A Multimodal Generative AI Copilot for Human Pathology.

The field of computational pathology[1,2] has witnessed remarkable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders[3,4]. However, despite the explosive growth of generative artificial intelligence (AI), there has been limited study on building general purpose, multimodal AI assistants and copilots[5] tailored to pathology. Here we present PathChat, a vision-language generalist AI assistant for human pathology. We build PathChat by adapting a foundational vision encoder for pathology, combining it with a pretrained large language model and finetuning the whole system on over 456,000 diverse visual language instructions consisting of 999,202 question-answer turns. We compare PathChat against several multimodal vision language AI assistants and GPT4V, which powers the commercially available multimodal general purpose AI assistant ChatGPT-4[7]. PathChat achieved state-of-the-art performance on multiple-choice diagnostic questions from cases of diverse tissue origins and disease models. Furthermore, using open-ended questions and human expert evaluation, we found that overall PathChat produced more accurate and pathologist-preferable responses to diverse queries related to pathology. As an interactive and general vision-language AI Copilot that can flexibly handle both visual and natural language inputs, PathChat can potentially find impactful applications in pathology education, research, and human-in-the-loop clinical decision making.

Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior.

How cognitive task behavior is generated by brain network interactions is a central question in neuroscience. Answering this question calls for the development of novel analysis tools that can firstly capture neural signatures of task information with high spatial and temporal precision (the "where and when") and then allow for empirical testing of alternative network models of brain function that link information to behavior (the "how"). We outline a novel network modeling approach suited to this purpose that is applied to noninvasive functional neuroimaging data in humans. We first dynamically decoded the spatiotemporal signatures of task information in the human brain by combining MRI-individualized source electroencephalography (EEG) with multivariate pattern analysis (MVPA). A newly developed network modeling approach-dynamic activity flow modeling-then simulated the flow of task-evoked activity over more causally interpretable (relative to standard functional connectivity [FC] approaches) resting-state functional connections (dynamic, lagged, direct, and directional). We demonstrate the utility of this modeling approach by applying it to elucidate network processes underlying sensory-motor information flow in the brain, revealing accurate predictions of empirical response information dynamics underlying behavior. Extending the model toward simulating network lesions suggested a role for the cognitive control networks (CCNs) as primary drivers of response information flow, transitioning from early dorsal attention network-dominated sensory-to-response transformation to later collaborative CCN engagement during response selection. These results demonstrate the utility of the dynamic activity flow modeling approach in identifying the generative network processes underlying neurocognitive phenomena.

Precision Neoantigen Discovery Using Large-Scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation.

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past 2 decades. However, improvement in the accuracy of prediction algorithms is needed for clinical applications like the development of personalized cancer vaccines, the discovery of biomarkers for response to immunotherapies, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic Human Leukocyte Antigen (HLA) Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA allele to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.17-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

Adjunctive lumateperone (ITI-007) in the treatment of bipolar depression: Results from a randomized placebo-controlled clinical trial.

OBJECTIVE: This phase 3, randomized, double-blind, placebo-controlled study (NCT02600507) evaluated the efficacy and safety of lumateperone adjunctive therapy to lithium or valproate in patients with bipolar depression. METHODS: Patients (18-75 years) with bipolar I or bipolar II disorder experiencing a major depressive episode (MDE), with inadequate therapeutic response to lithium or valproate, were randomized 1:1:1 to 6 weeks adjunctive therapy with lumateperone 28 mg (n = 176), lumateperone 42 mg (n = 177), or placebo (n = 176). The primary and key secondary efficacy endpoints were change from baseline to Day 43 in Montgomery-Åsberg Depression Rating Scale (MADRS) Total score and the Clinical Global Impression Scale-Bipolar Version-Severity Scale (CGI-BP-S) depression subscore. Safety assessments included adverse events, laboratory evaluations, vital signs, extrapyramidal symptoms (EPS), and suicidality. RESULTS: Patients treated with adjunctive lumateperone 42 mg showed significantly greater improvement compared with adjunctive placebo in MADRS Total score (LS mean difference vs placebo [LSMD], -2.4; p = 0.02) and CGI-BP-S depression subscore (LSMD, -0.3; p = 0.01), while adjunctive lumateperone 28 mg showed numerical improvement in MADRS Total score (LSMD, -1.7; p = 0.10) and improvement in the CGI-BP-S depression subscore (LSMD, -0.3; p = 0.04). Adjunctive lumateperone treatment was well tolerated; treatment-emergent adverse events reported at rates >5% and twice placebo for lumateperone 42 mg were somnolence (11.3%), dizziness (10.7%), and nausea (8.5%), with minimal risk of EPS, metabolic abnormalities, or increased prolactin. CONCLUSIONS: Lumateperone 42-mg treatment adjunctive to lithium or valproate significantly improved depression symptoms and was generally well tolerated in patients with MDEs associated with either bipolar I or bipolar II disorder.

