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In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes, such as personality changes. These findings are particularly intriguing, given that a decrease of brain entropy is a robust indicator of loss of consciousness (e.g., from wakefulness to sleep). However, little is known about how context impacts the entropy-enhancing effect of psychedelics, which carries important implications for how it can be exploited in, for example, psychedelic psychotherapy. This article investigates how brain entropy is modulated by stimulus manipulation during a psychedelic experience by studying participants under the effects of lysergic acid diethylamide (LSD) or placebo, either with gross state changes (eyes closed vs open) or different stimuli (no stimulus vs music vs video). Results show that while brain entropy increases with LSD under all of the experimental conditions, it exhibits the largest changes when subjects have their eyes closed. Furthermore, brain entropy changes are consistently associated with subjective ratings of the psychedelic experience, but this relationship is disrupted when participants are viewing a video─potentially due to a competition between external stimuli and endogenous LSD-induced imagery. Taken together, our findings provide strong quantitative evidence of the role of context in modulating neural dynamics during a psychedelic experience, underlining the importance of performing psychedelic psychotherapy in a suitable environment.

Diagnostic development must occur in parallel with drug development to ensure the longevity of new treatment compounds. Despite an increasing number of novel and repurposed anti-tuberculosis compounds and regimens, there remains a large number of drugs for which no rapid and accurate molecular diagnostic option exists. The lack of rapid drug susceptibility testing for linezolid, bedaquiline, clofazimine, the nitroimidazoles (i.e pretomanid and delamanid) and pyrazinamide at any level of the healthcare system compromises the effectiveness of current tuberculosis and drug-resistant tuberculosis treatment regimens. In the context of current WHO tuberculosis treatment guidelines as well as promising new regimens, we identify the key diagnostic gaps for initial and follow-on tests to diagnose emerging drug resistance and aid in regimen selection. Additionally, we comment on potential gene targets for inclusion in rapid molecular drug susceptibility assays and sequencing assays for novel and repurposed drug compounds currently prioritized in current regimens, and evaluate the feasibility of mutation detection given the design of existing technologies. Based on current knowledge, we also propose design priorities for next generation molecular assays to support triage of tuberculosis patients to appropriate and effective treatment regimens. We encourage assay developers to prioritize development of these key molecular assays and support the continued evolution, uptake, and utility of sequencing to build knowledge of tuberculosis resistance mechanisms and further inform rapid treatment decisions in order to curb resistance to critical drugs in current regimens and achieve End TB targets.Trial registration: ClinicalTrials.gov identifier: NCT05117788..

BACKGROUND: Social determinants of health (SDOH) are becoming increasingly recognised as mediators of human health. In the setting of metabolic dysfunction-associated steatotic liver disease (MASLD), most of the literature on SDOH relates to individual-level risk factors. However, there are very limited data on neighbourhood-level SDOH in MASLD. AIM: To assess whether SDOH impact fibrosis progression in patients who already have MASLD. METHODS: This was a retrospective cohort study of patients with MASLD seen at Michigan Medicine. The primary predictors were two neighbourhood-level SDOH, disadvantage and affluence. The primary outcomes were mortality, incident liver-related events (LREs) and incident cardiovascular disease (CVD). We modelled these outcomes using Kaplan-Meier statistics for mortality and competing risk analyses for LREs and CVD, using a 1-year landmark. RESULTS: We included 15,904 patients with MASLD with median follow-up of 63 months. Higher affluence was associated with lower risk of overall mortality (hazard ratio 0.49 [0.37-0.66], p

Changes in the function of inhibitory interneurons (INs) during cortical development could contribute to the pathophysiology of neurodevelopmental disorders. Using all-optical in vivo approaches, we find that parvalbumin (PV) INs and their immature precursors are hypoactive and transiently decoupled from excitatory neurons in postnatal mouse somatosensory cortex (S1) of Fmr1 KO mice, a model of fragile X syndrome (FXS). This leads to a loss of parvalbumin INs (PV-INs) in both mice and humans with FXS. Increasing the activity of future PV-INs in neonatal Fmr1 KO mice restores PV-IN density and ameliorates transcriptional dysregulation in S1, but not circuit dysfunction. Critically, administering an allosteric modulator of Kv3.1 channels after the S1 critical period does rescue circuit dynamics and tactile defensiveness. Symptoms in FXS and related disorders could be mitigated by targeting PV-INs.

Pancreatic ductal adenocarcinoma (PDAC) is an insidious disease with a low 5-year survival rate. PDAC is characterized by infiltration of abundant tumor-associated macrophages (TAM), which promote immune tolerance and immunotherapeutic resistance. Here we report that macrophage spleen tyrosine kinase (Syk) promotes PDAC growth and metastasis. In orthotopic PDAC mouse models, genetic deletion of myeloid Syk reprogrammed macrophages into immunostimulatory phenotype, increased the infiltration, proliferation, and cytotoxicity of CD8+ T cells, and repressed PDAC growth and metastasis. Furthermore, gemcitabine (Gem) treatment induced an immunosuppressive microenvironment in PDAC by promoting protumorigenic polarization of macrophages. In contrast, treatment with the FDA-approved Syk inhibitor R788 (fostamatinib) remodeled the tumor immune microenvironment, "re-educated" protumorigenic macrophages towards an immunostimulatory phenotype and boosted CD8+ T-cell responses in Gem-treated PDAC in orthotopic mouse models and an ex vivo human pancreatic slice culture model. These findings illustrate the potential of Syk inhibition for enhancing the antitumor immune responses in PDAC and support the clinical evaluation of R788 either alone or together with Gem as a potential treatment strategy for PDAC.SignificanceSyk blockade induces macrophage polarization to an immunostimulatory phenotype, which enhances CD8+ T-cell responses and improves gemcitabine efficacy in pancreatic ductal adenocarcinoma, a clinically challenging malignancy.

With the current state of COVID-19 changing from a pandemic to being more endemic, the priorities of diagnostics will likely vary from rapid detection to stratification for the treatment of the most vulnerable patients. Such patient stratification can be facilitated using multiple markers, including SARS-CoV-2-specific viral enzymes, like the 3CL protease, and viral-life-cycle-associated host proteins, such as ACE2. To enable future explorations, we have developed a fluorescent and Raman spectroscopic SARS-CoV-2 3CL protease assay that can be run sequentially with a fluorescent ACE2 activity measurement within the same sample. Our prototype assay functions well in saliva, enabling non-invasive sampling. ACE2 and 3CL protease activity can be run with minimal sample volumes in 30 min. To test the prototype, a small initial cohort of eight clinical samples was used to check if the assay could differentiate COVID-19-positive and -negative samples. Though these small clinical cohort samples did not reach statistical significance, results trended as expected. The high sensitivity of the assay also allowed the detection of a low-activity 3CL protease mutant.

