. Financial toxicity in BRCA1 and BRCA2 carriers: A pilot study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-14-07.

Differentiating between drug-sensitive and drug-resistant tuberculosis with machine learning for clinical and radiological features

Background

Tuberculosis (TB) drug resistance is a worldwide public health problem that threatens progress made in TB care and control. Early detection of drug resistance is important for disease control, with discrimination between drug-resistant TB (DR-TB) and drug-sensitive TB (DS-TB) still being an open problem. The objective of this work is to investigate the relevance of readily available clinical data and data derived from chest X-rays (CXRs) in DR-TB prediction and to investigate the possibility of applying machine learning techniques to selected clinical and radiological features for discrimination between DR-TB and DS-TB. We hypothesize that the number of sextants affected by abnormalities such as nodule, cavity, collapse and infiltrate may serve as a radiological feature for DR-TB identification, and that both clinical and radiological features are important factors for machine classification of DR-TB and DS-TB.

Methods

We use data from the NIAID TB Portals program (https://tbportals.niaid.nih.gov), 1,455 DR-TB cases and 782 DS-TB cases from 11 countries. We first select three clinical features and 26 radiological features from the dataset. Then, we perform Pearson's chi-squared test to analyze the significance of the selected clinical and radiological features. Finally, we train machine classifiers based on different features and evaluate their ability to differentiate between DR-TB and DS-TB.

Results

Pearson's chi-squared test shows that two clinical features and 23 radiological features are statistically significant regarding DR-TB vs. DS-TB. A ten-fold cross-validation using a support vector machine shows that automatic discrimination between DR-TB and DS-TB achieves an average accuracy of 72.34% and an average AUC value of 78.42%, when combing all 25 statistically significant features.

Conclusions

Our study suggests that the number of affected lung sextants can be used for predicting DR-TB, and that automatic discrimination between DR-TB and DS-TB is possible, with a combination of clinical features and radiological features providing the best performance.

Advancing TB research using digitized programmatic data

The use of real-world data from national TB care programs has great potential to answer key research questions in TB control and is now opportune due to increasing digital data collection and storage. We summarize an expert stakeholder workshop conducted on this topic in October 2019, with perspectives from academics, national TB program officers, and data managers. We discuss challenges and opportunities in the use of TB programmatic data for research and describe digital data availability in two large, high TB burden countries, Brazil and South Africa. From this, we posit that with a standardized data collection set, improved data management, and greater collaboration, more TB programmatic data can be used for research with measurable public health impact.

POS1124 IDENTIFYING POTENTIAL CLASSIFICATION CRITERIA FOR CALCIUM PYROPHOSPHATE DEPOSITION DISEASE (CPPD): RESULTS FROM THE INITIAL PHASES

Background:

Classification criteria for calcium pyrophosphate deposition disease (CPPD) will facilitate clinical research on this common crystalline arthritis. ACR/EULAR are jointly sponsoring development of CPPD classification criteria using a multi-phase process.

Objectives:

To report preliminary results from the first two phases of a four-phase process for developing CPPD classification criteria.

Methods:

CPPD classification criteria development is overseen by a 12-member Steering Committee. Item generation (Phase I) included a scoping literature review of five literature databases and contributions from a 35-member Combined Expert Committee and two Patient Research Partners. Item reduction and refinement (Phase II) involved a Combined Expert Committee meeting, discussions among Clinical, Imaging, and Laboratory Advisory Groups, and an item rating exercise to assess the influence of individual items toward classification. The Steering Committee reviewed the modal rating score for each item (range -3 [strongly pushes away from CPPD] to +3 [strongly pushes toward CPPD]) to determine items to retain for future phases of criteria development.

Results:

Item generation yielded 420 items (312 from the literature, 108 from experts/patients). The Advisory Groups eliminated items they agreed were unlikely to distinguish between CPPD and other forms of arthritis, yielding 127 items for the item rating exercise. Fifty-six items, most of which had a modal rating of +/- 2 or 3, were retained for future phases (see Table 1). As numerous imaging items were rated +3, the Steering Committee recommended focusing on imaging of the knee, wrist, and one additional affected joint for calcification suggestive of CPP crystal deposition.

Conclusion:

The ACR/EULAR CPPD classification criteria working group has adopted both data- and expert-driven approaches, leading to 56 candidate items broadly categorized as clinical, imaging, and laboratory features. Remaining steps for criteria development include domain establishment, item weighting through a multi-criteria decision analysis exercise, threshold score determination, and criteria validation.

