Rare SNP in the HELB gene interferes with RPA interaction and cellular function of HELB.

HELB is a human helicase involved in initiation of DNA replication, the replication stress response, and regulation of double-strand DNA break repair. rs75770066 is a rare SNP in the HELB gene that affects age at natural menopause. rs75770066 results in a D506G substitution in an acidic patch within the 1A domain of the helicase that is known to interact with RPA. We found that this amino acid change dramatically impairs the cellular function of HELB. D506G-HELB exhibits impaired interaction with RPA, which likely results in the effects of rs75770066 as this reduces recruitment of HELB to sites of DNA damage. Reduced recruitment of D506G-HELB to double-strand DNA breaks and the concomitant increase in homologous recombination likely alters the levels of meiotic recombination, which affects the viability of gametes. Because menopause occurs when oocyte levels drop below a minimum threshold, altered repair of meiotic double-stranded DNA breaks has the potential to directly affect the age at natural menopause.

Thriving In and Out of the Reading Room: A Faculty Development Workshop.

RATIONALE AND OBJECTIVES: Given the immense time and energy radiologists dedicate to their profession, the experience at work should be a major contributor to a meaningful and fulfilling life. In pursuit of this vision, our department launched a novel faculty development workshop entitled "Thriving In and Out of the Reading Room: What They Didn't Teach Us in Training." We report on the design, implementation and initial outcomes of this faculty development workshop. MATERIALS AND METHODS: The workshop drew upon positive psychology research and the PERMA model of well-being, which encompasses five key elements: Positive emotion, Engagement, Relationships, Meaning, and Achievement. These elements have been shown to enhance work satisfaction and foster resilience. Using interactive, small group exercises, the workshop provided strategies for incorporating PERMA elements into daily life. At the conclusion of each workshop, an anonymous voluntary electronic survey was distributed to participants. RESULTS: The final version of the workshop was offered to 58 faculty over eight sessions between September 2022 and May 2023. Survey results indicate that participants found the workshop to be highly valuable and practical. They also found the workshop to promote camaraderie and peer learning. Developing the workshop internally allowed us to customize it to our faculty's unique experiences and engage a large number of participants. CONCLUSION: The workshop shows promise in improving job satisfaction and addressing burnout among academic radiologists.

Using machine learning probabilities to identify effects of COVID-19.

Coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has had extensive economic, social, and public health impacts in the United States and around the world. To date, there have been more than 600 million reported infections worldwide with more than 6 million reported deaths. Retrospective analysis, which identified comorbidities, risk factors, and treatments, has underpinned the response. As the situation transitions to an endemic, retrospective analyses using electronic health records will be important to identify the long-term effects of COVID-19. However, these analyses can be complicated by incomplete records, which makes it difficult to differentiate visits where the patient had COVID-19. To address this issue, we trained a random Forest classifier to assign a probability of a patient having been diagnosed with COVID-19 during each visit. Using these probabilities, we found that higher COVID-19 probabilities were associated with a future diagnosis of myocardial infarction, urinary tract infection, acute renal failure, and type 2 diabetes.

Natural Language Processing Can Automate Extraction of Barrett's Esophagus Endoscopy Quality Metrics.

Objectives: To develop an automated natural language processing (NLP) method for extracting high-fidelity Barrett's Esophagus (BE) endoscopic surveillance and treatment data from the electronic health record (EHR). Methods: Patients who underwent BE-related endoscopies between 2016 and 2020 at a single medical center were randomly assigned to a development or validation set. Those not aged 40 to 80 and those without confirmed BE were excluded. For each patient, free text pathology reports and structured procedure data were obtained. Gastroenterologists assigned ground truth labels. An NLP method leveraging MetaMap Lite generated endoscopy-level diagnosis and treatment data. Performance metrics were assessed for this data. The NLP methodology was then adapted to label key endoscopic eradication therapy (EET)-related endoscopy events and thereby facilitate calculation of patient-level pre-EET diagnosis, endotherapy time, and time to CE-IM. Results: 99 patients (377 endoscopies) and 115 patients (399 endoscopies) were included in the development and validation sets respectively. When assigning high-fidelity labels to the validation set, NLP achieved high performance (recall: 0.976, precision: 0.970, accuracy: 0.985, and F1-score: 0.972). 77 patients initiated EET and underwent 554 endoscopies. Key EET-related clinical event labels had high accuracy (EET start: 0.974, CE-D: 1.00, and CE-IM: 1.00), facilitating extraction of pre-treatment diagnosis, endotherapy time, and time to CE-IM. Conclusions: High-fidelity BE endoscopic surveillance and treatment data can be extracted from routine EHR data using our automated, transparent NLP method. This method produces high-level clinical datasets for clinical research and quality metric assessment.

