Antifungal heteroresistance causes prophylaxis failure and facilitates breakthrough Candida parapsilosis infections.

Breakthrough fungal infections in patients on antimicrobial prophylaxis during allogeneic hematopoietic cell transplantation (allo-HCT) represent a major and often unexplained cause of morbidity and mortality. Candida parapsilosis is a common cause of invasive candidiasis and has been classified as a high-priority fungal pathogen by the World Health Organization. In high-risk allo-HCT recipients on micafungin prophylaxis, we show that heteroresistance (the presence of a phenotypically unstable, low-frequency subpopulation of resistant cells (~1 in 10,000)) underlies breakthrough bloodstream infections by C. parapsilosis. By analyzing 219 clinical isolates from North America, Europe and Asia, we demonstrate widespread micafungin heteroresistance in C. parapsilosis. Standard antimicrobial susceptibility tests, such as broth microdilution or gradient diffusion assays, which guide drug selection for invasive infections, fail to detect micafungin heteroresistance in C. parapsilosis. To facilitate rapid detection of micafungin heteroresistance in C. parapsilosis, we constructed a predictive machine learning framework that classifies isolates as heteroresistant or susceptible using a maximum of ten genomic features. These results connect heteroresistance to unexplained antifungal prophylaxis failure in allo-HCT recipients and demonstrate a proof-of-principle diagnostic approach with the potential to guide clinical decisions and improve patient care.

A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Aluminothermic reduction of CeO2: mechanism of an economical route to aluminum-cerium alloys.

Cerium oxide is a low-value byproduct of rare-earth mining yet constitutes the largest fraction of the rare earth elements. The reduction of cerium oxide by liquid aluminum is proposed as an energy- and cost-efficient route to produce high-strength Al-Ce alloys. This work investigated the mechanism of a multi-step reduction reaction to facilitate the industrial adaptation of the process. Differential scanning calorimetry in combination with time-resolved synchrotron diffraction data uncovered the rate-limiting reaction step as the origin of the reported temperature dependence of reduction efficiency. This is the first in situ study of a metallothermic reaction mechanism and will serve as guidance for cost- and energy efficient industrial process control.

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset.

Supplemental material is available for this article.

IVT generation of guideRNAs for Cas9-enrichment Nanopore Sequencing.

Generating high-coverage sequencing coverage at select genomic loci has extensive applications in both research science and genetic medicine. Long-read sequencing technologies (e.g. nanopore sequencing) have expanded our ability to generate sequencing data in regions (e.g. repetitive elements) that are difficult to interrogate with short-read sequencing methods. In work presented here, we expand on our previous work using CRISPR/Cas9 for targeted nanopore sequencing by using in vitro transcribed guideRNAs, with 1100 guideRNAs in a single experiment. This approach decreases the cost per guideRNA, increases the number of guideRNAs that can be multiplexed in a single experiment, and provides a way to rapidly screen numerous guideRNAs for cutting efficiency. We apply this strategy in multiple patient-derived pancreatic cancer cell lines, demonstrating its ability to unveil structural variation in "deletion hotspots" around the tumor suppressor genes p16 (CDKN2A), and SMAD4.

Longitudinal Assessment of Posttreatment Diffuse Glioma Tissue Volumes with Three-dimensional Convolutional Neural Networks.

Neural networks were trained for segmentation and longitudinal assessment of posttreatment diffuse glioma. A retrospective cohort (from January 2018 to December 2019) of 298 patients with diffuse glioma (mean age, 52 years ± 14 [SD]; 177 men; 152 patients with glioblastoma, 72 patients with astrocytoma, and 74 patients with oligodendroglioma) who underwent two consecutive multimodal MRI examinations were randomly selected into training (n = 198) and testing (n = 100) samples. A posttreatment tumor segmentation three-dimensional nnU-Net convolutional neural network with multichannel inputs (T1, T2, and T1 postcontrast and fluid-attenuated inversion recovery [FLAIR]) was trained to segment three multiclass tissue types (peritumoral edematous, infiltrated, or treatment-changed tissue [ED]; active tumor or enhancing tissue [AT]; and necrotic core). Separate longitudinal change nnU-Nets were trained on registered and subtracted FLAIR and T1 postlongitudinal images to localize and better quantify and classify changes in ED and AT. Segmentation Dice scores, volume similarities, and 95th percentile Hausdorff distances ranged from 0.72 to 0.89, 0.90 to 0.96, and 2.5 to 3.6 mm, respectively. Accuracy rates of the posttreatment tumor segmentation and longitudinal change networks being able to classify longitudinal changes in ED and AT as increased, decreased, or unchanged were 76%-79% and 90%-91%, respectively. The accuracy levels of the longitudinal change networks were not significantly different from those of three neuroradiologists (accuracy, 90%-92%; κ, 0.58-0.63; P > .05). The results of this study support the potential clinical value of artificial intelligence-based automated longitudinal assessment of posttreatment diffuse glioma. Keywords: MR Imaging, Neuro-Oncology, Neural Networks, CNS, Brain/Brain Stem, Segmentation, Quantification, Convolutional Neural Network (CNN) Supplemental material is available for this article. © RSNA, 2022.