Table 1.

Categories of items retained for future phases of classification criteria development

Age in decade at symptom onsetAcute inflammatory arthritis (e.g. knee, wrist, 1st MTP joint*)Recurrence and pattern of joint involvement (e.g. 1 self-limited episode, >1 self-limited episode)Physical findings (e.g. palpable subcutaneous tophus*, psoriasis*)Co-morbidities and family history (e.g. Gitelman disease, hemochromatosis, familial CPPD)Osteoarthritis location and features (e.g. 2nd or 3rd MCP joint, wrist)Synovial fluid findings (e.g. CPP crystals present, CPP crystals absent on 1 occasion* or 2 occasions*, monosodium urate crystals present*)Laboratory findings (e.g. hypomagnesemia, hyperparathyroidism, rheumatoid factor*, anti-CCP*)Plain radiograph: calcification in regions of fibro- or hyaline cartilage+Plain radiograph: calcification of the synovial membrane/capsule/tendon+Conventional CT: calcification in regions of fibro- or hyaline cartilage+Conventional CT: calcification of the synovial membrane/capsule/tendon+Ultrasound: CPP crystal deposition in fibro- or hyaline cartilage+Ultrasound: CPP crystal deposition in synovial membrane/capsule/tendons+Dual-energy CT: CPP crystal deposition in fibro- or hyaline cartilage+Dual-energy CT: CPP crystal deposition in synovial membrane/capsule/tendon+

*Potential negative predictor +Assessed in the knee, wrist, and/or 1 additional affected joint

Disclosure of Interests:

Sara Tedeschi Consultant of: NGM Biopharmaceuticals, Tristan Pascart: None declared, Augustin Latourte Consultant of: Novartis, Cattleya Godsave: None declared, Burak Kundaki: None declared, Raymond Naden: None declared, William Taylor: None declared, Nicola Dalbeth Speakers bureau: Abbvie and Janssen, Consultant of: AstraZeneca, Dyve, Selecta, Horizon, Arthrosi, and Cello Health, Tuhina Neogi: None declared, Fernando Perez-Ruiz: None declared, Ann Rosenthal: None declared, Fabio Becce Consultant of: Horizon Therapeutics, Grant/research support from: Siemens Healthineers, Eliseo Pascual: None declared, Mariano Andrés: None declared, Thomas Bardin: None declared, Michael Doherty: None declared, Hang Korng Ea: None declared, Georgios Filippou: None declared, John FitzGerald: None declared, Marwin Gutierrez: None declared, Annamaria Iagnocco: None declared, Tim Jansen Speakers bureau: Abbvie, Amgen, BMS, Grunenthal, Olatec, Sanofi Genzyme, Consultant of: Abbvie, Amgen, BMS, Grunenthal, Olatec, Sanofi Genzyme, Minna Kohler Speakers bureau: Lilly, Consultant of: Novartis, Frederic Lioté: None declared, Mark Matza: None declared, Geraldine McCarthy Consultant of: PK Med, Roberta Ramonda: None declared, Anthony Reginato: None declared, Pascal Richette: None declared, Jasvinder Singh Speakers bureau: Simply Speaking, Consultant of: Crealta/Horizon, Medisys, Fidia, UBM LLC, Trio health, Medscape, WebMD, Adept Field Solutions, Clinical Care options, Clearview healthcare partners, Putnam associates, Focus forward, Navigant consulting, Spherix, Practice Point communications, Francisca Sivera: None declared, Alexander So: None declared, Lisa Stamp: None declared, Janeth Yinh: None declared, Chio Yokose: None declared, Robert Terkeltaub Consultant of: Sobi, Horizon Therapeutics, Astra-Zeneca, Selecta, Grant/research support from: Astra-Zeneca, Hyon Choi: None declared, Abhishek Abhishek Consultant of: NGM Biopharmaceuticals.