Breast cancer risk prediction combining a convolutional neural network-based mammographic evaluation with clinical factors.

PURPOSE: Deep learning techniques, including convolutional neural networks (CNN), have the potential to improve breast cancer risk prediction compared to traditional risk models. We assessed whether combining a CNN-based mammographic evaluation with clinical factors in the Breast Cancer Surveillance Consortium (BCSC) model improved risk prediction. METHODS: We conducted a retrospective cohort study among 23,467 women, age 35-74, undergoing screening mammography (2014-2018). We extracted electronic health record (EHR) data on risk factors. We identified 121 women who subsequently developed invasive breast cancer at least 1 year after the baseline mammogram. Mammograms were analyzed with a pixel-wise mammographic evaluation using CNN architecture. We used logistic regression models with breast cancer incidence as the outcome and predictors including clinical factors only (BCSC model) or combined with CNN risk score (hybrid model). We compared model prediction performance via area under the receiver operating characteristics curves (AUCs). RESULTS: Mean age was 55.9 years (SD, 9.5) with 9.3% non-Hispanic Black and 36% Hispanic. Our hybrid model did not significantly improve risk prediction compared to the BCSC model (AUC of 0.654 vs 0.624, respectively, p = 0.063). In subgroup analyses, the hybrid model outperformed the BCSC model among non-Hispanic Blacks (AUC 0.845 vs. 0.589; p = 0.026) and Hispanics (AUC 0.650 vs 0.595; p = 0.049). CONCLUSION: We aimed to develop an efficient breast cancer risk assessment method using CNN risk score and clinical factors from the EHR. With future validation in a larger cohort, our CNN model combined with clinical factors may help predict breast cancer risk in a cohort of racially/ethnically diverse women undergoing screening.

Hysterectomy Trends and Risk of Vaginal Cuff Dehiscence: An Update by Mode of Surgery.

STUDY OBJECTIVE: To analyze hysterectomy trends and vaginal cuff dehiscence (VCD) rates by mode of surgery at a tertiary care medical center and to describe characteristics of VCD cases. DESIGN: Observational retrospective cohort study. SETTING: Large academic hospital and affiliated community hospital. PATIENTS: 4722 patients who underwent hysterectomy at Columbia University Irving Medical Center between January 2010 and August 2021. INTERVENTIONS: Current Procedural Terminology and International Classification of Diseases codes identified hysterectomies and VCD cases. Hysterectomy trends and VCD rates were calculated by mode of surgery. Relative risks of VCD for each mode were compared with total abdominal hysterectomy (TAH). Clinical characteristics of VCDs were reviewed. MEASUREMENTS AND MAIN RESULTS: There were 4059 total hysterectomies. Laparoscopic hysterectomies, including total laparoscopic hysterectomies (TLHs), laparoscopic-assisted vaginal hysterectomies, and robot-assisted TLHs (RA-TLHs), increased from 41.9% in 2010 to 65.9% in 2021 (p <.001). RA-TLH increased from 5.7% in 2010 to 40.2% in 2021. Supracervical hysterectomies followed similar trends and were excluded from VCD analysis. There were 15 VCDs (overall rate 0.37%). VCD was highest after RA-TLH (0.66%), followed by TLH (0.32%) and TAH (0.27%), with no VCDs after laparoscopic-assisted vaginal hysterectomy or total vaginal hysterectomy. Compared with TAH, the relative risk for VCD after RA-TLH was 2.44 (95% confidence interval 0.66-9.00) and after TLH was 1.18 (95% confidence interval 0.24-5.83), which were not statistically significant. The mean time to dehiscence was 39 days (range 8-145 days). The most common trigger event was coitus (41%). CONCLUSION: VCD rates were low (<1%) for all modes of hysterectomy, and rates after robotic and laparoscopic hysterectomy were much lower than previously reported. Although VCD rates trended higher after robotic and laparoscopic hysterectomy compared with abdominal hysterectomy, the difference was not significant. It is difficult to determine whether this finding represents true lack of difference vs a lack of power to detect a significant difference given the rarity of VCD.

Implementation of Systematic Financial Screening in an Outpatient Breast Oncology Setting.