Precision Neoantigen Discovery Using Large-scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation.

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass-spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past two decades. However, improvement in the sensitivity and specificity of prediction algorithms is needed for clinical applications such as the development of personalized cancer vaccines, the discovery of biomarkers for response to checkpoint blockade, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic HLA Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA alleles to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC-binding pocket diversity in the training data and extend allelic coverage in under profiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.15-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

Community College Mental Health Navigators: A Pilot Program to Improve Access to Care.

The California Community College (CCC), the largest system of higher education and provider of workforce training in the nation, serves approximately 2.1 million students across its 116 campuses. CCCs work to reduce barriers to academic success by providing mental health services (MHS). However, CCCs provide MHS on a short-term model because of limited staffing and high demand with most campuses placing a restriction of six to eight sessions per academic term. A referral list of local agencies is typically provided for students who need continued care, though students often do not know how to explore options or navigate their health insurance benefits. During the 2020-2021 academic year, an MH navigator program was piloted at four community colleges in a San Francisco Bay Area county. Participants included 10 students with academic/career interests in social work, nursing, and the social sciences. Fall Semester 2020 focused on increasing students' knowledge on mental health topics, while Spring Semester 2021 focused on experiential learning through case management of student clients. The navigator pilot program showed promising results with navigators gaining practical experience and exposure to mental health careers while assisting their peers from campus-based to community-based care. Future efforts will focus on cultivating stronger relationships between navigators and MH liaisons. Doing so will help staff develop greater familiarity of the navigator's role, thus ensuring an increase in usage of its services and allowing the student-client a smoother transitioning experience from campus-based to community-based care.

A 4-tier Protocolized Radiological Classification System for Leaks Following Sleeve Gastrectomy.

OBJECTIVES: To develop and validate a classification of sleeve gastrectomy leaks able to reliably predict outcomes, from protocolized computed tomography (CT) findings and readily available variables. SUMMARY OF BACKGROUND DATA: Leaks post sleeve gastrectomy remain morbid and resource-consuming. Incidence, treatments, and outcomes are variable, representing heterogeneity of the problem. A predictive tool available at presentation would aid management and predict outcomes. METHODS: From a prospective database (2009-2018) we reviewed patients with staple line leaks. A Delphi process was undertaken on candidate variables (80-20). Correlations were performed to stratify 4 groupings based on outcomes (salvage resection, length of stay, and complications) and predictor variables. Training and validation cohorts were established by block randomization. RESULTS: A 4-tiered classification was developed based on CT appearance and duration postsurgery. Interobserver agreement was high (κ = 0.85, P < 0.001). There were 59 patients, (training: 30, validation: 29). Age 42.5 ± 10.8 versus 38.9 ± 10.0 years (P = 0.187); female 65.5% versus 80.0% (P = 0.211), weight 127.4 ± 31.3 versus 141.0 ± 47.9 kg, (P = 0.203). In the training group, there was a trend toward longer hospital stays as grading increased (I = 10.5 d; II = 24 d; III = 66.5 d; IV = 72 d; P = 0.005). Risk of salvage resection increased (risk ratio grade 4 = 9; P = 0.043) as did complication severity (P = 0.027).Findings were reproduced in the validation group: risk of salvage resection (P = 0.007), hospital stay (P = 0.001), complications (P = 0.016). CONCLUSION: We have developed and validated a classification system, based on protocolized CT imaging that predicts a step-wise increased risk of salvage resection, complication severity, and increased hospital stay. The system should aid patient management and facilitate comparisons of outcomes and efficacy of interventions.

Randomized controlled trial of geriatric consultation versus standard care in older adults with hematologic malignancies.