Genomic analyses of Mycobacterium tuberculosis from human lung resections reveal a high frequency of polyclonal infections

Polyclonal infections occur when at least two unrelated strains of the same pathogen are detected in an individual. This has been linked to worse clinical outcomes in tuberculosis, as undetected strains with different antibiotic resistance profiles can lead to treatment failure. Here, we examine the amount of polyclonal infections in sputum and surgical resections from patients with tuberculosis in the country of Georgia. For this purpose, we sequence and analyse the genomes of Mycobacterium tuberculosis isolated from the samples, acquired through an observational clinical study (NCT02715271). Access to the lung enhanced the detection of multiple strains (40% of surgery cases) as opposed to just using a sputum sample (0-5% in the general population). We show that polyclonal infections often involve genetically distant strains and can be associated with reversion of the patient's drug susceptibility profile over time. In addition, we find different patterns of genetic diversity within lesions and across patients, including mutational signatures known to be associated with oxidative damage; this suggests that reactive oxygen species may be acting as a selective pressure in the granuloma environment. Our results support the idea that the magnitude of polyclonal infections in high-burden tuberculosis settings is underestimated when only testing sputum samples.

Radiologist observations of computed tomography (CT) images predict treatment outcome in TB Portals, a real-world database of tuberculosis (TB) cases

The TB Portals program provides a publicly accessible repository of TB case data containing multi-modal information such as case clinical characteristics, pathogen genomics, and radiomics. The real-world resource contains over 3400 TB cases, primarily drug resistant cases, and CT images with radiologist annotations are available for many of these cases. The breadth of data collected offers a patient-centric view into the etiology of the disease including the temporal context of the available imaging information. Here, we analyze a cohort of new TB cases with available radiologist observations of CTs taken around the time of initial registration of the case into the database and with available follow up to treatment outcome of cured or died. Follow up ranged from 5 weeks to a little over 2 years consistent with the longest treatment regimens for drug resistant TB and cases were registered within the years 2008 to 2019. The radiologist observations were incorporated into machine learning pipelines to test various class balancing strategies on the performance of predictive models. The modeling results support that the radiologist observations are predictive of treatment outcome. Moreover, inferential statistical analysis identifies markers of TB disease spread as having an association with poor treatment outcome including presence of radiologist observations in both lungs, swollen lymph nodes, multiple cavities, and large cavities. While the initial results are promising, further data collection is needed to incorporate methods to mitigate potential confounding such as including additional model covariates or matching cohorts on covariates of interest (e.g. demographics, BMI, comorbidity, TB subtype, etc.). Nonetheless, the preliminary results highlight the utility of the resource for hypothesis generation and exploration of potential biomarkers of TB disease severity and support these additional data collection efforts.

DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics

The Database of Antimicrobial Activity and Structure of Peptides (DBAASP) is an open-access, comprehensive database containing information on amino acid sequences, chemical modifications, 3D structures, bioactivities and toxicities of peptides that possess antimicrobial properties. DBAASP is updated continuously, and at present, version 3.0 (DBAASP v3) contains >15 700 entries (8000 more than the previous version), including >14 500 monomers and nearly 400 homo- and hetero-multimers. Of the monomeric antimicrobial peptides (AMPs), >12 000 are synthetic, about 2700 are ribosomally synthesized, and about 170 are non-ribosomally synthesized. Approximately 3/4 of the entries were added after the initial release of the database in 2014 reflecting the recent sharp increase in interest in AMPs. Despite the increased interest, adoption of peptide antimicrobials in clinical practice is still limited as a consequence of several factors including side effects, problems with bioavailability and high production costs. To assist in developing and optimizing de novo peptides with desired biological activities, DBAASP offers several tools including a sophisticated multifactor analysis of relevant physicochemical properties. Furthermore, DBAASP has implemented a structure modelling pipeline that automates the setup, execution and upload of molecular dynamics (MD) simulations of database peptides. At present, >3200 peptides have been populated with MD trajectories and related analyses that are both viewable within the web browser and available for download. More than 400 DBAASP entries also have links to experimentally determined structures in the Protein Data Bank. DBAASP v3 is freely accessible at http://dbaasp.org.

The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration

OBJECTIVE

Clinical research informatics tools are necessary to support comprehensive studies of infectious diseases. The National Institute of Allergy and Infectious Diseases (NIAID) developed the publicly accessible Tuberculosis Data Exploration Portal (TB DEPOT) to address the complex etiology of tuberculosis (TB).

MATERIALS AND METHODS

TB DEPOT displays deidentified patient case data and facilitates analyses across a wide range of clinical, socioeconomic, genomic, and radiological factors. The solution is built using Amazon Web Services cloud-based infrastructure, .NET Core, Angular, Highcharts, R, PLINK, and other custom-developed services. Structured patient data, pathogen genomic variants, and medical images are integrated into the solution to allow seamless filtering across data domains.