PURPOSE: Implementation of routine financial screening is a critical step toward mitigating financial toxicity. We evaluated the feasibility, sustainability, and acceptability of systematic financial screening in the outpatient breast oncology clinic at a large, urban cancer center. METHODS: We developed and implemented a stakeholder-informed process to systematically screen for financial hardship and worry. A 2-item assessment in English or Spanish was administered to patients through the electronic medical record portal or using paper forms. We evaluated completion rates and mode of completion. Through feedback from patients, clinicians, and staff, we identified strategies to improve completion rates and acceptability. RESULTS: From March, 2021, to February, 2022, 3,500 patients were seen in the breast oncology clinic. Of them, 39% (n = 1,349) responded to the screening items, either by paper or portal, 12% (n = 437) preferred not to answer, and the remaining 49% (n = 1,714) did not have data in their electronic health record, meaning they were not offered screening or did not complete the paper forms. Young adults (18-39 years) were more likely to respond compared with patients 70 years or older (61% v 30%, P < .01). English-preferring patients were more likely to complete the screening compared with those who preferred Spanish (46% v 28%, P < .01). Non-Hispanic White patients were more likely to respond compared with Non-Hispanic Black patients and with Hispanic patients (46% v 39% v 32%, P < .01). Strategies to improve completion rates included partnering with staff to facilitate paper form administration, optimizing patient engagement with the portal, and clearly communicating the purpose of the screening. CONCLUSION: Systematic financial screening is feasible, and electronic data capture facilitates successful implementation. However, inclusive procedures that address language and technology preferences are needed to optimize screening.

Structured deep embedding model to generate composite clinical indices from electronic health records for early detection of pancreatic cancer.

The high-dimensionality, complexity, and irregularity of electronic health records (EHR) data create significant challenges for both simplified and comprehensive health assessments, prohibiting an efficient extraction of actionable insights by clinicians. If we can provide human decision-makers with a simplified set of interpretable composite indices (i.e., combining information about groups of related measures into single representative values), it will facilitate effective clinical decision-making. In this study, we built a structured deep embedding model aimed at reducing the dimensionality of the input variables by grouping related measurements as determined by domain experts (e.g., clinicians). Our results suggest that composite indices representing liver function may consistently be the most important factor in the early detection of pancreatic cancer (PC). We propose our model as a basis for leveraging deep learning toward developing composite indices from EHR for predicting health outcomes, including but not limited to various cancers, with clinically meaningful interpretations.

Association between neighborhood socioeconomic status, built environment and SARS-CoV-2 infection among cancer patients treated at a Tertiary Cancer Center in New York City.

BACKGROUND: Racial and ethnic minority groups experience a disproportionate burden of SARS-CoV-2 illness and studies suggest that cancer patients are at a particular risk for severe SARS-CoV-2 infection. AIMS: The objective of this study was examine the association between neighborhood characteristics and SARS-CoV-2 infection among patients with cancer. METHODS AND RESULTS: We performed a cross-sectional study of New York City residents receiving treatment for cancer at a tertiary cancer center. Patients were linked by their address to data from the US Census Bureau's American Community Survey and to real estate tax data from New York's Department of City Planning. Models were used to both to estimate odds ratios (ORs) per unit increase and to predict probabilities (and 95% CI) of SARS-CoV2 infection. We identified 2350 New York City residents with cancer receiving treatment. Overall, 214 (9.1%) were infected with SARS-CoV-2. In adjusted models, the percentage of Hispanic/Latino population (aOR = 1.01; 95% CI, 1.005-1.02), unemployment rate (aOR = 1.10; 95% CI, 1.05-1.16), poverty rates (aOR = 1.02; 95% CI, 1.0002-1.03), rate of >1 person per room (aOR = 1.04; 95% CI, 1.01-1.07), average household size (aOR = 1.79; 95% CI, 1.23-2.59) and population density (aOR = 1.86; 95% CI, 1.27-2.72) were associated with SARS-CoV-2 infection. CONCLUSION: Among cancer patients in New York City receiving anti-cancer therapy, SARS-CoV-2 infection was associated with neighborhood- and building-level markers of larger household membership, household crowding, and low socioeconomic status. NOVELTY AND IMPACT: We performed a cross-sectional analysis of residents of New York City receiving treatment for cancer in which we linked subjects to census and real estate date. This linkage is a novel way to examine the neighborhood characteristics that influence SARS-COV-2 infection. We found that among patients receiving anti-cancer therapy, SARS-CoV-2 infection was associated with building and neighborhood-level markers of household crowding, larger household membership, and low socioeconomic status. With ongoing surges of SARS-CoV-2 infections, these data may help in the development of interventions to decrease the morbidity and mortality associated with SARS-CoV-2 among cancer patients.