We conducted a randomized controlled trial in older adults with hematologic malignancies to determine the impact of geriatrician consultation embedded in our oncology clinic alongside standard care. From February 2015 to May 2018, transplant-ineligible patients aged ≥75 years who presented for initial consultation for lymphoma, leukemia, or multiple myeloma at Dana-Farber Cancer Institute (Boston, MA, USA) were eligible. Pre-frail and frail patients, classified based on phenotypic and deficit-accumulation approaches, were randomized to receive either standard oncologic care with or without consultation with a geriatrician. The primary outcome was 1-year overall survival. Secondary outcomes included unplanned care utilization within 6 months of follow-up and documented end-of-life (EOL) goals-of-care discussions. Clinicians were surveyed as to their impressions of geriatric consultation. One hundred sixty patients were randomized to either geriatric consultation plus standard care (n=60) or standard care alone (n=100). The median age of the patients was 80.4 years (standard deviation = 4.2). Of those randomized to geriatric consultation, 48 (80%) completed at least one visit with a geriatrician. Consultation did not improve survival at 1 year compared to standard care (difference: 2.9%, 95% confidence interval: -9.5% to 15.2%, P=0.65), and did not significantly reduce the incidence of emergency department visits, hospital admissions, or days in hospital. Consultation did improve the odds of having EOL goals-of-care discussions (odds ratio = 3.12, 95% confidence interval: 1.03 to 9.41) and was valued by surveyed hematologic-oncology clinicians, with 62.9%-88.2% of them rating consultation as useful in the management of several geriatric domains.

A systematic review and meta-analysis of the mental health symptoms during the Covid-19 pandemic in Southeast Asia.

AIMS: The Covid-19 pandemic has had a substantial impact on the mental health of the general public and high-risk groups worldwide. Due to its proximity and close links to China, Southeast Asia was one of the first regions to be affected by the outbreak. The aim of this systematic review was to evaluate the prevalence of anxiety, depression and insomnia in the general adult population and healthcare workers (HCWs) in Southeast Asia during the course of the first year of the pandemic. METHODS: Several literature databases were systemically searched for articles published up to February 2021 and two reviewers independently evaluated all relevant studies using pre-determined criteria. The prevalence rates of mental health symptoms were calculated using a random-effect meta-analysis model. RESULTS: In total, 32 samples from 25 studies with 20 352 participants were included. Anxiety was assessed in all 25 studies and depression in 15 studies with pooled prevalence rates of 22% and 16%, respectively. Only two studies assessed insomnia, which was estimated at 19%. The prevalence of anxiety and depression was similar among frontline HCWs (18%), general HCWs (17%), and students (20%) while being noticeably higher in the general population (27%). CONCLUSIONS: This is the first systematic review to investigate the mental health impact of the Covid-19 pandemic in Southeast Asia. A considerable proportion of the general population and HCWs reported mild to moderate symptoms of anxiety and depression; the pooled prevalence rater, however, remain significantly lower than those reported in other areas such as China and Europe.

CD40 agonistic monoclonal antibody APX005M (sotigalimab) and chemotherapy, with or without nivolumab, for the treatment of metastatic pancreatic adenocarcinoma: an open-label, multicentre, phase 1b study.