Longitudinal assessment of colonoscopy adverse events in the prospective Cooperative Studies Program no. 380 colorectal cancer screening and surveillance cohort.

BACKGROUND AND AIMS: Data are limited regarding colonoscopy risk during long-term, programmatic colorectal cancer screening and follow-up. We aimed to describe adverse events during follow-up in a colonoscopy screening program after the baseline examination and examine factors associated with increased risk. METHODS: Cooperative Studies Program no. 380 includes 3121 asymptomatic veterans aged 50 to 75 years who underwent screening colonoscopy between 1994 and 1997. Periprocedure adverse events requiring significant intervention were defined as major events (other events were minor) and were tracked during follow-up for at least 10 years. Multivariable odds ratios (ORs) were calculated for factors associated with risk of follow-up adverse events. RESULTS: Of 3727 follow-up examinations in 1983 participants, adverse events occurred in 105 examinations (2.8%) in 93 individuals, including 22 major and 87 minor events (examinations may have had >1 event). Incidence of major events (per 1000 examinations) remained relatively stable over time, with 6.1 events at examination 2, 4.8 at examination 3, and 7.2 at examination 4. Examinations with major events included 1 perforation, 3 GI bleeds requiring intervention, and 17 cardiopulmonary events. History of prior colonoscopic adverse events was associated with increased risk of events (major or minor) during follow-up (OR, 2.7; 95% confidence interval, 1.6-4.6). CONCLUSIONS: Long-term programmatic screening and surveillance was safe, as major events were rare during follow-up. However, serious cardiopulmonary events were the most common major events. These results highlight the need for detailed assessments of comorbid conditions during routine clinical practice, which could help inform individual decisions regarding the utility of ongoing colonoscopy follow-up.

Screening Colonoscopy Findings Are Associated With Noncolorectal Cancer Mortality.

INTRODUCTION: Controversy exists regarding the impact of various risk factors on noncolorectal cancer (CRC) mortality in healthy screening populations. We examined the impact of known CRC risk factors, including baseline colonoscopy findings, on non-CRC mortality in a screening population. METHODS: Cooperative Studies Program (CSP) #380 is comprised of 3,121 veterans aged 50-75 years who underwent screening colonoscopy from 1994 to 97 and were then followed for at least 10 years or until death. Hazard ratios (HRs) for risk factors on non-CRC mortality were estimated by multivariate Cox proportional hazards. RESULTS: Current smoking (HR 2.12, 95% confidence interval [CI] 1.78-2.52, compared with nonsmokers) and physical activity (HR 0.89, 95% CI 0.84-0.93) were the modifiable factors most associated with non-CRC mortality in CSP#380. In addition, compared with no neoplasia at baseline colonoscopy, non-CRC mortality was higher in participants with ≥3 small adenomas (HR 1.43, 95% CI 1.06-1.94), advanced adenomas (HR 1.32, 95% CI 0.99-1.75), and CRC (HR 2.95, 95% CI 0.98-8.85). Those with 1-2 small adenomas were not at increased risk for non-CRC mortality (HR 1.15, 95% CI 0.94-1.4). DISCUSSION: In a CRC screening population, known modifiable risk factors were significantly associated with 10-year non-CRC mortality. Furthermore, those who died from non-CRC causes within 10 years were more likely to have had high-risk findings at baseline colonoscopy. These results suggest that advanced colonoscopy findings may be a risk marker of poor health outcomes. Integrated efforts are needed to motivate healthy lifestyle changes during CRC screening, particularly in those with high-risk colonoscopy findings and unaddressed risk factors.