Radiographic features of pneumonitis in patients treated with immunotherapy compared to traditional chemotherapy for non-small cell lung cancer.

BACKGROUND: Pneumonitis has been described as a side effect of immunotherapy as well as traditional chemotherapy. Although immune-related adverse event (IRAE) pneumonitis has been extensively characterized, the relationship between IRAE pneumonitis and pneumonitis secondary to chemotherapy is less clear. Here, we present the first analysis of radiographic features of pneumonitis secondary to immunotherapy compared to chemotherapy. METHODS: Using our radiology records system, we searched chest computed tomography (CT) reports for the term "pneumonitis". We evaluated medical records to establish chronicity of pneumonitis occurring after medication administration and excluded cases where radiation therapy appeared to be the cause of pneumonitis. We also obtained information regarding demographic, clinical, and treatment characteristics for comparison. RESULTS: Patients treated with immunotherapy demonstrated more specific features of pneumonitis including consolidation, ground glass opacities, septal thickening, traction bronchiectasis, and pulmonary nodules compared to those treated with chemotherapy. Immunotherapy treatment correlated with the development of pulmonary nodules (p = 0.048), and administration of more than one immunotherapy agent correlated with a greater incidence of development of nodules (p = 0.050). Radiographic features in patients treated with immunotherapy all decreased over time. Conversely, in patients treated with chemotherapy the incidence of ground glass opacities, traction bronchiectasis, pulmonary nodules, and mediastinal/hilar adenopathy increased over time. CONCLUSIONS: IRAE-pneumonitis has distinct features and a distinct clinical course compared to pneumonitis secondary to chemotherapy. Importantly, IRAE-pneumonitis features decreased over time, suggesting that careful consideration of the benefit-risk ratio may allow for continuation of immunotherapy in some patients who develop pneumonitis.

Breast Cancer Risk and Screening Mammography Frequency Among Multiethnic Women.

INTRODUCTION: In 2009, the U.S. Preventive Services Task Force updated recommended mammography screening frequency from annual to biennial for average-risk women aged 50-74 years. The association between estimated breast cancer risk and mammography screening frequency was evaluated. METHODS: A single-center retrospective cohort study was conducted among racially/ethnically diverse women, aged 50-74 years, who underwent screening mammography from 2014 to 2018. Data on age, race/ethnicity, first-degree family history of breast cancer, previous benign breast biopsies, and mammographic density were extracted from the electronic health record to calculate Breast Cancer Surveillance Consortium 5-year risk of invasive breast cancer, with a 5-year risk ≥1.67% defined as high risk. Multivariable analyses were conducted to determine the association between breast cancer risk factors and mammography screening frequency (annual versus biennial). Data were analyzed from 2020 to 2022. RESULTS: Among 12,929 women with a mean age of 61±6.9 years, 82.7% underwent annual screening mammography, and 30.7% met high-risk criteria for breast cancer. Hispanic women were more likely to screen annually than non-Hispanic Whites (85.0% vs 79.8%, respectively), despite fewer meeting high-risk criteria. In multivariable analyses adjusting for breast cancer risk factors, high- versus low/average-risk women (OR=1.17; 95% CI=1.04, 1.32) and Hispanic versus non-Hispanic White women (OR=1.46; 95% CI=1.29, 1.65) were more likely to undergo annual mammography. CONCLUSIONS: A majority of women continue to undergo annual screening mammography despite only a minority meeting high-risk criteria, and Hispanic women were more likely to screen annually despite lower overall breast cancer risk. Future studies should focus on the implementation of risk-stratified breast cancer screening strategies.

Lack of Age-Appropriate Reference Intervals Causing Potentially Missed Alerts in Clinical Reports of Dyslipidemia.

This study shows that only 12.5% of laboratory reports (2/16) included age-appropriate pediatric reference ranges for all lipid and lipoproteins. The use of erroneous reference range(s) could lead to missed alerts of dyslipidemia in up to 97.3% (total cholesterol), 93.6% (high-density lipoprotein cholesterol), 94.8% (low-density lipoprotein cholesterol), and 87.8% (triglycerides) of youth in the population-based National Health and Nutrition Examination Survey cohort. These findings highlight the potential missed opportunities for reinforcing lifestyle counseling for dyslipidemia in addition to obesity in youth.

Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer.