BACKGROUND: Standard chemotherapy remains inadequate in metastatic pancreatic adenocarcinoma. Combining an agonistic CD40 monoclonal antibody with chemotherapy induces T-cell-dependent tumour regression in mice and improves survival. In this study, we aimed to evaluate the safety of combining APX005M (sotigalimab) with gemcitabine plus nab-paclitaxel, with and without nivolumab, in patients with pancreatic adenocarcinoma to establish the recommended phase 2 dose. METHODS: This non-randomised, open-label, multicentre, four-cohort, phase 1b study was done at seven academic hospitals in the USA. Eligible patients were adults aged 18 years and older with untreated metastatic pancreatic adenocarcinoma, Eastern Cooperative Oncology Group performance status score of 0-1, and measurable disease by Response Evaluation Criteria in Solid Tumors version 1.1. All patients were treated with 1000 mg/m2 intravenous gemcitabine and 125 mg/m2 intravenous nab-paclitaxel. Patients received 0·1 mg/kg intravenous APX005M in cohorts B1 and C1 and 0·3 mg/kg in cohorts B2 and C2. In cohorts C1 and C2, patients also received 240 mg intravenous nivolumab. Primary endpoints comprised incidence of adverse events in all patients who received at least one dose of any study drug, incidence of dose-limiting toxicities (DLTs) in all patients who had a DLT or received at least two doses of gemcitabine plus nab-paclitaxel and one dose of APX005M during cycle 1, and establishing the recommended phase 2 dose of intravenous APX005M. Objective response rate in the DLT-evaluable population was a key secondary endpoint. This trial (PRINCE, PICI0002) is registered with ClinicalTrials.gov, NCT03214250 and is ongoing. FINDINGS: Between Aug 22, 2017, and July 10, 2018, of 42 patients screened, 30 patients were enrolled and received at least one dose of any study drug; 24 were DLT-evaluable with median follow-up 17·8 months (IQR 16·0-19·4; cohort B1 22·0 months [21·4-22·7], cohort B2 18·2 months [17·0-18·9], cohort C1 17·9 months [14·3-19·7], cohort C2 15·9 months [12·7-16·1]). Two DLTs, both febrile neutropenia, were observed, occurring in one patient each for cohorts B2 (grade 3) and C1 (grade 4). The most common grade 3-4 treatment-related adverse events were lymphocyte count decreased (20 [67%]; five in B1, seven in B2, four in C1, four in C2), anaemia (11 [37%]; two in B1, four in B2, four in C1, one in C2), and neutrophil count decreased (nine [30%]; three in B1, three in B2, one in C1, two in C2). 14 (47%) of 30 patients (four each in B1, B2, C1; two in C2) had a treatment-related serious adverse event. The most common serious adverse event was pyrexia (six [20%] of 30; one in B2, three in C1, two in C2). There were two chemotherapy-related deaths due to adverse events: one sepsis in B1 and one septic shock in C1. The recommended phase 2 dose of APX005M was 0·3 mg/kg. Responses were observed in 14 (58%) of 24 DLT-evaluable patients (four each in B1, C1, C2; two in B2). INTERPRETATION: APX005M and gemcitabine plus nab-paclitaxel, with or without nivolumab, is tolerable in metastatic pancreatic adenocarcinoma and shows clinical activity. If confirmed in later phase trials, this treatment regimen could replace chemotherapy-only standard of care in this population. FUNDING: Parker Institute for Cancer Immunotherapy, Cancer Research Institute, and Bristol Myers Squibb.

Gait speed, survival, and recommended treatment intensity in older adults with blood cancer requiring treatment.

BACKGROUND: Brief measures of physical function such as gait speed may be useful to optimize treatment intensity for older adults who have blood cancer; however, little is known about whether such assessments are already captured within oncologists' "gestalt" assessments. METHODS: Gait speed was assessed in 782 patients ≥75 years of age who had blood cancer, with results reported to providers after treatment decisions were made; 408 patients required treatment when different intensities were available per National Comprehensive Cancer Network (NCCN) guidelines. We performed structured abstractions of treatment intensity recommendations into standard intensity, reduced intensity, or supportive care, based on NCCN guidelines. We modeled gait speed and survival using Cox regression and performed ordinal logistic regression to assess predictors of NCCN-based categorizations of oncologists' treatment intensity recommendations, including gait speed. RESULTS: The median survival by gait speed category was 10.8 months (<0.4 m/s), 18.6 months (0.4-0.6 m/s), 34.0 months (0.6-0.8 m/s), and unreached (>0.8 m/s). Univariable hazard ratios (HRs) for death increased for each lower category compared with ≥0.8 m/s (0.6-0.8 m/s: HR, 1.76; 0.4-0.6 m/s: HR, 2.30; <0.4 m/s: HR, 3.31). Gait speed predicted survival in multivariable Cox regression (all P < .05). In multivariable models including age, sex, and Eastern Cooperative Oncology Group performance status, gait speed did not predict oncologists' recommended treatment intensity (all P > .05) and did not add to a base model predicting recommended treatment intensity. CONCLUSION: In older adults with blood cancer who presented for treatment, gait speed predicted survival but not treatment intensity recommendation. Incorporating gait speed into decision making may improve optimal treatment selection.

Prevalence and Tolerance of Prognostic Uncertainty Among Thoracic Oncologists.

We undertook a cross-sectional survey of a random sample of thoracic oncologists from the American Society of Clinical Oncology clinical directory to characterize whether prognostic uncertainty has increased and if tolerance of uncertainty is associated with prognostic discussion practices. We also assessed the Physicians' Reactions to Uncertainty Scale and presented a vignette about an incurable patient with uncertain life expectancy. One hundred and ninety-two of 438 surveys (43.8%) were received. Of the respondents, 52.1% agreed "there is more prognostic uncertainty in the management of lung cancer now than 10 years ago," and 37.4% noted difficulty "staying up-to-date." In multivariable analyses, physician-reported anxiety about uncertainty (p = .05) and reluctance to disclose uncertainty (p = .04) were inversely associated with reporting having prognostic discussions with most patients. For the vignette, 92.1% reported they would discuss incurability, but only 76.3% said they would discuss the patient's life expectancy. Our data suggest prognostic uncertainty has increased in thoracic oncology and oncologists' tolerance of uncertainty may affect discussion practices.

