Genetic diversity within diagnostic sputum samples is mirrored in the culture of Mycobacterium tuberculosis across different settings.

Culturing and genomic sequencing of Mycobacterium tuberculosis (MTB) from tuberculosis (TB) cases is the basis for many research and clinical applications. The alternative, culture-free sequencing from diagnostic samples, is promising but poses challenges to obtain and analyse the MTB genome. Paradoxically, culture is assumed to impose a diversity bottleneck, which, if true, would entail unexplored consequences. To unravel this paradox we generate high-quality genomes of sputum-culture pairs from two different settings after developing a workflow for sequencing from sputum and a tailored bioinformatics analysis. Careful downstream comparisons reveal sources of sputum-culture incongruences due to false positive/negative variation associated with factors like low input MTB DNA or variable genomic depths. After accounting for these factors, contrary to the bottleneck dogma, we identify a 97% variant agreement within sputum-culture pairs, with a high correlation also in the variants' frequency (0.98). The combined analysis from five different settings and more than 100 available samples shows that our results can be extrapolated to different TB epidemic scenarios, demonstrating that for the cases tested culture accurately mirrors clinical samples.

Percent of lung involved in disease on chest X-ray predicts unfavorable treatment outcome in pulmonary tuberculosis.

Radiology may better define tuberculosis (TB) severity and guide duration of treatment. We aimed to systematically study baseline chest X-rays (CXR) and their association with TB treatment outcome using real-world data. We used logistic regression to associate TB treatment outcomes with CXR findings, including percent of lung involved in disease (PLI), cavitation, and Timika score, alone or in combination with other clinical characteristics, stratifying by drug resistance status and HIV (n = 2,809). We fine-tuned convolutional neural nets (CNN) to automate PLI measurement from the CXR DICOM images (n = 5,261). PLI is the only CXR finding associated with unfavorable outcome across drug resistance and HIV subgroups [Rifampicin-susceptible disease without HIV, adjusted odds ratio (aOR) 1·11 (1·01, 1·22), P-value 0·025]. The most informed model of baseline characteristics tested predicts outcome with a validation mean area under the curve (AUC) of 0·769. PLI and Timika (AUC 0·656 and 0·655 respectively) predict unfavorable outcomes better than cavitary information (best AUC 0·591). The addition of PLI improves prediction compared to sex and age alone (AUC 0·680 and 0·627, respectively).PLI>25% provides a better separation of favorable and unfavorable outcomes compared to PLI>50%. The best performing ensemble of CNNs has an AUC 0·850 for PLI>25% and mean absolute error of 11·7% for the PLI value. PLI is better than cavitation for predicting unfavorable treatment outcome in pulmonary TB in non-clinical trial settings and it can be accurately and automatically predicted with CNNs. One Sentence Summary: The percent of lung involved in disease improves prediction of unfavorable outcomes in pulmonary tuberculosis when added to clinical characteristics.

Timing of Trial of Void After Radical Hysterectomy: Long-Term Urinary Outcomes at Two Academic Tertiary Care Institutions.

INTRODUCTION AND HYPOTHESIS: Many patients develop bladder symptoms after radical hysterectomy. This study compared urinary outcomes following radical hysterectomy based on trial of void (TOV) timing (pre-discharge TOV versus post-discharge TOV). METHODS: A retrospective non-inferiority study of patients at two academic tertiary referral centers who underwent radical hysterectomy between January 2010 and January 2020 was carried out. Patients were stratified according to timing of postoperative TOV: either pre-discharge or post-discharge from the hospital. Short-term urinary outcomes (including passing TOV, representation with retention) and long-term de novo urinary dysfunction (defined as irritative voiding symptoms, urgency, frequency, nocturia, stress or urgency incontinence, neurogenic bladder, and/or urinary retention) were extracted from the medical record. We hypothesized that the proportion of patients who failed pre-discharge TOV would be within a 15% non-inferiority margin of post-discharge TOV. RESULTS: A total of 198 patients underwent radical hysterectomy for cervical (118 out of 198; 59.6%), uterine (36 out of 198; 18.2%), and ovarian (29 out of 198; 14.6%) cancer. One hundred and nineteen patients (119 out of 198, 60.1%) underwent pre-discharge TOV, of whom 14 out of 119 (11.8%) failed. Of the post-discharge TOV patients (79 out of 198, 39.9%), 5 out of 79 (6.3%) failed. The proportion of patients who failed a pre-discharge TOV was within the non-inferiority margin (5.4% difference, p = 0.23). A greater proportion of patients in the post-discharge TOV group developed long-term de novo urinary dysfunction (27.2% difference, p = 0.005). Median time to diagnosis of de novo urinary dysfunction was 0.5 years (range 0-9) in the pre-discharge TOV group versus 1.0 year (range 0-6) in the post-discharge TOV group (p > 0.05). CONCLUSIONS: In this study, pre-discharge TOV had non-inferior short-term outcomes and improved long-term outcomes.