RESULTS

Researchers can use TB DEPOT to query TB patient cases, create and save patient cohorts, and execute comparative statistical analyses on demand. The tool supports user-driven data exploration and fulfills the National Institute of Health's Findable, Accessible, Interoperable, and Reusable (FAIR) principles.

DISCUSSION

TB DEPOT is the first tool of its kind in the field of TB research to integrate multidimensional data from TB patient cases. Its scalable and flexible architectural design has accommodated growth in the data, organizations, types of data, feature requests, and usage. Use of client-side technologies over server-side technologies and prioritizing maintenance have been important lessons learned. Future directions are dynamically prioritized and key functionality is shared through an application programming interface.

CONCLUSION

This paper describes the platform development methodology, resulting functionality, benefits, and technical considerations of a clinical research informatics application to support increased understanding of TB.

Pushing the limits of solids retention time for enhanced biological phosphorus removal: process characteristics and Accumulibacter population structure

Reducing the solids retention time (SRT) of the enhanced biological phosphorus removal (EBPR) process can increase organic carbon diversion to the sidestream for energy recovery, thereby realizing some of the benefits of the high rate activated sludge (HRAS) process. Determining the washout (i.e. minimum) SRT of polyphosphate accumulating organisms (PAOs), therefore, allows for simultaneous phosphorus and carbon diversion for energy recovery from EBPR systems. However, few studies have investigated the washout SRT of PAOs in real wastewater, and little is known of the diversity of PAOs in high rate EBPR systems. Here we demonstrate efficient phosphorus removal (83% orthophosphate removal) in a high rate EBPR sequencing batch reactor fed real primary effluent and operated at 20 °C. Stable operation was achieved at a total SRT of 1.8 ± 0.2 days and hydraulic retention time of 3.7-4.8 hours. 16S rRNA gene sequencing data demonstrated that Accumulibacter were the dominant PAO throughout the study, with a washout aerobic SRT between 0.8 and 1.4 days. qPCR targeting the polyphosphate kinase gene revealed that Accumulibacter clades IIA, IIB and IID dominated the PAO community at low SRT operation, while clade IA was washed out at the lowest SRT values.

Assessment of aeration control strategies for biofilm-based partial nitritation/anammox systems

The objective of this work was to compare the nitrogen removal in mainstream, biofilm-based partial nitritation anammox (PN/A) systems employing (1) constant setpoint dissolved oxygen (DO) control, (2) intermittent aeration, and (3) ammonia-based aeration control (ABAC). A detailed water resource recovery facility (WRRF) model was used to study the dynamic performance of these aeration control strategies with respect to treatment performance and energy consumption. The results show that constant setpoint DO control cannot meet typical regulatory limits for total ammonia nitrogen (NH_x-N). Intermittent aeration shows improvement but requires optimisation of the aeration cycle. ABAC shows the best treatment performance with the advantages of continuous operation and over 20% lower average energy consumption as compared to intermittent aeration.

Performance of Qure.ai automatic classifiers against a large annotated database of patients with diverse forms of tuberculosis

Availability of trained radiologists for fast processing of CXRs in regions burdened with tuberculosis always has been a challenge, affecting both timely diagnosis and patient monitoring. The paucity of annotated images of lungs of TB patients hampers attempts to apply data-oriented algorithms for research and clinical practices. The TB Portals Program database (TBPP, https://TBPortals.niaid.nih.gov) is a global collaboration curating a large collection of the most dangerous, hard-to-cure drug-resistant tuberculosis (DR-TB) patient cases. TBPP, with 1,179 (83%) DR-TB patient cases, is a unique collection that is well positioned as a testing ground for deep learning classifiers. As of January 2019, the TBPP database contains 1,538 CXRs, of which 346 (22.5%) are annotated by a radiologist and 104 (6.7%) by a pulmonologist–leaving 1,088 (70.7%) CXRs without annotations. The Qure.ai qXR artificial intelligence automated CXR interpretation tool, was blind-tested on the 346 radiologist-annotated CXRs from the TBPP database. Qure.ai qXR CXR predictions for cavity, nodule, pleural effusion, hilar lymphadenopathy was successfully matching human expert annotations. In addition, we tested the 12 Qure.ai classifiers to find whether they correlate with treatment success (information provided by treating physicians). Ten descriptors were found as significant: abnormal CXR (p = 0.0005), pleural effusion (p = 0.048), nodule (p = 0.0004), hilar lymphadenopathy (p = 0.0038), cavity (p = 0.0002), opacity (p = 0.0006), atelectasis (p = 0.0074), consolidation (p = 0.0004), indicator of TB disease (p = < .0001), and fibrosis (p = < .0001). We conclude that applying fully automated Qure.ai CXR analysis tool is useful for fast, accurate, uniform, large-scale CXR annotation assistance, as it performed well even for DR-TB cases that were not used for initial training. Testing artificial intelligence algorithms (encapsulating both machine learning and deep learning classifiers) on diverse data collections, such as TBPP, is critically important toward progressing to clinically adopted automatic assistants for medical data analysis.