Femtosecond Transient Absorption Microscopy of Singlet Exciton Motion in Side-Chain Engineered Perylene-Diimide Thin Films.

We present a statistical analysis of femtosecond transient absorption microscopy applied to four different organic semiconductor thin films based on perylene-diimide (PDI). By achieving a temporal resolution of 12 fs with simultaneous sub-10 nm spatial precision, we directly probe the underlying exciton transport characteristics within 3 ps after photoexcitation free of model assumptions. Our study reveals sub-picosecond coherent exciton transport (12-45 cm2 s-1) followed by a diffusive phase of exciton transport (3-17 cm2 s-1). A comparison between the different films suggests that the exciton transport in the studied materials is intricately linked to their nanoscale morphology, with PDI films that form large crystalline domains exhibiting the largest diffusion coefficients and transport lengths. Our study demonstrates the advantages of directly studying ultrafast transport properties at the nanometer length scale and highlights the need to examine nanoscale morphology when investigating exciton transport in organic as well as inorganic semiconductors.

A comprehensive review of robotic surgery curriculum and training for residents, fellows, and postgraduate surgical education.

BACKGROUND: In 2017, the utilization of robotic-assisted surgery had grown 10-40-fold relative to laparoscopic surgery in common general surgery procedures. The rapid rise in the utilization of robotic-assisted surgery has necessitated a standardized training curriculum. Many curricula are currently being developed and validated. Additionally, advancements in virtual reality simulators have facilitated their integration into robotic-assisted surgery training. This review aims to highlight and discuss the features of existing curricula and robotic-assisted surgery training simulators and to provide updates on their respective validation process. MATERIALS AND METHODS: A literature review was conducted using PubMed from 2000-2019 and commercial websites. Information regarding availability, content, and status of validation was collected for each current robotic-assisted surgery curriculum. This review did not qualify as human subjects research, so institutional review board approval was not required. RESULTS: The daVinci Technology Training Pathway and Fundamentals of Robotic Surgery are purely web-based and self-paced robotic-assisted surgery training. The Society of American Gastrointestinal and Endoscopic Surgeon Robotic Masters Series, Fundamental Skills of Robot-Assisted Surgery training program, and the Robotics Training Network curriculum require trainees to be on site in order to provide expert feedback on surgical techniques and robot maintenance. Currently, there are few virtual reality simulators for robotic-assisted surgical training available on the market. CONCLUSIONS: Didactic courses are available in all of these training programs, but their contents are inconsistent. Furthermore, the availability and nature of hands-on training offered by these curriculums are widely variable.

All-Optical Detection of Neuronal Membrane Depolarization in Live Cells Using Colloidal Quantum Dots.

Luminescent semiconductor quantum dots (QDs) have recently been suggested as novel probes for imaging and sensing cell membrane voltages. However, a key bottleneck for their development is a lack of techniques to assess QD responses to voltages generated in the aqueous electrolytic environments typical of biological systems. Even more generally, there have been relatively few efforts to assess the response of QDs to voltage changes in live cells. Here, we develop a platform for monitoring the photoluminescence (PL) response of QDs under AC and DC voltage changes within aqueous ionic environments. We evaluate both traditional CdSe/CdS and more biologically compatible InP/ZnS QDs at a range of ion concentrations to establish their PL/voltage characteristics on chip. Wide-field, few-particle PL measurements with neuronal cells show the QDs can be used to track local voltage changes with greater sensitivity (ΔPL up to twice as large) than state-of-the-art calcium imaging dyes, making them particularly appealing for tracking subthreshold events. Additional physiological observation studies showed that while CdSe/CdS dots have greater PL responses on membrane depolarization, their lower cytotoxicity makes InP/ZnS far more suitable for voltage sensing in living systems. Our results provide a methodology for the rational development of QD voltage sensors and highlight their potential for imaging changes in cell membrane voltage.

Task activations produce spurious but systematic inflation of task functional connectivity estimates.