Immune-mediated anti-tumoral responses, elicited by oncolytic viruses and augmented with checkpoint inhibition, may be an effective treatment approach for glioblastoma. Here in this multicenter phase 1/2 study we evaluated the combination of intratumoral delivery of oncolytic virus DNX-2401 followed by intravenous anti-PD-1 antibody pembrolizumab in recurrent glioblastoma, first in a dose-escalation and then in a dose-expansion phase, in 49 patients. The primary endpoints were overall safety and objective response rate. The primary safety endpoint was met, whereas the primary efficacy endpoint was not met. There were no dose-limiting toxicities, and full dose combined treatment was well tolerated. The objective response rate was 10.4% (90% confidence interval (CI) 4.2-20.7%), which was not statistically greater than the prespecified control rate of 5%. The secondary endpoint of overall survival at 12 months was 52.7% (95% CI 40.1-69.2%), which was statistically greater than the prespecified control rate of 20%. Median overall survival was 12.5 months (10.7-13.5 months). Objective responses led to longer survival (hazard ratio 0.20, 95% CI 0.05-0.87). A total of 56.2% (95% CI 41.1-70.5%) of patients had a clinical benefit defined as stable disease or better. Three patients completed treatment with durable responses and remain alive at 45, 48 and 60 months. Exploratory mutational, gene-expression and immunophenotypic analyses revealed that the balance between immune cell infiltration and expression of checkpoint inhibitors may potentially inform on response to treatment and mechanisms of resistance. Overall, the combination of intratumoral DNX-2401 followed by pembrolizumab was safe with notable survival benefit in select patients (ClinicalTrials.gov registration: NCT02798406).

Immune-related adverse events (irAEs) associated with immune checkpoint inhibitor (ICI) therapy may vary substantially in their clinical presentation, including natural history, outcomes to treatment, and patterns. The application of clinical guidelines for irAE management can be challenging for practitioners due to a lack of common or consistently applied terminology. Furthermore, given the growing body of clinical experience and published data on irAEs, there is a greater appreciation for the heterogeneous natural histories, responses to treatment, and patterns of these toxicities, which is not currently reflected in irAE guidelines. Furthermore, there are no prospective trial data to inform the management of the distinct presentations of irAEs. Recognizing a need for uniform terminology for the natural history, response to treatment, and patterns of irAEs, the Society for Immunotherapy of Cancer (SITC) convened a consensus panel composed of leading international experts from academic medicine, industry, and regulatory agencies. Using a modified Delphi consensus process, the expert panel developed clinical definitions for irAE terminology used in the literature, encompassing terms related to irAE natural history (ie, re-emergent, chronic active, chronic inactive, delayed/late onset), response to treatment (ie, steroid unresponsive, steroid dependent), and patterns (ie, multisystem irAEs). SITC developed these definitions to support the adoption of a standardized vocabulary for irAEs, which will have implications for the uniform application of irAE clinical practice guidelines and to enable future irAE clinical trials.

Previously, two men were cured of HIV-1 through CCR5Δ32 homozygous (CCR5Δ32/Δ32) allogeneic adult stem cell transplant. We report the first remission and possible HIV-1 cure in a mixed-race woman who received a CCR5Δ32/Δ32 haplo-cord transplant (cord blood cells combined with haploidentical stem cells from an adult) to treat acute myeloid leukemia (AML). Peripheral blood chimerism was 100% CCR5Δ32/Δ32 cord blood by week 14 post-transplant and persisted through 4.8 years of follow-up. Immune reconstitution was associated with (1) loss of detectable replication-competent HIV-1 reservoirs, (2) loss of HIV-1-specific immune responses, (3) in vitro resistance to X4 and R5 laboratory variants, including pre-transplant autologous latent reservoir isolates, and (4) 18 months of HIV-1 control with aviremia, off antiretroviral therapy, starting at 37 months post-transplant. CCR5Δ32/Δ32 haplo-cord transplant achieved remission and a possible HIV-1 cure for a person of diverse ancestry, living with HIV-1, who required a stem cell transplant for acute leukemia.

ImportanceHypertension contributes to more than 1.6 million deaths annually in India, with many individuals being unaware they have the condition or receiving inadequate treatment. Policy initiatives to strengthen disease detection and management through primary care services in India are not currently informed by population preferences.ObjectiveTo quantify population preferences for attributes of public primary care services for hypertension.Design, setting, and participantsThis cross-sectional study involved administration of a household survey to a population-based sample of adults with hypertension in the Bengaluru Nagara district (Bengaluru City; urban setting) and the Kolar district (rural setting) in the state of Karnataka, India, from June 22 to July 27, 2021. A discrete choice experiment was designed in which participants selected preferred primary care clinic attributes from hypothetical alternatives. Eligible participants were 30 years or older with a previous diagnosis of hypertension or with measured diastolic blood pressure of 90 mm Hg or higher or systolic blood pressure of 140 mm Hg or higher. A total of 1422 of 1927 individuals (73.8%) consented to receive initial screening, and 1150 (80.9%) were eligible for participation, with 1085 (94.3%) of those eligible completing the survey.Main outcomes and measuresRelative preference for health care service attributes and preference class derived from respondents selecting a preferred clinic scenario from 8 sets of hypothetical comparisons based on wait time, staff courtesy, clinician type, carefulness of clinical assessment, and availability of free medication.ResultsAmong 1085 adult respondents with hypertension, the mean (SD) age was 54.4 (11.2) years; 573 participants (52.8%) identified as female, and 918 (84.6%) had a previous diagnosis of hypertension. Overall preferences were for careful clinical assessment and consistent availability of free medication; 3 of 5 latent classes prioritized 1 or both of these attributes, accounting for 85.1% of all respondents. However, the largest class (52.4% of respondents) had weak preferences distributed across all attributes (largest relative utility for careful clinical assessment: β = 0.13; 95% CI, 0.06-0.20; 36.4% preference share). Two small classes had strong preferences; 1 class (5.4% of respondents) prioritized shorter wait time (85.1% preference share; utility, β = -3.04; 95% CI, -4.94 to -1.14); the posterior probability of membership in this class was higher among urban vs rural respondents (mean [SD], 0.09 [0.26] vs 0.02 [0.13]). The other class (9.5% of respondents) prioritized seeing a physician (the term doctor was used in the survey) rather than a nurse (66.2% preference share; utility, β = 4.01; 95% CI, 2.76-5.25); the posterior probability of membership in this class was greater among rural vs urban respondents (mean [SD], 0.17 [0.35] vs 0.02 [0.10]).Conclusions and relevanceIn this study, stated population preferences suggested that consistent medication availability and quality of clinical assessment should be prioritized in primary care services in Karnataka, India. The heterogeneity observed in population preferences supports considering additional models of care, such as fast-track medication dispensing to reduce wait times in urban settings and physician-led services in rural areas.