The multi-modal and unstructured nature of observational data in Electronic Health Records (EHR) is currently a significant obstacle for the application of machine learning towards risk stratification. In this study, we develop a deep learning framework for incorporating longitudinal clinical data from EHR to infer risk for pancreatic cancer (PC). This framework includes a novel training protocol, which enforces an emphasis on early detection by applying an independent Poisson-random mask on proximal-time measurements for each variable. Data fusion for irregular multivariate time-series features is enabled by a "grouped" neural network (GrpNN) architecture, which uses representation learning to generate a dimensionally reduced vector for each measurement set before making a final prediction. These models were evaluated using EHR data from Columbia University Irving Medical Center-New York Presbyterian Hospital. Our framework demonstrated better performance on early detection (AUROC 0.671, CI 95% 0.667 - 0.675, p < 0.001) at 12 months prior to diagnosis compared to a logistic regression, xgboost, and a feedforward neural network baseline. We demonstrate that our masking strategy results greater improvements at distal times prior to diagnosis, and that our GrpNN model improves generalizability by reducing overfitting relative to the feedforward baseline. The results were consistent across reported race. Our proposed algorithm is potentially generalizable to other diseases including but not limited to cancer where early detection can improve survival.

Immunogenetics of gastrointestinal cancers: A systematic review and retrospective survey of inborn errors of immunity in humans.

BACKGROUND AND AIM: Humans with inborn errors of immunity (IEI), or primary immunodeficiencies, may be associated with a potential risk factor for early-onset gastrointestinal (GI) cancer. METHODS: We systematically reviewed all cases with clinical diagnoses of both an IEI and a GI cancer in three databases (MEDLINE, SCOPUS, and EMBASE). In total, 76 publications satisfying our inclusion criteria were identified, and data for 149 cases were analyzed. We also searched our institutional cancer registry for such cases. RESULTS: We identified 149 patients with both an IEI and a GI cancer, 95 presented gastric cancer, 13 small bowel cancer, 35 colorectal cancer, and 6 had an unspecified cancer or cancer at another site. Gastric and colon adenocarcinomas were the most common. For both gastric and colorectal cancers, age at onset was significantly earlier in patients with IEIs than in the general population, based on the SEER database. Common variable immunodeficiency (CVID) was the most common IEI associated with gastrointestinal cancer. About 12% of patients had molecular genetic diagnoses, the three most frequently implicated genes being ATM, CARMIL2, and CTLA4. Impaired humoral immunity and Epstein-Barr virus (EBV) infection were frequently reported as factors potentially underlying early-onset GI cancers in patients with IEIs. We identified one patient with CVID and early-onset gastric adenocarcinoma, recurrent diarrhea, and gastrointestinal CMV infection from a retrospective survey. CONCLUSION: Patients with IEIs should be considered at risk of early-onset GI cancers and should therefore undergo cancer screening at an earlier age.

Using a roller pump for establishing extra-corporal membrane oxygenation (ECMO) - technical considerations for times of crisis.

OBJECTIVE: The COVID-19 pandemic requires thinking about alternatives to establish ECMO when often-limited hardware resources are exhausted. Heart-lung-machines may potentially be used for ECMO but contain roller pumps as compared to centrifugal pumps in ECMO-circuits. We here tested roller pumps as rescue pump for ECMO-establishment. METHODS: We set up in vitro circuits on roller pumps from C5 heart-lung-machine with 5 l/minutes flow. In two series, we placed either PVC or silicon tubing for an ECMO circuit into the roller pump. We assessed the mechanical stress on the tubing (aiming to run the pump for at least 1 week), measured the temperature increase generated by the friction and assessed flow characteristics and its measurement in simulated situations resembling tube kinking and suction. RESULTS: The roller pumps led to expected and unexpected adverse events. PVC tubing burst between 36 and 78 hours, while silicon tubing lasted for at least 7 days. At 7 days, the silicone tubing showed significant signs of roller pump wear visible on the outside. The inside, however, was free of surface irregularities. Using these tubings in a roller pump led to a remarkable increase in circuit temperature (PVC: +12.0°C, silicone +2.9°C). Kinking or suction on the device caused the expected dramatic flow reduction (as assessed by direct measurement) while the roller pump display continued to show the preset flow. The roller pump is therefore not able to reliably determine the true flow rate. CONCLUSION: Roller pumps with silicone tubing but not PVC tubing may be used for running ECMO circuits. Silicone tubing may endure the roller pump shear forces for up to 1 week. Thus, repeated tubing repositioning may be a solution. Circuit heating and substantial limitations in flow detection should increase attention if clinical use in situations of crisis is considered.