A retrospective genomic analysis of drug-resistant strains of M. tuberculosis in a high-burden setting, with an emphasis on comparative diagnostics and reactivation and reinfection status

Background

Recurrence of drug-resistant tuberculosis (DR-TB) after treatment occurs through relapse of the initial infection or reinfection by a new drug-resistant strain. Outbreaks of DR-TB in high burden regions present unique challenges in determining recurrence status for effective disease management and treatment. In the Republic of Moldova the burden of DR-TB is exceptionally high, with many cases presenting as recurrent.

Methods

We performed a retrospective analysis of Mycobacterium tuberculosis from Moldova to better understand the genomic basis of drug resistance and its effect on the determination of recurrence status in a high DR-burden environment. To do this we analyzed genomes from 278 isolates collected from 189 patients, including 87 patients with longitudinal samples. These pathogen genomes were sequenced using Illumina technology, and SNP panels were generated for each sample for use in phylogenetic and network analysis. Discordance between genomic resistance profiles and clinical drug-resistance test results was examined in detail to assess the possibility of mixed infection.

Results

There were clusters of multiple patients with 10 or fewer differences among DR-TB samples, which is evidence of person-to-person transmission of DR-TB. Analysis of longitudinally collected isolates revealed that many infections exhibited little change over time, though 35 patients demonstrated reinfection by divergent (number of differences > 10) lineages. Additionally, several same-lineage sample pairs were found to be more divergent than expected for a relapsed infection. Network analysis of the H3/4.2.1 clade found very close relationships among 61 of these samples, making differentiation of reactivation and reinfection difficult. There was discordance between genomic profile and clinical drug sensitivity test results in twelve samples, and four of these had low level (but not statistically significant) variation at DR SNPs suggesting low-level mixed infections.

Conclusions

Whole-genome sequencing provided a detailed view of the genealogical structure of the DR-TB epidemic in Moldova, showing that reinfection may be more prevalent than currently recognized. We also found increased evidence of mixed infection, which could be more robustly characterized with deeper levels of genomic sequencing.

425. Longitudinal Trends in Risk Behaviors and Sexually Transmitted Diseases among Adolescents and Young Adults at a Sexually Transmitted Diseases Clinic, 2013–2017

Background

Sexually transmitted disease (STD) rates continue to rise in the United States (US). Over half of all new STDs occur in adolescents and young adults (AYA). Few studies have evaluated how sexual behaviors such as number of partners or condom use may contribute to this increase. We aimed to determine the association of sexual behaviors and condom use with STD incidence over time among AYA.

Methods

We reviewed all AYA ages 13–26 years attending a public STD clinic in Rhode Island from 2013–2017. We reviewed demographic and behavioral data including age, gender identity, risk group, race, ethnicity, insurance status, sexual behaviors, substance use, self-reported STD/HIV diagnosis (lifetime, past year), condom use, and HIV/STD testing results. We report proportions in 2013 and 2017, and performed trend analyses (Cocharn-Armitage test for categorical variables and Kruskal–Wallis trend test for continuous variables) to determine trends over time.

Results

A total of 3,822 AYA visited the clinic during the study time period. An increasing trend was observed for: multiple (≥5) partners (29% of AYA in 2013 vs. 38% in 2017, P < 0.001), self-reported past year and lifetime STD diagnosis (12 vs. 21%, P < 0.001 and 19 vs. 33%, P < 0.001, respectively), and lab-documented diagnosis of any STD (15 vs. 25%, P < 0.001), syphilis (2 vs. 5%, P = 0.006), any chlamydia (11 vs. 20%, P = 0.001), and any gonorrhea (3 vs. 8%, P = 0.008). A decreasing trend was observed for: white race (66% in 2013 vs. 43% in 2017, P < 0.001), uninsured (73 vs. 53%, P < 0.001), condomless sex during oral as well as vaginal/anal sex (22 vs. 10%, P = 0.001 and 16 vs. 8%, P = 0.001, respectively), and self-reported HIV diagnosis (2.5% to 0.9%, P = 0.016).