BACKGROUND: Peroxisome proliferator-activated receptor agonists such as fibrates restore oxidative metabolism in cytotoxic T-lymphocytes, thereby enhancing response to immune checkpoint inhibitors (ICI) in preclinical models. However, there is no evidence in humans on the clinical impact of fibrates as an adjunct to ICI. METHODS: In this cohort study of Veterans with non-small cell lung cancer (NSCLC) receiving ICI, fibrate exposure was defined as a prescription filled within 90 days of an ICI infusion. Overall survival (OS), measured from the start of ICI, was compared between exposed and unexposed Veterans. Cox multivariable analysis (MVA) was used to identify factors associated with OS. A sensitivity analysis of Veterans with stage IV NSCLC who received docetaxel without ICI was similarly performed. RESULTS: The ICI cohort included 3593 Veterans, of whom 301 (8.5%) coincidentally received a fibrate. Veterans receiving fibrates were more likely to be older, white, male, and married, and to have greater comorbidity burden, but less likely to receive chemotherapy. Coincidental fibrates were associated with improved OS both on MVA (HR 0.86, 95%CI 0.75-0.99) and in a matched subset (HR 0.75, 95%CI 0.63-0.90). In contrast, among the cohort of 968 Veterans treated with chemotherapy, fibrates did not have a significant impact on OS by MVA (HR 0.99, 95%CI 0.79-1.25) or in a matched subset (HR 1.02, 95%CI CI 0.75-1.39). CONCLUSIONS: Concomitant fibrates are associated with improved OS among NSCLC patients receiving ICI but not among those receiving chemotherapy. This hypothesis-generating observation supports a potential role for fibrates as an adjunct to immunotherapy.

Direct-acting antivirals are needed to combat coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The papain-like protease (PLpro) domain of Nsp3 from SARS-CoV-2 is essential for viral replication. In addition, PLpro dysregulates the host immune response by cleaving ubiquitin and interferon-stimulated gene 15 protein from host proteins. As a result, PLpro is a promising target for inhibition by small-molecule therapeutics. Here we design a series of covalent inhibitors by introducing a peptidomimetic linker and reactive electrophile onto analogs of the noncovalent PLpro inhibitor GRL0617. The most potent compound inhibits PLpro with kinact/KI = 9,600 M-1 s-1, achieves sub-μM EC50 values against three SARS-CoV-2 variants in mammalian cell lines, and does not inhibit a panel of human deubiquitinases (DUBs) at >30 μM concentrations of inhibitor. An X-ray co-crystal structure of the compound bound to PLpro validates our design strategy and establishes the molecular basis for covalent inhibition and selectivity against structurally similar human DUBs. These findings present an opportunity for further development of covalent PLpro inhibitors.

Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this next step are 'omics' technologies, which enable high-throughput characterization and quantification of biological molecules, and subsequent integration of genomics with these omics datasets, a field referred to as systems genomics. Single cell sequencing studies of the retina and choroid demonstrated that the majority of candidate AMD genes identified through genomic studies are expressed in non-neuronal cells, such as the retinal pigment epithelium (RPE), glia, myeloid and choroidal cells, highlighting that many different retinal and choroidal cell types contribute to the pathogenesis of AMD. Expression quantitative trait locus (eQTL) studies in retinal tissue have identified putative causal genes by demonstrating a genetic overlap between gene regulation and AMD risk. Linking genetic data to complement measurements in the systemic circulation has aided in understanding the effect of AMD-associated genetic variants in the complement system, and supports that protein QTL (pQTL) studies in plasma or serum samples may aid in understanding the effect of genetic variants and pinpointing causal genes in AMD. A recent epigenomic study fine-mapped AMD causal variants by determing regulatory regions in RPE cells differentiated from induced pluripotent stem cells (iPSC-RPE). Another approach that is being employed to pinpoint causal AMD genes is to produce synthetic DNA assemblons representing risk and protective haplotypes, which are then delivered to cellular or animal model systems. Pinpointing causal genes and understanding disease mechanisms is crucial for the next step towards clinical translation. Clinical trials targeting proteins encoded by the AMD-associated genomic loci C3, CFB, CFI, CFH, and ARMS2/HTRA1 are currently ongoing, and a phase III clinical trial for C3 inhibition recently showed a modest reduction of lesion growth in geographic atrophy. The EYERISK consortium recently developed a genetic test for AMD that allows genotyping of common and rare variants in AMD-associated genes. Polygenic risk scores (PRS) were applied to quantify AMD genetic risk, and may aid in predicting AMD progression. In conclusion, genomic studies represent a turning point in our exploration of AMD. The results of those studies now serve as a driving force for several clinical trials. Expanding to omics and systems genomics will further decipher function and causality from the associations that have been reported, and will enable the development of therapies that will lessen the burden of AMD.

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

BACKGROUND: The management and outcomes of patients diagnosed with acute pulmonary embolism in primary care have not been characterized. OBJECTIVE: To describe 30-day outcomes stratified by initial site-of-care decisions DESIGN: Multicenter retrospective cohort study PARTICIPANTS: Adults diagnosed with acute pulmonary embolism in primary care in a large, diverse community-based US health system (2013-2019) MAIN MEASURES: The primary outcome was a composite of 30-day serious adverse events (recurrent venous thromboembolism, major bleeding, and all-cause mortality). The secondary outcome was 7-day pulmonary embolism-related hospitalization, either initial or delayed. KEY RESULTS: Among 652 patient encounters (from 646 patients), median age was 64 years; 51.5% were male and 70.7% identified as non-Hispanic white. Overall, 134 cases (20.6%) were sent home from primary care and 518 cases (79.4%) were initially referred to the emergency department (ED) or hospital. Among the referred, 196 (37.8%) were discharged home from the ED without events. Eight patients (1.2%; 95% CI 0.5-2.4%) experienced a 30-day serious adverse event: 4 venous thromboemboli (0.6%), 1 major bleed (0.2%), and 3 deaths (0.5%). Seven of these patients were initially hospitalized, and 1 had been sent home from primary care. All 3 deaths occurred in patients with known metastatic cancer initially referred to the ED, hospitalized, then enrolled in hospice following discharge. Overall, 328 patients (50.3%) were hospitalized within 7 days: 322 at the time of the index diagnosis and 6 following initial outpatient management (4 clinic-only and 2 clinic-plus-ED patients). CONCLUSIONS: Patients diagnosed with acute pulmonary embolism in this primary care setting uncommonly experienced 30-day adverse events, regardless of initial site-of-care decisions. Over 20% were managed comprehensively by primary care. Delayed 7-day pulmonary embolism-related hospitalization was rare among the 51% treated as outpatients. Primary care management of acute pulmonary embolism appears to be safe and could have implications for cost-effectiveness and patient care experience.

Schizophrenia and states induced by certain psychotomimetic drugs may share some physiological and phenomenological properties, but they differ in fundamental ways: one is a crippling chronic mental disease, while the others are temporary, pharmacologically-induced states presently being explored as treatments for mental illnesses. Building towards a deeper understanding of these different alterations of normal consciousness, here we compare the changes in neural dynamics induced by LSD and ketamine (in healthy volunteers) against those associated with schizophrenia, as observed in resting-state M/EEG recordings. While both conditions exhibit increased neural signal diversity, our findings reveal that this is accompanied by an increased transfer entropy from the front to the back of the brain in schizophrenia, versus an overall reduction under the two drugs. Furthermore, we show that these effects can be reproduced via different alterations of standard Bayesian inference applied on a computational model based on the predictive processing framework. In particular, the effects observed under the drugs are modelled as a reduction of the precision of the priors, while the effects of schizophrenia correspond to an increased precision of sensory information. These findings shed new light on the similarities and differences between schizophrenia and two psychotomimetic drug states, and have potential implications for the study of consciousness and future mental health treatments.