Interinstitutional Portability of a Deep Learning Brain MRI Lesion Segmentation Algorithm.

PURPOSE: To assess how well a brain MRI lesion segmentation algorithm trained at one institution performed at another institution, and to assess the effect of multi-institutional training datasets for mitigating performance loss. MATERIALS AND METHODS: In this retrospective study, a three-dimensional U-Net for brain MRI abnormality segmentation was trained on data from 293 patients from one institution (IN1) (median age, 54 years; 165 women; patients treated between 2008 and 2018) and tested on data from 51 patients from a second institution (IN2) (median age, 46 years; 27 women; patients treated between 2003 and 2019). The model was then trained on additional data from various sources: (a) 285 multi-institution brain tumor segmentations, (b) 198 IN2 brain tumor segmentations, and (c) 34 IN2 lesion segmentations from various brain pathologic conditions. All trained models were tested on IN1 and external IN2 test datasets, assessing segmentation performance using Dice coefficients. RESULTS: The U-Net accurately segmented brain MRI lesions across various pathologic conditions. Performance was lower when tested at an external institution (median Dice score, 0.70 [IN2] vs 0.76 [IN1]). Addition of 483 training cases of a single pathologic condition, including from IN2, did not raise performance (median Dice score, 0.72; P = .10). Addition of IN2 training data with heterogeneous pathologic features, representing only 10% (34 of 329) of total training data, increased performance to baseline (Dice score, 0.77; P < .001). This final model produced total lesion volumes with a high correlation to the reference standard (Spearman r = 0.98). CONCLUSION: For brain MRI lesion segmentation, adding a modest amount of relevant training data from an external institution to a previously trained model supported successful application of the model to this external institution.Keywords: Neural Networks, Brain/Brain Stem, Segmentation Supplemental material is available for this article. © RSNA, 2021.

Prevalence of colistin heteroresistance in carbapenem-resistant Pseudomonas aeruginosa and association with clinical outcomes in patients: an observational study.

OBJECTIVES: To describe the prevalence of colistin heteroresistance in carbapenem-resistant Pseudomonas aeruginosa (CRPA) and evaluate the association with clinical outcomes. METHODS: Colistin heteroresistance was evaluated in CRPA isolates collected from patients without cystic fibrosis in Atlanta, Georgia, USA using two definitions: HR1, growth at 4 and 8 mg/L of colistin at a frequency ≥1 × 10-6 the main population; and HR2, growth at a colistin concentration ≥8× the MIC of the main population at a frequency ≥1 × 10-7. A modified population analysis profile (mPAP) technique was compared with reference PAP for detecting heteroresistance. For adults hospitalized at the time of or within 1 week of CRPA culture, multivariable logistic regression estimated the association between heteroresistance and 90 day mortality. RESULTS: Of 143 colistin-susceptible CRPA isolates, 8 (6%) met the HR1 definition and 37 (26%) met the HR2 definition. Compared with the reference PAP, mPAP had a sensitivity and specificity of 50% and 100% for HR1 and 32% and 99% for HR2. Of 82 hospitalized patients, 45 (56%) were male and the median age was 63 years (IQR 49-73). Heteroresistance was not associated with 90 day mortality using HR1 (0% in heteroresistant versus 22% in non-heteroresistant group; P = 0.6) or HR2 (12% in heteroresistant versus 24% in non-heteroresistant group; P = 0.4; adjusted OR 0.8; 95% CI 0.2-3.4). CONCLUSIONS: Colistin heteroresistance was identified in up to 26% of patients with CRPA in our sample, although the prevalence varied depending on the definition. We did not observe an apparent association between colistin heteroresistance and 90 day mortality.