Conclusion

Among AYA, risk behaviors such as condomless sex and multiple partners increased significantly from 2013–2017, which may be contributing to an increase in STDs. Increased public health efforts are needed to promote education and other interventions to address behaviors associated with STD transmission.

Disclosures

All authors: No reported disclosures.

Towards mechanical characterization of granular biofilms by optical coherence elastography measurements of circumferential elastic waves

Microbial granular biofilms are spherical, multi-layered aggregates composed of communities of bacterial cells encased in a complex matrix of hydrated extracellular polymeric substances (EPS). While granular aggregates are increasingly used for applications in industrial and municipal wastewater treatment, their underlying mechanical properties are poorly understood. The challenges of viscoelastic characterization for these structures are due to their spherical geometry, spatially heterogeneous properties, and their delicate nature. In this study, we report a model-based approach for nondestructive characterization of viscoelastic properties (shear modulus and shear viscosity) of alginate spheres with different concentrations, which was motivated by our measurements in granular biofilms. The characterization technique relies on experimental measurements of circumferential elastic wave speeds as a function of frequency in the samples using the Optical Coherence Elastography (OCE) technique. A theoretical model was developed to estimate the viscoelastic properties of the samples from OCE data through inverse analysis. This work represents the first attempt to explore elastic waves for mechanical characterization of granular biofilms. The combination of the OCE technique and the theoretical model presented in this paper provides a framework that can facilitate quantitative viscoelastic characterization of samples with curved geometries and the study of the relationships between morphology and mechanical properties in granular biofilms.

Genome-Wide Analysis of MDR and XDR Tuberculosis from Belarus: Machine-Learning Approach

Emergence of drug-resistant microorganisms has been recognized as a serious threat to public health worldwide. This problem is extensively discussed in the context of tuberculosis treatment. Alterations in pathogen genomes are among the main mechanisms by which microorganisms exhibit drug resistance. Analysis of 144 M. tuberculosis strains of different phenotypes including drug susceptible, MDR, and XDR isolated in Belarus was fulfilled in this paper. A wide range of machine learning methods that can discover SNPs related to drug-resistance in the whole bacteria genomes was investigated. Besides single-SNP testing approaches, methods that allow detecting joint effects from interacting SNPs were considered. We proposed a framework for automated selection of the best performing statistical model in terms of recall, precision, and accuracy to identify drug resistance-associated mutations. Analysis of whole-genome sequences often leads to situations where the number of treated features exceeds the number of available observations. For this reason, special attention is paid to fair evaluation of the model prediction quality and minimizing the risk of overfitting while estimating the underlying parameters. Results of our experiments aimed at identifying top-scoring resistance mutations to the major first-line and second-line anti-TB drugs are presented.

Updates on 18F-FDG-PET/CT as a clinical tool for tuberculosis evaluation and therapeutic monitoring

Tuberculosis (TB) is currently the world's leading cause of infectious mortality. The complex immune response of the human body to Mycobacterium tuberculosis (M.tb) results in a wide array of clinical manifestations, thus the clinical and radiological diagnosis can be challenging. ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG-PET) scan with/without computed tomography (CT) component images the whole body and provides a metabolic map of the infection, enabling clinicians to assess the disease burden. ¹⁸F-FDG-PET/CT scan is particularly useful in detecting the disease in previously unknown sites, and allows the most appropriate site of biopsy to be selected. ¹⁸F-FDG-PET/CT is also very valuable in assessing early disease response to therapy, and plays an important role in cases where conventional microbiological methods are unavailable and for monitoring response to therapy in cases of multidrug-resistant TB or extrapulmonary TB. ¹⁸F-FDG-PET/CT cannot reliably differentiate active TB lesion from malignant lesions and false positives can also be due to other infective or inflammatory conditions. ¹⁸F-FDG PET is also unable to distinguish tuberculous lymphadenitis from metastatic lymph node involvement. The lack of specificity is a limitation for ¹⁸F-FDG-PET/CT in TB management.