SignificanceOral cancer is one of the most prevalent cancers, especially in middle- and low-income countries such as India. Automatic segmentation of oral cancer images can improve the diagnostic workflow, which is a significant task in oral cancer image analysis. Despite the remarkable success of deep-learning networks in medical segmentation, they rarely provide uncertainty quantification for their output.AimWe aim to estimate uncertainty in a deep-learning approach to semantic segmentation of oral cancer images and to improve the accuracy and reliability of predictions.ApproachThis work introduced a UNet-based Bayesian deep-learning (BDL) model to segment potentially malignant and malignant lesion areas in the oral cavity. The model can quantify uncertainty in predictions. We also developed an efficient model that increased the inference speed, which is almost six times smaller and two times faster (inference speed) than the original UNet. The dataset in this study was collected using our customized screening platform and was annotated by oral oncology specialists.ResultsThe proposed approach achieved good segmentation performance as well as good uncertainty estimation performance. In the experiments, we observed an improvement in pixel accuracy and mean intersection over union by removing uncertain pixels. This result reflects that the model provided less accurate predictions in uncertain areas that may need more attention and further inspection. The experiments also showed that with some performance compromises, the efficient model reduced computation time and model size, which expands the potential for implementation on portable devices used in resource-limited settings.ConclusionsOur study demonstrates the UNet-based BDL model not only can perform potentially malignant and malignant oral lesion segmentation, but also can provide informative pixel-level uncertainty estimation. With this extra uncertainty information, the accuracy and reliability of the model’s prediction can be improved.

In October 2020, the National Cancer Institute (NCI) Serological Sciences Network (SeroNet) was established to study the immune response to COVID-19, and "to develop, validate, improve, and implement serological testing and associated technologies" (https://www.cancer.gov/research/key-initiatives/covid-19/coronavirus-research-initiatives/serological-sciences-network). SeroNet is comprised of 25 participating research institutions partnering with the Frederick National Laboratory for Cancer Research (FNLCR) and the SeroNet Coordinating Center. Since its inception, SeroNet has supported collaborative development and sharing of COVID-19 serological assay procedures and has set forth plans for assay harmonization. To facilitate collaboration and procedure sharing, a detailed survey was sent to collate comprehensive assay details and performance metrics on COVID-19 serological assays within SeroNet. In addition, FNLCR established a protocol to calibrate SeroNet serological assays to reference standards, such as the U.S. severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology standard reference material and first WHO international standard (IS) for anti-SARS-CoV-2 immunoglobulin (20/136), to facilitate harmonization of assay reporting units and cross-comparison of study data. SeroNet institutions reported development of a total of 27 enzyme-linked immunosorbent assay (ELISA) methods, 13 multiplex assays, and 9 neutralization assays and use of 12 different commercial serological methods. FNLCR developed a standardized protocol for SeroNet institutions to calibrate these diverse serological assays to reference standards. In conclusion, SeroNet institutions have established a diverse array of COVID-19 serological assays to study the immune response to SARS-CoV-2 and vaccines. Calibration of SeroNet serological assays to harmonize results reporting will facilitate future pooled data analyses and study cross-comparisons. IMPORTANCE SeroNet institutions have developed or implemented 61 diverse COVID-19 serological assays and are collaboratively working to harmonize these assays using reference materials to establish standardized reporting units. This will facilitate clinical interpretation of serology results and cross-comparison of research data.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This study was conducted to validate the accuracy of Convolutional-Neural-Network (CNN) enabled m(mobile)-Health device deployed with FHWs for delineation of suspicious oral lesions (malignant/potentially-malignant disorders). The effectiveness of the device was tested in tertiary-care hospitals and low-resource settings in India. The subjects were screened independently, either by FHWs alone or along with specialists. All the subjects were also remotely evaluated by oral cancer specialist/s. The program screened 5025 subjects (Images: 32,128) with 95% (n = 4728) having telediagnosis. Among the 16% (n = 752) assessed by onsite specialists, 20% (n = 102) underwent biopsy. Simple and complex CNN were integrated into the mobile phone and cloud respectively. The onsite specialist diagnosis showed a high sensitivity (94%), when compared to histology, while telediagnosis showed high accuracy in comparison with onsite specialists (sensitivity: 95%; specificity: 84%). FHWs, however, when compared with telediagnosis, identified suspicious lesions with less sensitivity (60%). Phone integrated, CNN (MobileNet) accurately delineated lesions (n = 1416; sensitivity: 82%) and Cloud-based CNN (VGG19) had higher accuracy (sensitivity: 87%) with tele-diagnosis as reference standard. The results of the study suggest that an automated mHealth-enabled, dual-image system is a useful triaging tool and empowers FHWs for oral cancer screening in low-resource settings.

To understand reinfection rates and correlates of protection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we established eight different longitudinal cohorts in 2020 under the umbrella of the PARIS (Protection Associated with Rapid Immunity to SARS-CoV-2)/SPARTA (SARS SeroPrevalence And Respiratory Tract Assessment) studies. Here, we describe the PARIS/SPARTA cohorts, the harmonized assays and analysis that are performed across the cohorts, as well as case definitions for SARS-CoV-2 infection and reinfection that have been established by the team of PARIS/SPARTA investigators. IMPORTANCE Determining reinfection rates and correlates of protection against SARS-CoV-2 infection induced by both natural infection and vaccination is of high significance for the prevention and control of coronavirus disease 2019 (COVID-19). Furthermore, understanding reinfections or infection after vaccination and the role immune escape plays in these scenarios will inform the need for updates of the current SARS-CoV-2 vaccines and help update guidelines suitable for the postpandemic world.

Astrocytes respond to injury and disease in the central nervous system with reactive changes that influence the outcome of the disorder1-4. These changes include differentially expressed genes (DEGs) whose contextual diversity and regulation are poorly understood. Here we combined biological and informatic analyses, including RNA sequencing, protein detection, assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and conditional gene deletion, to predict transcriptional regulators that differentially control more than 12,000 DEGs that are potentially associated with astrocyte reactivity across diverse central nervous system disorders in mice and humans. DEGs associated with astrocyte reactivity exhibited pronounced heterogeneity across disorders. Transcriptional regulators also exhibited disorder-specific differences, but a core group of 61 transcriptional regulators was identified as common across multiple disorders in both species. We show experimentally that DEG diversity is determined by combinatorial, context-specific interactions between transcriptional regulators. Notably, the same reactivity transcriptional regulators can regulate markedly different DEG cohorts in different disorders; changes in the access of transcriptional regulators to DNA-binding motifs differ markedly across disorders; and DEG changes can crucially require multiple reactivity transcriptional regulators. We show that, by modulating reactivity, transcriptional regulators can substantially alter disorder outcome, implicating them as therapeutic targets. We provide searchable resources of disorder-related reactive astrocyte DEGs and their predicted transcriptional regulators. Our findings show that transcriptional changes associated with astrocyte reactivity are highly heterogeneous and are customized from vast numbers of potential DEGs through context-specific combinatorial transcriptional-regulator interactions.