Ten or More Cumulative Lifetime Adenomas Are Associated with Increased Risk for Advanced Neoplasia and Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) screening guidelines recommend frequent colonoscopies and consideration of genetic testing in individuals with ≥10 cumulative adenomas. However, it is unclear how these guidelines apply to routine practice. AIMS: We estimated the proportion of participants found to have ≥10 cumulative adenomas in a screening population and described their outcomes of advanced neoplasia (AN), CRC, and extra-colonic malignancy. METHODS: We performed a secondary analysis of VA CSP#380, which includes 3121 veterans aged 50-75 who were followed up to 10 years after screening colonoscopy. We calculated the cumulative risk of ≥10 cumulative adenomas by Kaplan-Meier method. We compared baseline risk factors in those with and without ≥10 cumulative adenomas as well as the risk for AN (adenoma ≥1 cm, villous adenoma or high-grade dysplasia, or CRC) and extra-colonic malignancy by multivariate logistic regression. RESULTS: The cumulative risk of ≥10 cumulative adenomas over 10.5 years was 6.51% (95% CI 4.38%-9.62%). Age 60-69 or 70-75 at baseline colonoscopy was the only factors associated with the finding of ≥10 cumulative adenomas. Compared to those with 0-9 cumulative adenomas, participants with ≥10 cumulative adenomas were more likely to have had AN (OR 17.03; 95% CI 9.41-30.84), including CRC (OR 7.00; 95% CI 2.84-17.28), but not extra-colonic malignancies. CONCLUSIONS: Approximately 6.5% of participants in this screening population were found to have ≥10 cumulative adenomas over 10.5 years, which was uncommon before age 60. These participants were found to have AN and CRC significantly more often compared to those with lower cumulative adenomas.

An Open Trial of Metacognitive Remediation Therapy and Pharmacotherapy to Promote Smoking Cessation among Individuals with Psychotic-Spectrum Disorders.

INTRODUCTION: Individuals with psychotic-spectrum disorders may smoke due to the ameliorating effect of nicotine on the cognitive deficits that accompany these illnesses. Metacognitive remediation therapy (MCR) has been shown to produce improvements in cognitive functioning among individuals with psychotic-spectrum disorders and provides a foundation for a novel smoking cessation intervention for this population. AIMS: To complete an open investigation of pharmacotherapy and a modified version of MCR [MCR to Quit (MCR-Q)] in promoting smoking cessation among individuals with psychotic-spectrum disorders. METHODS: Forty-nine individuals with a psychotic-spectrum disorder and who currently smoke cigarettes participated in MCR-Q while also receiving evidence-based smoking cessation pharmacotherapy. Tobacco use was assessed as follows: (i) prior to MCR-Q, (ii) immediately after completing MCR-Q, and (iii) six weeks after completion of MCR-Q. RESULTS: /Findings. During participation in MCR-Q, nearly 80% of participants made a 24-hour quit attempt. Following the completion of MCR-Q, participants experienced reductions in level of nicotine dependency and exhaled carbon monoxide, with reductions in nicotine dependency sustained six weeks after completion of MCR-Q. Over the course of their participation in MCR-Q, participants reported strong therapeutic alliance with their MCR-Q therapist and high levels of intrinsic motivation with regard to completing MCR-Q exercises. CONCLUSIONS: The results from the current study suggest cautious optimism with regard to the use of MCR-Q in combination with medication for individuals with psychotic-spectrum disorders who want to quit smoking.

Anti-NMDA receptor encephalitis and overlapping demyelinating disorder in a 20-year old female with borderline personality disorder: proposal of a diagnostic and therapeutic algorithm for autoimmune encephalitis in psychiatric patients "case report".

BACKGROUND: Anti-NMDA receptor encephalitis (NMDAR-E) is an autoimmune encephalitis (AE) mainly affecting young females. It typically presents with isolated psychiatric symptoms (e.g. depressed mood) at first and neurological abnormalities (e.g. seizures, movement disorders) only develop later. Thus, there is a high risk of overlooking NMDAR-E in patients with preexisting psychiatric illness due to symptom overlap in the prodromal period of the disease when treatment is most effective. Although rare, concomitant or sequential development of a demyelinating disorder is increasingly recognized as an associated disease entity (overlap syndrome), with immediate diagnostic and therapeutic implications. CASE PRESENTATION: We report a patient with a borderline personality disorder (BPD), which developed NMDAR-E and an overlapping demyelinating disorder with anti-Myelin oligodendrocyte glycoprotein (MOG) -IgG positivity. The initial clinical presentation with predominantly affective symptoms (e.g. mood lability, anxiety, depressed mood) lead us to suspect an exacerbation of the BPD at first. However, acute changes in premorbid behavior, newly developed psychotic symptoms and memory deficits lead us to the correct diagnosis of an AE, which was further complicated by the development of a demyelinating disorder. As a result of impaired illness awareness and psychosis, diagnostic and treatment was difficult to carry out. The symptoms completely remitted after treatment with methylprednisolone 1 g daily for 5 days and 5 cycles of plasma exchange. CONCLUSIONS: Continuous awareness for neuropsychiatric clinical warning signs in patients with a pre-diagnosed psychiatric disorder is important for a timely diagnosis. Therefore, we believe that the diagnostic and therapeutic algorithm provided here, for the first time specifically addressing patients with preexisting psychiatric illness and integrating overlap syndromes, can be a useful tool. Moreover, in order to timely perform diagnostics and treatment, judicial approval should be obtained rapidly.