Immunotherapy related pericardial effusion on chest CT.

BACKGROUND: Immunotherapy has become a critical class of anticancer therapy in recent years, functioning by releasing brakes on the immune system that ultimately results in immune cell activation which eliminates cancer cells. Immune related adverse events (IRAEs) are a specific type of adverse event described in patients taking checkpoint inhibitor immunotherapy which results from unrestrained immune activation. Immune related pericardial effusion has been described however has not been comprehensively characterized. Here, we present the most extensive report to date detailing this adverse event. METHODS: We queried our medical record system to retrospectively identify patients on checkpoint inhibitor therapy for lung cancer who subsequently developed pericardial effusion. We analyzed the clinical and radiographic characteristics, prior therapies, treatment for the effusion, and outcomes in patients with immune related pericardial effusion and compared them to similar patients with pericardial effusion not attributable to checkpoint inhibitor therapy. RESULTS: Our data demonstrate that most of these pericardial effusions were small and not clinically significant. The majority were successfully treated with steroids or resolved spontaneously. Anti-PD-1 inhibitors were the most common checkpoint inhibitor preceding pericardial effusion, and a significant number of patients who went on to develop IRAE pericardial effusion previously had treatment with carboplatin for their cancer. CONCLUSIONS: These data suggest that IRAE pericardial effusion is not a clinically significant adverse event however it sometimes leads to permanent discontinuation of checkpoint inhibitor therapy which is not necessary.

Conventional Hepatic Volumetry May Lead to Inaccurate Segmental Yttrium-90 Radiation Dosimetry.

OBJECTIVE: To compare radioembolization treatment zone volumes from mapping cone beam CT (CBCT) versus planning CT/MRI and to model their impact on dosimetry. METHODS: Y90 cases were retrospectively identified in which intra-procedural CBCT angiograms were performed. Segmental and lobar treatment zone volumes were calculated with semi-automated contouring using Couinaud venous anatomy (planning CT/MRI) or tumor angiosome enhancement (CBCT). Differences were compared with a Wilcoxon signed-rank test. Treatment zone-specific differences in segmental volumes by volumetric method were also calculated and used to model differences in delivered dose using medical internal radiation dosimetry (MIRD) at 200 and 120 Gy targets. Anatomic, pathologic, and technical factors likely affecting segmental volumes by volumetric method were evaluated. RESULTS: Forty segmental and 48 lobar CBCT angiograms and corresponding planning CT/MRI scans were included. Median Couinaud- and CBCT-derived segmental volumes were 281 and 243 mL, respectively (p = 0.005). Differences between Couinaud and CBCT lobar volumes (right, left) were not significant (p = 0.24, p = 0.07). Couinaud overestimated segmental volumes in 28 cases by a median of 98 mL (83%) and underestimated in 12 cases by median 69 mL (20%). At a 200 Gy dose target, Couinaud estimates produced median delivered doses of 367 and 160 Gy in these 28 and 12 cases. At a 120 Gy target, Couinaud produced doses of 220 and 96 Gy. Proximal vs. distal microcatheter positioning, variant arterial anatomy, and tumor location on or near segmental watersheds were leading factors linked to volumetric differences. CONCLUSION: Use of CBCT-based volumetry may allow more accurate, personalized dosimetry for segmental Y90 radioembolization.

Kinetic characterisation and inhibitor sensitivity of Candida albicans and Candida auris recombinant AOX expressed in a self-assembled proteoliposome system.

Candidemia caused by Candida spp. is a serious threat in hospital settings being a major cause of acquired infection and death and a possible contributor to Covid-19 mortality. Candidemia incidence has been rising worldwide following increases in fungicide-resistant pathogens highlighting the need for more effective antifungal agents with novel modes of action. The membrane-bound enzyme alternative oxidase (AOX) promotes fungicide resistance and is absent in humans making it a desirable therapeutic target. However, the lipophilic nature of the AOX substrate (ubiquinol-10) has hindered its kinetic characterisation in physiologically-relevant conditions. Here, we present the purification and expression of recombinant AOXs from C. albicans and C. auris in a self-assembled proteoliposome (PL) system. Kinetic parameters (Km and Vmax) with respect to ubiquinol-10 have been determined. The PL system has also been employed in dose-response assays with novel AOX inhibitors. Such information is critical for the future development of novel treatments for Candidemia.