BackgroundPatients undergoing surgery for early stage non-small cell lung cancer (NSCLC) may be at high risk for postoperative mortality. Access to stereotactic body radiation therapy (SBRT) may facilitate more appropriate patient selection for surgery.Research questionIs postoperative mortality associated with early stage NSCLC lower at facilities with higher use of SBRT?Study design and methodsPatients with early stage NSCLC reported to the National Cancer Database between 2004 and 2015 were included. Use of SBRT was defined by each facility's SBRT experience (in years) and SBRT to surgery volume ratios. Multivariate logistic regression was used to test for the associations between SBRT use and postoperative mortality.ResultsThe study cohort consisted of 202,542 patients who underwent surgical resection of cT1-T2N0M0 NSCLC tumors. The 90-day postoperative mortality rate declined during the study period from 4.6% to 2.6% (P < .001), the proportion of facilities that used SBRT increased from 4.6% to 77.5% (P < .001), and the proportion of patients treated with SBRT increased from 0.7% to 15.4% (P < .001). On multivariate analysis, lower 90-day postoperative mortality rates were observed at facilities with > 6 years of SBRT experience (OR, 0.84; 95% CI, 0.76-0.94; P = .003) and SBRT to surgery volume ratios of more than 17% (OR, 0.85; 95% CI, 0.79-0.92; P < .001). Ninety-day mortality also was associated with surgical volume, region, year, age, sex, and race, among other covariates. Interaction testing between these covariates showed negative results.InterpretationPatients who underwent resection for early stage NSCLC at facilities with higher SBRT use showed lower rates of postoperative mortality. These findings suggest that the availability and use of SBRT may improve the selection of patients for surgery who are predicted to be at high risk of postoperative mortality.

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.

Nature evolves molecular interaction networks through persistent perturbation and selection, in stark contrast to drug discovery, which evaluates candidates one at a time by screening. Here, nature's highly parallel ligand-target search paradigm is recapitulated in a screen of a DNA-encoded library (DEL; 73,728 ligands) against a library of RNA structures (4,096 targets). In total, the screen evaluated ∼300 million interactions and identified numerous bona fide ligand-RNA three-dimensional fold target pairs. One of the discovered ligands bound a 5'GAG/3'CCC internal loop that is present in primary microRNA-27a (pri-miR-27a), the oncogenic precursor of microRNA-27a. The DEL-derived pri-miR-27a ligand was cell active, potently and selectively inhibiting pri-miR-27a processing to reprogram gene expression and halt an otherwise invasive phenotype in triple-negative breast cancer cells. By exploiting evolutionary principles at the earliest stages of drug discovery, it is possible to identify high-affinity and selective target-ligand interactions and predict engagements in cells that short circuit disease pathways in preclinical disease models.

The choroid plexus secretes cerebrospinal fluid and is critical for the development and function of the brain. In the telencephalon, the choroid plexus epithelium arises from the Wnt- expressing cortical hem. Canonical Wnt signaling pathway molecules such as nuclear β-CATENIN are expressed in the mouse and human embryonic choroid plexus epithelium indicating that this pathway is active. Point mutations in human β-CATENIN are known to result in the constitutive activation of canonical Wnt signaling. In a mouse model that recapitulates this perturbation, we report a loss of choroid plexus epithelial identity and an apparent transformation of this tissue to a neuronal identity. Aspects of this phenomenon are recapitulated in human embryonic stem cell derived organoids. The choroid plexus is also disrupted when β-Catenin is conditionally inactivated. Together, our results indicate that canonical Wnt signaling is required in a precise and regulated manner for normal choroid plexus development in the mammalian brain.

Robotics and autonomous systems are reshaping the world, changing healthcare, food production and biodiversity management. While they will play a fundamental role in delivering the UN Sustainable Development Goals, associated opportunities and threats are yet to be considered systematically. We report on a horizon scan evaluating robotics and autonomous systems impact on all Sustainable Development Goals, involving 102 experts from around the world. Robotics and autonomous systems are likely to transform how the Sustainable Development Goals are achieved, through replacing and supporting human activities, fostering innovation, enhancing remote access and improving monitoring. Emerging threats relate to reinforcing inequalities, exacerbating environmental change, diverting resources from tried-and-tested solutions and reducing freedom and privacy through inadequate governance. Although predicting future impacts of robotics and autonomous systems on the Sustainable Development Goals is difficult, thoroughly examining technological developments early is essential to prevent unintended detrimental consequences. Additionally, robotics and autonomous systems should be considered explicitly when developing future iterations of the Sustainable Development Goals to avoid reversing progress or exacerbating inequalities.

Universal drug susceptibility testing (DST) for tuberculosis is a major goal of the END TB strategy. PCR-based molecular diagnostic tests have been instrumental in increasing DST globally and several assays have now been endorsed by the World Health Organization (WHO) for use in the diagnosis of drug resistance. These endorsed assays, however, each interrogate a limited number of mutations associated with resistance, potentially limiting their sensitivity compared to sequencing-based methods. We applied an in silico method to compare the sensitivity and specificity of WHO-endorsed molecular based diagnostics to the mutation set identified by the WHO mutations catalogue using phenotypic DST as the reference. We found that, in silico, the mutation sets used by probe-based molecular diagnostic tests to identify rifampicin, isoniazid, pyrazinamide, levofloxacin, moxifloxacin, amikacin, capreomycin and kanamycin resistance produced similar sensitivities and specificities to the WHO mutation catalogue. PCR-based diagnostic tests were most sensitive for drugs where mechanisms of resistance are well established and localised to small genetic regions or a few prevalent mutations. Approaches using sequencing technologies can provide advantages for drugs where our knowledge of resistance is limited, or where complex resistance signatures exist.

Section headClinical/translational cancer immunotherapy.BackgroundThe goal of this study was to estimate the objective response rate for utomilumab in adults with immune checkpoint inhibitor (ICI)-refractory melanoma and non-small-cell lung cancer (NSCLC).MethodsUtomilumab was dosed intravenously every 4 weeks (Q4W) and adverse events (AEs) monitored. Tumor responses by RECIST1.1 were assessed by baseline and on-treatment scans. Tumor biopsies were collected for detection of programmed cell death ligand 1, CD8, 4-1BB, perforin, and granzyme B, and gene expression analyzed by next-generation sequencing. CD8+ T cells from healthy donors were stimulated with anti-CD3 ± utomilumab and compared with control.ResultsPatients with melanoma (n=43) and NSCLC (n=20) received utomilumab 0.24 mg/kg (n=36), 1.2 mg/kg (n=26), or 10 mg/kg (n=1). Treatment-emergent AEs (TEAEs) occurred in 55 (87.3%) patients and serious TEAEs in 18 (28.6%). Five (7.9%) patients discontinued owing to TEAEs. Thirty-two (50.8%) patients experienced treatment-related AEs, mostly grade 1-2. Objective response rate: 2.3% in patients with melanoma; no confirmed responses for patients with NSCLC. Ten patients each with melanoma (23.3%) or NSCLC (50%) had stable disease; respective median (95% confidence interval, CI) progression-free survival was 1.8 (1.7-1.9) and 3.6 (1.6-6.5) months. Utomilumab exposure increased with dose. The incidences of antidrug and neutralizing antibodies were 46.3% and 19.4%, respectively. Efficacy was associated with immune-active tumor microenvironments, and pharmacodynamic activity appeared to be blunted at higher doses.ConclusionsUtomilumab was well tolerated, but antitumor activity was low in patients who previously progressed on ICIs. The potential of 4-1BB agonists requires additional study to optimize efficacy while maintaining the tolerable safety profile.