Three-dimensional U-Net Convolutional Neural Network for Detection and Segmentation of Intracranial Metastases.

PURPOSE: To develop and validate a neural network for automated detection and segmentation of intracranial metastases on brain MRI studies obtained for stereotactic radiosurgery treatment planning. MATERIALS AND METHODS: In this retrospective study, 413 patients (average age, 61 years ± 12 [standard deviation]; 238 women) with a total of 5202 intracranial metastases (median volume, 0.05 cm3; interquartile range, 0.02-0.18 cm3) undergoing stereotactic radiosurgery at one institution were included (January 2017 to February 2020). A total of 563 MRI examinations were performed among the patients, and studies were split into training (n = 413), validation (n = 50), and test (n = 100) datasets. A three-dimensional (3D) U-Net convolutional network was trained and validated on 413 T1 postcontrast or subtraction scans, and several loss functions were evaluated. After model validation, 100 discrete test patients, who underwent imaging after the training and validation patients, were used for final model evaluation. Performance for detection and segmentation of metastases was evaluated using Dice scores, false discovery rates, and false-negative rates, and a comparison with neuroradiologist interrater reliability was performed. RESULTS: The median Dice score for segmenting enhancing metastases in the test set was 0.75 (interquartile range, 0.63-0.84). There were strong correlations between manually segmented and predicted metastasis volumes (r = 0.98, P < .001) and between the number of manually segmented and predicted metastases (R = 0.95, P < .001). Higher Dice scores were strongly correlated with larger metastasis volumes on a logarithmically transformed scale (r = 0.71). Sensitivity across the whole test sample was 70.0% overall and 96.4% for metastases larger than 6 mm. There was an average of 0.46 false-positive results per scan, with the positive predictive value being 91.5%. In comparison, the median Dice score between two neuroradiologists was 0.85 (interquartile range, 0.80-0.89), with sensitivity across the test sample being 87.9% overall and 98.4% for metastases larger than 6 mm. CONCLUSION: A 3D U-Net-based convolutional neural network was able to segment brain metastases with high accuracy and perform detection at the level of human interrater reliability for metastases larger than 6 mm.Keywords: Adults, Brain/Brain Stem, CNS, Feature detection, MR-Imaging, Neural Networks, Neuro-Oncology, Quantification, Segmentation© RSNA, 2021.

Improving the Delivery of Function-Directed Care During Acute Hospitalizations: Methods to Develop and Validate the Functional Assessment in Acute Care Multidimensional Computerized Adaptive Test (FAMCAT).

OBJECTIVE: To (1) develop a patient-reported, multidomain functional assessment tool focused on medically ill patients in acute care settings; (2) characterize the measure's psychometric performance; and (3) establish clinically actionable score strata that link to easily implemented mobility preservation plans. DESIGN: This article describes the approach that our team pursued to develop and characterize this tool, the Functional Assessment in Acute Care Multidimensional Computer Adaptive Test (FAMCAT). Development involved a multistep process that included (1) expanding and refining existing item banks to optimize their salience for hospitalized patients; (2) administering candidate items to a calibration cohort; (3) estimating multidimensional item response theory models; (4) calibrating the item banks; (5) evaluating potential multidimensional computerized adaptive testing (MCAT) enhancements; (6) parameterizing the MCAT; (7) administering it to patients in a validation cohort; and (8) estimating its predictive and psychometric characteristics. SETTING: A large (2000-bed) Midwestern Medical Center. PARTICIPANTS: The overall sample included 4495 adults (2341 in a calibration cohort, 2154 in a validation cohort) who were admitted either to medical services with at least 1 chronic condition or to surgical/medical services if they required readmission after a hospitalization for surgery (N=4495). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Not applicable. RESULTS: The FAMCAT is an instrument designed to permit the efficient, precise, low-burden, multidomain functional assessment of hospitalized patients. We tried to optimize the FAMCAT's efficiency and precision, as well as its ability to perform multiple assessments during a hospital stay, by applying cutting edge methods such as the adaptive measure of change (AMC), differential item functioning computerized adaptive testing, and integration of collateral test-taking information, particularly item response times. Evaluation of these candidate methods suggested that all may enhance MCAT performance, but none were integrated into initial MCAT parameterization. CONCLUSIONS: The FAMCAT has the potential to address a longstanding need for structured, frequent, and accurate functional assessment among patients hospitalized with medical diagnoses and complications of surgery.

Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.

Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care.

Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies.

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

Genetic Colorectal Cancer and Adenoma Risk Variants Are Associated with Increasing Cumulative Adenoma Counts.

BACKGROUND: The genetic basis for most individuals with high cumulative lifetime colonic adenomas is unknown. We investigated associations between known colorectal cancer-risk single-nucleotide polymorphisms (SNP) and increasing cumulative adenoma counts. METHODS: The Cooperative Studies Program #380 screening colonoscopy cohort includes 612 selected participants age 50 to 75 with genotyped blood samples and 10 years of clinical follow-up. We evaluated 41 published "colorectal cancer-risk SNPs" for associations with individual cumulative adenoma counts or having ≥10 cumulative adenomas. SNPs were analyzed singly or combined in a polygenic risk score (PRS). The PRS was constructed from eight published SNPs associated with multiple adenomas, termed "adenoma-risk SNPs." RESULTS: Four colorectal cancer-risk SNPs were associated with increasing cumulative adenoma counts (P < 0.05): rs12241008 (gene: VTI1A), rs2423279 (BMP2/HAO1), rs3184504 (SH2B3), and rs961253 (FERMT1/BMP2), with risk allele risk ratios of 1.31, 1.29, 1.24, and 1.23, respectively. Three colorectal cancer-risk SNPs were associated with ≥10 cumulative adenomas (P < 0.05), with risk allele odds ratios of 2.09 (rs3184504), 2.30 (rs961253), and 1.94 (rs3217901). A weighted PRS comprised of adenoma-risk SNPs was associated with higher cumulative adenomas (weighted rate ratio = 1.57; P = 0.03). CONCLUSIONS: In this mostly male veteran colorectal cancer screening cohort, several known colorectal cancer-risk SNPs were associated with increasing cumulative adenoma counts and the finding of ≥10 cumulative adenomas. In addition, an increasing burden of adenoma-risk SNPs, measured by a weighted PRS, was associated with higher cumulative adenomas. IMPACT: Future work will seek to validate these findings in different populations and then augment current colorectal cancer risk prediction tools with precancerous, adenoma genetic data.

Phase II Study of Combination Obinutuzumab, Ibrutinib, and Venetoclax in Treatment-Naïve and Relapsed or Refractory Chronic Lymphocytic Leukemia.

PURPOSE: The development of highly effective targeted agents for chronic lymphocytic leukemia offers the potential for fixed-duration combinations that achieve deep remissions without cytotoxic chemotherapy. PATIENTS AND METHODS: This phase II study tested a combination regimen of obinutuzumab, ibrutinib, and venetoclax for a total of 14 cycles in both patients with treatment-naïve (n = 25) and relapsed or refractory (n = 25) chronic lymphocytic leukemia to determine the response to therapy and safety. RESULTS: The primary end point was the rate of complete remission with undetectable minimal residual disease by flow cytometry in both the blood and bone marrow 2 months after completion of treatment, which was 28% in both groups. The overall response rate at that time was 84% in treatment-naïve patients and 88% in relapsed or refractory patients. At that time, 67% of treatment-naïve patients and 50% of relapsed or refractory patients had undetectable minimal residual disease in both the blood and marrow. At a median follow-up of 24.2 months in treatment-naïve patients and 21.5 months in relapsed or refractory patients, the median progression-free and overall survival times were not yet reached, with only 1 patient experiencing progression and 1 death. Neutropenia and thrombocytopenia were the most frequent adverse events, followed by hypertension. Grade 3 or 4 neutropenia was experienced by 66% of patients, with more events in the relapsed or refractory cohort. There was only 1 episode of neutropenic fever. A favorable impact on both perceived and objective cognitive performance during treatment was observed. CONCLUSION: The combination regimen of obinutuzumab, ibrutinib, and venetoclax offers time-limited treatment that results in deep remissions and is now being studied in phase III cooperative group trials.