Most neuroscientific studies have focused on task-evoked activations (activity amplitudes at specific brain locations), providing limited insight into the functional relationships between separate brain locations. Task-state functional connectivity (FC) - statistical association between brain activity time series during task performance - moves beyond task-evoked activations by quantifying functional interactions during tasks. However, many task-state FC studies do not remove the first-order effect of task-evoked activations prior to estimating task-state FC. It has been argued that this results in the ambiguous inference "likely active or interacting during the task", rather than the intended inference "likely interacting during the task". Utilizing a neural mass computational model, we verified that task-evoked activations substantially and inappropriately inflate task-state FC estimates, especially in functional MRI (fMRI) data. Various methods attempting to address this problem have been developed, yet the efficacies of these approaches have not been systematically assessed. We found that most standard approaches for fitting and removing mean task-evoked activations were unable to correct these inflated correlations. In contrast, methods that flexibly fit mean task-evoked response shapes effectively corrected the inflated correlations without reducing effects of interest. Results with empirical fMRI data confirmed the model's predictions, revealing activation-induced task-state FC inflation for both Pearson correlation and psychophysiological interaction (PPI) approaches. These results demonstrate that removal of mean task-evoked activations using an approach that flexibly models task-evoked response shape is an important preprocessing step for valid estimation of task-state FC.

Early somatic mosaicism is a rare cause of long-QT syndrome.

Somatic mosaicism, the occurrence and propagation of genetic variation in cell lineages after fertilization, is increasingly recognized to play a causal role in a variety of human diseases. We investigated the case of life-threatening arrhythmia in a 10-day-old infant with long QT syndrome (LQTS). Rapid genome sequencing suggested a variant in the sodium channel NaV1.5 encoded by SCN5A, NM_000335:c.5284G > T predicting p.(V1762L), but read depth was insufficient to be diagnostic. Exome sequencing of the trio confirmed read ratios inconsistent with Mendelian inheritance only in the proband. Genotyping of single circulating leukocytes demonstrated the mutation in the genomes of 8% of patient cells, and RNA sequencing of cardiac tissue from the infant confirmed the expression of the mutant allele at mosaic ratios. Heterologous expression of the mutant channel revealed significantly delayed sodium current with a dominant negative effect. To investigate the mechanism by which mosaicism might cause arrhythmia, we built a finite element simulation model incorporating Purkinje fiber activation. This model confirmed the pathogenic consequences of cardiac cellular mosaicism and, under the presenting conditions of this case, recapitulated 2:1 AV block and arrhythmia. To investigate the extent to which mosaicism might explain undiagnosed arrhythmia, we studied 7,500 affected probands undergoing commercial gene-panel testing. Four individuals with pathogenic variants arising from early somatic mutation events were found. Here we establish cardiac mosaicism as a causal mechanism for LQTS and present methods by which the general phenomenon, likely to be relevant for all genetic diseases, can be detected through single-cell analysis and next-generation sequencing.

Exciton-Phonon Interactions Govern Charge-Transfer-State Dynamics in CdSe/CdTe Two-Dimensional Colloidal Heterostructures.

CdSe/CdTe core-crown type-II nanoplatelet heterostructures are two-dimensional semiconductors that have attracted interest for use in light-emitting technologies due to their ease of fabrication, outstanding emission yields, and tunable properties. Despite this, the exciton dynamics of these complex materials, and in particular how they are influenced by phonons, is not yet well understood. Here, we use a combination of femtosecond vibrational spectroscopy, temperature-resolved photoluminescence (PL), and temperature-dependent structural measurements to investigate CdSe/CdTe nanoplatelets with a thickness of four monolayers. We show that charge-transfer (CT) excitons across the CdSe/CdTe interface are formed on two distinct time scales: initially from an ultrafast (∼70 fs) electron transfer and then on longer time scales (∼5 ps) from the diffusion of domain excitons to the interface. We find that the CT excitons are influenced by an interfacial phonon mode at ∼120 cm-1, which localizes them to the interface. Using low-temperature PL spectroscopy we reveal that this same phonon mode is the dominant mechanism in broadening the CT PL. On cooling to 4 K, the total PL quantum yield reaches close to unity, with an ∼85% contribution from CT emission and the remainder from an emissive sub-band-gap state. At room temperature, incomplete diffusion of domain excitons to the interface and scattering between CT excitons and phonons limit the PL quantum yield to ∼50%. Our results provide a detailed picture of the nature of exciton-phonon interactions at the interfaces of 2D heterostructures and explain both the broad shape of the CT PL spectrum and the origin of PL quantum yield losses. Furthermore, they suggest that to maximize the PL quantum yield both improved engineering of the interfacial crystal structure and diffusion of domain excitons to the interface, e.g., by altering the relative core/crown size, are required.