Loss of lean muscle mass impairs immunity and increases mortality risk among individuals with HIV/AIDS. We evaluated the relative contributions of protein supplementation and nutrition education on body composition among 600 women living with HIV/AIDS in rural Andhra Pradesh, India. We conducted a cluster randomized controlled 2 × 2 factorial trial lasting six months with follow up at twelve and eighteen months. Interventions occurred in the Nellore and Prakasam regions of Andhra Pradesh by trained village women, ASHA (Accredited Social Health Activists), and included: (1) the usual supportive care from ASHA (UC); (2) UC plus nutrition education (NE); (3) UC plus nutritional protein supplementation (NS); (4) combined UC plus NE plus NS. A Bioimpedance Analyzer Model 310e measured body composition. SAS 9.4 analyzed all data. Mixed models using repeated measures evaluated lean mass change from baseline as primary and fat weight and total weight as secondary outcomes. Lean mass change was significantly associated with NS (p = 0.0001), NE (p = 0.0001), and combined NS plus NE (p = 0.0001), with similar associations for secondary outcomes. Stronger associations for total weight were observed with greater ART adherence. Nutritional interventions may improve physiologic response to HIV. Significant increases in lean mass resulted from independent and combined protein supplementation and nutrition education.

How environmental cues influence peroxisome proliferation, particularly through organelles, remains largely unknown. Yeast peroxisomes metabolize fatty acids (FA), and methylotrophic yeasts also metabolize methanol. NADH and acetyl-CoA, produced by these pathways enter mitochondria for ATP production and for anabolic reactions. During the metabolism of FA and/or methanol, the mitochondrial oxidative phosphorylation (OXPHOS) pathway accepts NADH for ATP production and maintains cellular redox balance. Remarkably, peroxisome proliferation in Pichia pastoris was abolished in NADH-shuttling- and OXPHOS mutants affecting complex I or III, or by the mitochondrial uncoupler, 2,4-dinitrophenol (DNP), indicating ATP depletion causes the phenotype. We show that mitochondrial OXPHOS deficiency inhibits expression of several peroxisomal proteins implicated in FA and methanol metabolism, as well as in peroxisome division and proliferation. These genes are regulated by the Snf1 complex (SNF1), a pathway generally activated by a high AMP/ATP ratio. In OXPHOS mutants, Snf1 is activated by phosphorylation, but Gal83, its interacting subunit, fails to translocate to the nucleus. Phenotypic defects in peroxisome proliferation observed in the OXPHOS mutants, and phenocopied by the Δgal83 mutant, were rescued by deletion of three transcriptional repressor genes (MIG1, MIG2, and NRG1) controlled by SNF1 signaling. Our results are interpreted in terms of a mechanism by which peroxisomal and mitochondrial proteins and/or metabolites influence redox and energy metabolism, while also influencing peroxisome biogenesis and proliferation, thereby exemplifying interorganellar communication and interplay involving peroxisomes, mitochondria, cytosol, and the nucleus. We discuss the physiological relevance of this work in the context of human OXPHOS deficiencies.

Pex11, an abundant peroxisomal membrane protein (PMP), is required for division of peroxisomes and is robustly imported to peroxisomal membranes. We present a comprehensive analysis of how the Pichia pastoris Pex11 is recognized and chaperoned by Pex19, targeted to peroxisome membranes and inserted therein. We demonstrate that Pex11 contains one Pex19-binding site (Pex19-BS) that is required for Pex11 insertion into peroxisomal membranes by Pex19, but is non-essential for peroxisomal trafficking. We provide extensive mutational analyses regarding the recognition of Pex19-BS in Pex11 by Pex19. Pex11 also has a second, Pex19-independent membrane peroxisome-targeting signal (mPTS) that is preserved among Pex11-family proteins and anchors the human HsPex11γ to the outer leaflet of the peroxisomal membrane. Thus, unlike most PMPs, Pex11 can use two mechanisms of transport to peroxisomes, where only one of them depends on its direct interaction with Pex19, but the other does not. However, Pex19 is necessary for membrane insertion of Pex11. We show that Pex11 can self-interact, using both homo- and/or heterotypic interactions involving its N-terminal helical domains. We demonstrate that Pex19 acts as a chaperone by interacting with the Pex19-BS in Pex11, thereby protecting Pex11 from spontaneous oligomerization that would otherwise cause its aggregation and subsequent degradation.

SignificanceConvolutional neural networks (CNNs) show the potential for automated classification of different cancer lesions. However, their lack of interpretability and explainability makes CNNs less than understandable. Furthermore, CNNs may incorrectly concentrate on other areas surrounding the salient object, rather than the network's attention focusing directly on the object to be recognized, as the network has no incentive to focus solely on the correct subjects to be detected. This inhibits the reliability of CNNs, especially for biomedical applications.AimDevelop a deep learning training approach that could provide understandability to its predictions and directly guide the network to concentrate its attention and accurately delineate cancerous regions of the image.ApproachWe utilized Selvaraju et al.'s gradient-weighted class activation mapping to inject interpretability and explainability into CNNs. We adopted a two-stage training process with data augmentation techniques and Li et al.'s guided attention inference network (GAIN) to train images captured using our customized mobile oral screening devices. The GAIN architecture consists of three streams of network training: classification stream, attention mining stream, and bounding box stream. By adopting the GAIN training architecture, we jointly optimized the classification and segmentation accuracy of our CNN by treating these attention maps as reliable priors to develop attention maps with more complete and accurate segmentation.ResultsThe network's attention map will help us to actively understand what the network is focusing on and looking at during its decision-making process. The results also show that the proposed method could guide the trained neural network to highlight and focus its attention on the correct lesion areas in the images when making a decision, rather than focusing its attention on relevant yet incorrect regions.ConclusionsWe demonstrate the effectiveness of our approach for more interpretable and reliable oral potentially malignant lesion and malignant lesion classification.

BackgroundThe large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression.MethodsWe analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants.ResultsWe found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections.ConclusionsThese data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.

The biogenesis of mammalian autophagosomes remains to be fully defined. Here, we used cellular and in vitro membrane fusion analyses to show that autophagosomes are formed from a hitherto unappreciated hybrid membrane compartment. The autophagic precursors emerge through fusion of FIP200 vesicles, derived from the cis-Golgi, with endosomally derived ATG16L1 membranes to generate a hybrid pre-autophagosomal structure, HyPAS. A previously unrecognized apparatus defined here controls HyPAS biogenesis and mammalian autophagosomal precursor membranes. HyPAS can be modulated by pharmacological agents whereas its formation is inhibited upon severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or by expression of SARS-CoV-2 nsp6. These findings reveal the origin of mammalian autophagosomal membranes, which emerge via convergence of secretory and endosomal pathways, and show that this process is targeted by microbial factors such as coronaviral membrane-modulating proteins.