Using publicly available, interactive epidemiological dashboards: an innovative approach to sharing data from the Rakai Community Cohort Study.

Objectives: Public sharing of de-identified biomedical data promotes collaboration between researchers and accelerates the development of disease prevention and treatment strategies. However, open-access data sharing presents challenges to researchers who need to protect the privacy of study participants, ensure that data are used appropriately, and acknowledge the inputs of all involved researchers. This article presents an approach to data sharing which addresses the above challenges by using a publicly available dashboard with de-identified, aggregated participant data from a large HIV surveillance cohort. Materials and Methods: Data in this study originated from the Rakai Community Cohort Study (RCCS), which was integrated into a centralized data mart as part of a larger data management strategy for the Rakai Health Sciences Program in Uganda. These data were used to build a publicly available, protected health information (PHI)-secured visualization dashboard for general research use. Results: Using two unique case studies, we demonstrate the capability of the dashboard to generate the following hypotheses: firstly, that HIV prevention strategies ART and circumcision have differing levels of impact depending on the marital status of investigated communities; secondly, that ART is very successful in comparison to circumcision as an interventional strategy in certain communities. Discussion: The democratization of large-scale anonymized epidemiological data using public-facing dashboards has multiple benefits, including facilitated exploration of research data and increased reproducibility of research findings. Conclusion: By allowing the public to explore data in depth and form new hypotheses, public-facing dashboard platforms have significant potential to generate new relationships and collaborations and further scientific discovery and reproducibility.

Left-Handed Palming of the Needle Driver: A Technical Report for Surgical Trainees.

Left-handed surgical trainees are uniquely challenged when learning how to suture using standard needle drivers designed for right-handed individuals and often feel disadvantaged in comparison to their right-handed peers. "Palming," a suturing technique that improves suturing mechanics and efficiency, cannot be achieved in the standard manner using the left hand. This paper proposes a previously undescribed technique for palming using the left hand that provides many of the same benefits as standard palming methods using the right hand, potentially reducing a common source of inequity in surgical training.

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 1.67kgm2. 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.

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.

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.

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).

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.

Analysis, Modeling, and Target-Specific Predictions of Linear Peptides Inhibiting Virus Entry.

Antiviral peptides (AVPs) are bioactive peptides that exhibit the inhibitory activity against viruses through a range of mechanisms. Virus entry inhibitory peptides (VEIPs) make up a specific class of AVPs that can prevent envelope viruses from entering cells. With the growing number of experimentally verified VEIPs, there is an opportunity to use machine learning to predict peptides that inhibit the virus entry. In this paper, we have developed the first target-specific prediction model for the identification of new VEIPs using, along with the peptide sequence characteristics, the attributes of the envelope proteins of the target virus, which overcomes the problem of insufficient data for particular viral strains and improves the predictive ability. The model's performance was evaluated through 10 repeats of 10-fold cross-validation on the training data set, and the results indicate that it can predict VEIPs with 87.33% accuracy and Matthews correlation coefficient (MCC) value of 0.76. The model also performs well on an independent test set with 90.91% accuracy and MCC of 0.81. We have also developed an automatic computational tool that predicts VEIPs, which is freely available at https://dbaasp.org/tools?page=linear-amp-prediction.

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.

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.

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.

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.

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.

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.

Partial Nitritation/Anammox and biological phosphorus removal integration in a single bioreactor under mainstream conditions.

Anammox-based nitrogen removal and enhanced biological phosphorus removal (EBPR) are increasingly applied for nutrient removal from wastewater, but are typically operated in separate reactors. Here, a novel process for integrated partial nitritation/anammox (PN/A) and EBPR in a single reactor employing integrated fixed film activated sludge was tested. The reactor was fed with mainstream municipal wastewater (5.4 ± 1.3 g COD/g N) at 20 °C for 243 days. Robust ammonium, total inorganic nitrogen, and orthophosphate removal efficiencies of 94 ± 4 %, 87 ± 7 % and 92 ± 7 % were achieved. Nitrite-oxidizing organisms suppression and ammonia-oxidizing organisms retention were achieved via solids retention time control, intermittent aeration, and suspended versus attached biomass population segregation. The contribution of anammox to nitrogen removal increased from 24 % to 74 %. In parallel, a substantial enrichment of Tetrasphaera polyphosphate accumulating organisms was observed. This work demonstrates a novel intensified bioprocess coupling PN/A and EBPR in the same reactor for efficient nutrient removal from wastewater.