TB DEPOT (Data Exploration Portal): A multi-domain tuberculosis data analysis resource

The NIAID TB Portals Program (TBPP) established a unique and growing database repository of socioeconomic, geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis (DR-TB). Currently, there are 2,428 total cases from nine country sites (Azerbaijan, Belarus, Moldova, Georgia, Romania, China, India, Kazakhstan, and South Africa), 1,611 (66%) of which are multidrug- or extensively-drug resistant and 1,185 (49%), 863 (36%), and 952 (39%) of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. We introduce the Data Exploration Portal (TB DEPOT, https://depot.tbportals.niaid.nih.gov) to visualize and analyze these multi-domain data. The TB DEPOT leverages the TBPP integration of clinical, socioeconomic, genomic, and imaging data into standardized formats and enables user-driven, repeatable, and reproducible analyses. It furthers the TBPP goals to provide a web-enabled analytics platform to countries with a high burden of multidrug-resistant TB (MDR-TB) but limited IT resources and inaccessible data, and enables the reusability of data, in conformity with the NIH's Findable, Accessible, Interoperable, and Reusable (FAIR) principles. TB DEPOT provides access to "analysis-ready" data and the ability to generate and test complex clinically-oriented hypotheses instantaneously with minimal statistical background and data processing skills. TB DEPOT is also promising for enhancing medical training and furnishing well annotated, hard to find, MDR-TB patient cases. TB DEPOT, as part of TBPP, further fosters collaborative research efforts to better understand drug-resistant tuberculosis and aid in the development of novel diagnostics and personalized treatment regimens.

Biomass segregation between biofilm and flocs improves the control of nitrite-oxidizing bacteria in mainstream partial nitritation and anammox processes

The control of nitrite-oxidizing bacteria (NOB) challenges the implementation of partial nitritation and anammox (PN/A) processes under mainstream conditions. The aim of the present study was to understand how operating conditions impact microbial competition and the control of NOB in hybrid PN/A systems, where biofilm and flocs coexist. A hybrid PN/A moving-bed biofilm reactor (MBBR; also referred to as integrated fixed film activated sludge or IFAS) was operated at 15 °C on aerobically pre-treated municipal wastewater (23 mg_NH4-N L^-1). Ammonium-oxidizing bacteria (AOB) and NOB were enriched primarily in the flocs, and anammox bacteria (AMX) in the biofilm. After decreasing the dissolved oxygen concentration (DO) from 1.2 to 0.17 mg_O2 L^-1 - with all other operating conditions unchanged - washout of NOB from the flocs was observed. The activity of the minor NOB fraction remaining in the biofilm was suppressed at low DO. As a result, low effluent NO₃^- concentrations (0.5 mg_N L^-1) were consistently achieved at aerobic nitrogen removal rates (80 mg_N L^-1 d^-1) comparable to those of conventional treatment plants. A simple dynamic mathematical model, assuming perfect biomass segregation with AOB and NOB in the flocs and AMX in the biofilm, was able to qualitatively reproduce the selective washout of NOB from the flocs in response to the decrease in DO-setpoint. Similarly, numerical simulations indicated that flocs removal is an effective operational strategy to achieve the selective washout of NOB. The direct competition for NO₂^- between NOB and AMX - the latter retained in the biofilm and acting as a "NO₂-sink" - was identified by the model as key mechanism leading to a difference in the actual growth rates of AOB and NOB (i.e., μ_NOB < μ_AOB in flocs) and allowing for the selective NOB washout over a broad range of simulated sludge retention times (SRT = 6.8-24.5 d). Experimental results and model predictions demonstrate the increased operational flexibility, in terms of variables that can be easily controlled by operators, offered by hybrid systems as compared to solely biofilm systems for the control of NOB in mainstream PN/A applications.

Skin cancer prevention: a review of current topical options complementary to sunscreens

The incidence of non-melanoma skin cancer (NMSC) is dramatically increasing worldwide, despite the increased use of improved sunscreens. In 2014, the Surgeon General estimated that 2.2-5.0 million people were treated annually for NMSC. As the number of newly diagnosed skin cancers continues to rise, there is a need for additional preventative measures beyond sunscreens. Several newer topical products that focus on boosting DNA repair, modulating DNA transcription, decreasing inflammation and selectively targeting precancerous cells may play an important role in future skin cancer prevention.