SignificanceEarly detection of oral cancer is vital for high-risk patients, and machine learning-based automatic classification is ideal for disease screening. However, current datasets collected from high-risk populations are unbalanced and often have detrimental effects on the performance of classification.AimTo reduce the class bias caused by data imbalance.ApproachWe collected 3851 polarized white light cheek mucosa images using our customized oral cancer screening device. We use weight balancing, data augmentation, undersampling, focal loss, and ensemble methods to improve the neural network performance of oral cancer image classification with the imbalanced multi-class datasets captured from high-risk populations during oral cancer screening in low-resource settings.ResultsBy applying both data-level and algorithm-level approaches to the deep learning training process, the performance of the minority classes, which were difficult to distinguish at the beginning, has been improved. The accuracy of "premalignancy" class is also increased, which is ideal for screening applications.ConclusionsExperimental results show that the class bias induced by imbalanced oral cancer image datasets could be reduced using both data- and algorithm-level methods. Our study may provide an important basis for helping understand the influence of unbalanced datasets on oral cancer deep learning classifiers and how to mitigate.

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of individuals with ulcerative colitis (UC) require colectomy within 5 years of diagnosis, but polygenic risk scores (PRSs) utilizing findings from genome-wide association studies (GWASs) are unable to provide meaningful prediction of this adverse status. By contrast, in Crohn disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a transcriptional risk score (TRS). Here, we demonstrate that a measured TRS based on bulk rectal gene expression in the PROTECT inception cohort study has a positive predictive value approaching 50% for colectomy. Single-cell profiling demonstrates that the genes are active in multiple diverse cell types from both the epithelial and immune compartments. Expression quantitative trait locus (QTL) analysis identifies genes with differential effects at baseline and week 52 follow-up, but for the most part, differential expression associated with colectomy risk is independent of local genetic regulation. Nevertheless, a predicted polygenic transcriptional risk score (PPTRS) derived by summation of transcriptome-wide association study (TWAS) effects identifies UC-affected individuals at 5-fold elevated risk of colectomy with data from the UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with TWASs for stratification of risk of disease complications.

The integral membrane protein ATG9A plays a key role in autophagy. It displays a broad intracellular distribution and is present in numerous compartments, including the plasma membrane (PM). The reasons for the distribution of ATG9A to the PM and its role at the PM are not understood. Here, we show that ATG9A organizes, in concert with IQGAP1, components of the ESCRT system and uncover cooperation between ATG9A, IQGAP1 and ESCRTs in protection from PM damage. ESCRTs and ATG9A phenocopied each other in protection against PM injury. ATG9A knockouts sensitized the PM to permeabilization by a broad spectrum of microbial and endogenous agents, including gasdermin, MLKL and the MLKL-like action of coronavirus ORF3a. Thus, ATG9A engages IQGAP1 and the ESCRT system to maintain PM integrity.

Liquid biopsy is now considered a valuable diagnostic tool for advanced metastatic non-small cell lung cancer (NSCLC). In NSCLC, circulating tumor DNA (ctDNA) analysis has been shown to increase the chances of identifying the presence of targetable mutations and has been adopted by many clinicians owing to its low risk. Serial monitoring of ctDNA may also help assess the treatment response or for monitoring relapse. As the presence of detectable plasma ctDNA post-surgery likely indicates residual tumor burden, studies have been performed to quantify plasma ctDNA to assess minimal residual disease (MRD) in early-stage resected NSCLC. Most data on utilizing liquid biopsy for monitoring MRD in early-stage NSCLC are from small-scale studies using ctDNA. Here, we review the recent research on liquid biopsy in NSCLC, not limited to ctDNA, and focus on novel methods such as micro RNAs (miRNA) and long non-coding (lncRNA).

SignificanceOral cancer is among the most common cancers globally, especially in low- and middle-income countries. Early detection is the most effective way to reduce the mortality rate. Deep learning-based cancer image classification models usually need to be hosted on a computing server. However, internet connection is unreliable for screening in low-resource settings.AimTo develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection.ApproachThe dataset used in our study was captured among 5025 patients with our customized dual-modality mobile oral screening devices. We trained an efficient network MobileNet with focal loss and converted the model into TensorFlow Lite format. The finalized lite format model is ∼16.3  MB and ideal for smartphone platform operation. We have developed an Android smartphone application in an easy-to-use format that implements the mobile-based dual-modality image classification approach to distinguish oral potentially malignant and malignant images from normal/benign images.ResultsWe investigated the accuracy and running speed on a cost-effective smartphone computing platform. It takes ∼300  ms to process one image pair with the Moto G5 Android smartphone. We tested the proposed method on a standalone dataset and achieved 81% accuracy for distinguishing normal/benign lesions from clinically suspicious lesions, using a gold standard of clinical impression based on the review of images by oral specialists.ConclusionsOur study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.

IntroductionLung-MAP S1400K was designed to evaluate the response to telisotuzumab vedotin, an antibody-drug conjugate targeting c-MET, in patients with c-MET-positive squamous cell carcinoma (SCC).Patients and methodsPatients with previously treated SCC with c-MET-positive tumors (H score ≥ 150, Ventana SP44 assay) were enrolled into 2 cohorts: Cohort 1 (immune checkpoint inhibitor-naive) and Cohort 2 (immune checkpoint inhibitor refractory). Telisotuzumab vedotin 2.7 mg/kg was administered intravenously every 3 weeks until disease progression or unacceptable toxicity. Response assessments were performed every 6 weeks. The primary endpoint was response by Response Evaluation Criteria in Solid Tumors (RECIST) v1.1. Secondary endpoints included progression-free survival, overall survival, response within cohort, duration of response, and toxicities. Interim analysis was planned after 20 evaluable patients, with ≥ 3 responses needed to continue enrollment.ResultsForty-nine patients (14% of screened patients) were assigned to S1400K, 28 patients enrolled (15 in Cohort 1 and 13 in Cohort 2), and 23 were eligible. S1400K closed on December 21, 2018 owing to lack of efficacy. Two responses (response rate of 9%; 95% confidence interval, 0%-20%) were reported in cohort 1 (1 complete and 1 unconfirmed partial response), whereas 10 patients had stable disease, with a disease control rate of 52%. The median overall and progression-free survival was 5.6 and 2.4 months, respectively. There were 3 grade 5 events (2 pneumonitis, in Cohort 2, and 1 bronchopulmonary hemorrhage, in Cohort 1).ConclusionTelisotuzumab vedotin failed to meet the pre-specified response needed to justify continuing enrollment to S1400K. Pneumonitis was an unanticipated toxicity observed in patients with SCC.

Whether or not populations diverge with respect to the genetic contribution to risk of specific complex diseases is relevant to understanding the evolution of susceptibility and origins of health disparities. Here, we describe a large-scale whole-genome sequencing study of inflammatory bowel disease encompassing 1,774 affected individuals and 1,644 healthy control Americans with African ancestry (African Americans). Although no new loci for inflammatory bowel disease are discovered at genome-wide significance levels, we identify numerous instances of differential effect sizes in combination with divergent allele frequencies. For example, the major effect at PTGER4 fine maps to a single credible interval of 22 SNPs corresponding to one of four independent associations at the locus in European ancestry individuals but with an elevated odds ratio for Crohn disease in African Americans. A rare variant aggregate analysis implicates Ca2+-binding neuro-immunomodulator CALB2 in ulcerative colitis. Highly significant overall overlap of common variant risk for inflammatory bowel disease susceptibility between individuals with African and European ancestries was observed, with 41 of 241 previously known lead variants replicated and overall correlations in effect sizes of 0.68 for combined inflammatory bowel disease. Nevertheless, subtle differences influence the performance of polygenic risk scores, and we show that ancestry-appropriate weights significantly improve polygenic prediction in the highest percentiles of risk. The median amount of variance explained per locus remains the same in African and European cohorts, providing evidence for compensation of effect sizes as allele frequencies diverge, as expected under a highly polygenic model of disease.

AbstractDespite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.

Recent developments in three-dimensional (3D) printing technology offer immense potential in fabricating scaffolds and implants for various biomedical applications, especially for bone repair and regeneration. As the availability of autologous bone sources and commercial products is limited and surgical methods do not help in complete regeneration, it is necessary to develop alternative approaches for repairing large segmental bone defects. The 3D printing technology can effectively integrate different types of living cells within a 3D construct made up of conventional micro- or nanoscale biomaterials to create an artificial bone graft capable of regenerating the damaged tissues. This article reviews the developments and applications of 3D printing in bone tissue engineering and highlights the numerous conventional biomaterials and nanomaterials that have been used in the production of 3D-printed scaffolds. A comprehensive overview of the 3D printing methods such as stereolithography (SLA), selective laser sintering (SLS), fused deposition modeling (FDM), and ink-jet 3D printing, and their technical and clinical applications in bone repair and regeneration has been provided. The review is expected to be useful for readers to gain an insight into the state-of-the-art of 3D printing of bone substitutes and their translational perspectives.

ObjectiveThe purpose of this report is to provide insight from pediatric stakeholders with a shared desire to facilitate a revision of the current United States regulatory pathways for the development of pediatric healthcare devices.MethodsOn August 5, 2020, a group of innovators, engineers, professors and clinicians met to discuss challenges and opportunities for the development of new medical devices for pediatric health and the importance of creating a regulatory environment that encourages and accelerates the research and development of such devices. On January 6, 2021, this group joined regulatory experts at a follow-up meeting.ResultsOne of the primary issues identified was the need to present decision-makers with opportunities that change the return-on-investment balance between adult and pediatric devices to promote investment in pediatric devices.Discussion/conclusionSeveral proposed strategies were discussed, and these strategies can be divided into two broad categories: 1. Removal of real and perceived barriers to pediatric device innovation; 2. Increasing incentives for pediatric device innovation.

WNT proteins are secreted symmetry breaking signals that interact with cell surface receptors of the FZD family to regulate a multitude of developmental processes. Studying selectivity between WNTs and FZDs has been hampered by the paucity of purified WNT proteins and by their apparent non-selective interactions with the FZD receptors. Here, we describe an engineered protein, called F7L6, comprised of antibody-derived single-chain variable fragments, that selectively binds to human FZD7 and the co-receptor LRP6. F7L6 potently activates WNT/β-catenin signaling in a manner similar to Wnt3a. In contrast to Wnt3a, F7L6 engages only FZD7 and none of the other FZD proteins. Treatment of human pluripotent stem (hPS) cells with F7L6 initiates transcriptional programs similar to those observed during primitive streak formation and subsequent gastrulation in the mammalian embryo. This demonstrates that selective engagement and activation of FZD7 signaling is sufficient to promote mesendodermal differentiation of hPS cells.

In 2018, the American Board of Anesthesiology (ABA) became the first US medical specialty certifying board to incorporate an Objective Structured Clinical Examination (OSCE) into its initial certification examination system. Previously, the ABA's staged examination system consisted of 2 written examinations (the BASIC and ADVANCED examinations) and the Standardized Oral Examination (SOE). The OSCE and the existing SOE are now 2 separate components of the APPLIED Examination. This report presents the results of the first-year OSCE administration. A total of 1410 candidates took both the OSCE and the SOE in 2018. Candidate performance approximated a normal distribution for both the OSCE and the SOE, and was not associated with the timing of the examination, including day of the week, morning versus afternoon session, and order of the OSCE and the SOE. Practice-based Learning and Improvement was the most difficult station, while Application of Ultrasonography was the least difficult. The correlation coefficient between SOE and OSCE scores was 0.35 ([95% confidence interval {CI}, 0.30-0.39]; P < .001). Scores for the written ADVANCED Examination were modestly correlated with scores for the SOE (r = 0.29 [95% CI, 0.25-0.34]; P < .001) and the OSCE (r = 0.15 [95% CI, 0.10-0.20]; P < .001). Most of the candidates who failed the SOE passed the OSCE, and most of the candidates who failed the OSCE passed the SOE. Of the 1410 candidates, 77 (5.5%) failed the OSCE, 155 (11.0%) failed the SOE, and 25 (1.8%) failed both. Thus, 207 (14.7%) failed at least 1 component of the APPLIED Examination. Adding an OSCE to a board certification examination system is feasible. Preliminary evidence indicates that the OSCE measures aspects of candidate abilities distinct from those measured by other examinations used for initial board certification.

RationaleThe evidence for outpatient pulmonary embolism (PE) management apart from hospitalization is expanding. The availability and ease of direct oral anticoagulants have facilitated this transition. The literature, however, is sparse on the topic of comprehensive management of pulmonary embolism in the primary care clinic setting. As such, the role of the primary care physician in the complete diagnosis, risk stratification for outpatient eligibility, and initiation of treatment is unclear.Case presentationsCase 1: A 33-year-old man with known heterozygous Factor V Leiden mutation and a remote history of deep vein thrombosis presented to his primary care physician's office with 2 days of mild pleuritic chest pain and a dry cough after a recent transcontinental flight. Case 2: A 48-year-old man with a complex medical history including recent transverse myelitis presented to his primary care family physician with dyspnea and pleuritic chest pain for 6 days.DiagnosisCase 1: Computed tomographic pulmonary angiography that same afternoon showed multiple bilateral segmental and subsegmental emboli as well as several small pulmonary infarcts. Case 2: The patient's D-dimer was elevated at 1148 ng/mL. His physician ordered a computed tomographic pulmonary angiography, performed that evening, which showed segmental and subsegmental PE.InterventionsBoth patients were contacted by their respective physicians shortly after their diagnoses and, in shared decision-making, opted for treatment at home with 5 days of enoxaparin followed by dabigatran.OutcomesNeither patient developed recurrence nor complications in the subsequent 3 months.LessonsThese cases, stratified as low risk using the American College of Chest Physicians criteria and the PE Severity Index, are among the first in the literature to illustrate comprehensive primary care-based outpatient PE management. Care was provided within an integrated delivery system with ready, timely access to laboratory, advanced radiology, and allied health services. This report sets the stage for investigating the public health implications of comprehensive primary care-based PE management, including cost-savings as well as enhanced patient follow-up and patient satisfaction.