Sotigalimab and/or nivolumab with chemotherapy in first-line metastatic pancreatic cancer: clinical and immunologic analyses from the randomized phase 2 PRINCE trial

Chemotherapy combined with immunotherapy has improved the treatment of certain solid tumors, but effective regimens remain elusive for pancreatic ductal adenocarcinoma (PDAC). We conducted a randomized phase 2 trial evaluating the efficacy of nivolumab (nivo; anti-PD-1) and/or sotigalimab (sotiga; CD40 agonistic antibody) with gemcitabine/nab-paclitaxel (chemotherapy) in patients with first-line metastatic PDAC (NCT03214250). In 105 patients analyzed for efficacy, the primary endpoint of 1-year overall survival (OS) was met for nivo/chemo (57.7%, P = 0.006 compared to historical 1-year OS of 35%, n = 34) but was not met for sotiga/chemo (48.1%, P = 0.062, n = 36) or sotiga/nivo/chemo (41.3%, P = 0.223, n = 35). Secondary endpoints were progression-free survival, objective response rate, disease control rate, duration of response and safety. Treatment-related adverse event rates were similar across arms. Multi-omic circulating and tumor biomarker analyses identified distinct immune signatures associated with survival for nivo/chemo and sotiga/chemo. Survival after nivo/chemo correlated with a less suppressive tumor microenvironment and higher numbers of activated, antigen-experienced circulating T cells at baseline. Survival after sotiga/chemo correlated with greater intratumoral CD4 T cell infiltration and circulating differentiated CD4 T cells and antigen-presenting cells. A patient subset benefitting from sotiga/nivo/chemo was not identified. Collectively, these analyses suggest potential treatment-specific correlates of efficacy and may enable biomarker-selected patient populations in subsequent PDAC chemoimmunotherapy trials

Sensitization in Transplantation: Assessment of Risk (STAR) 2017 Working Group Meeting Report

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144684/1/ajt14752_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144684/2/ajt14752.pd

What is the potential of oligodendrocyte progenitor cells to successfully treat human spinal cord injury?

<p>Abstract</p> <p>Background</p> <p>Spinal cord injury is a serious and debilitating condition, affecting millions of people worldwide. Long seen as a permanent injury, recent advances in stem cell research have brought closer the possibility of repairing the spinal cord. One such approach involves injecting oligodendrocyte progenitor cells, derived from human embryonic stem cells, into the injured spinal cord in the hope that they will initiate repair. A phase I clinical trial of this therapy was started in mid 2010 and is currently underway.</p> <p>Discussion</p> <p>The theory underlying this approach is that these myelinating progenitors will phenotypically replace myelin lost during injury whilst helping to promote a repair environment in the lesion. However, the importance of demyelination in the pathogenesis of human spinal cord injury is a contentious issue and a body of literature suggests that it is only a minor factor in the overall injury process.</p> <p>Summary</p> <p>This review examines the validity of the theory underpinning the on-going clinical trial as well as analysing published data from animal models and finally discussing issues surrounding safety and purity in order to assess the potential of this approach to successfully treat acute human spinal cord injury.</p

Fish assemblage stability over fifty years in the Lake Pontchartrain Estuary; comparisons among habitats using Canonical Correspondence Analysis

We assessed fish assemblage stability over the last half century in Lake Pontchartrain, an environmentally degraded oligohaline estuary in southeastern Louisiana. Because assemblage instability over time has been consistently associated with severe habitat degradation, we attempted to determine whether fish assemblages in demersal, nearshore, and pelagic habitats exhibited change that was unrelated to natural fluctuations in environmental variables (e.g., assemblage changes between wet and dry periods). Collection data from three gear types (trawl, beach seine, and gill nets) and monthly environmental data (salinity, temperature, and Secchi depth) were compared for four collecting periods: 1954 (dry period), 1978 (wet period), 1996–1998 (wet period), and 1998–2000 (dry period). Canonical correspondence analysis (CCA) revealed that although the three environmental variables were significantly associated with the distribution and abundance patterns of fish assemblages in all habitats (with the exception of Secchi depth for pelagic samples), most fish assemblage change occurred among sampling periods (i.e., along a temporal gradient unrelated to changing environmental variables). Assemblage instability was the most pronounced for fishes collected by trawls from demersal habitats. A marked lack of cyclicity in the trawl data CCA diagram indicated a shift away from a baseline demersal assemblage of 50 yr ago. Centroid positions for the five most collected species indicated that three benthic fishes, Atlantic croaker (Micropogonias undulatus), spot (Leiostomus xanthurus), and hardhead catfish (Arius felis), were more dominant inWe assessed fish assemblage stability over the last half century in Lake Pontchartrain, an environmentally degraded oligohaline estuary in southeastern Louisiana. Because assemblage instability over time has been consistently associated with severe habitat degradation, we attempted to determine whether fish assemblages in demersal, nearshore, and pelagic habitats exhibited change that was unrelated to natural fluctuations in environmental variables (e.g., assemblage changes between wet and dry periods). Collection data from three gear types (trawl, beach seine, and gill nets) and monthly environmental data (salinity, temperature, and Secchi depth) were compared for four collecting periods: 1954 (dry period), 1978 (wet period), 1996–1998 (wet period), and 1998–2000 (dry period). Canonical correspondence analysis (CCA) revealed that although the three environmental variables were significantly associated with the distribution and abundance patterns of fish assemblages in all habitats (with the exception of Secchi depth for pelagic samples), most fish assemblage change occurred among sampling periods (i.e., along a temporal gradient unrelated to changing environmental variables). Assemblage instability was the most pronounced for fishes collected by trawls from demersal habitats. A marked lack of cyclicity in the trawl data CCA diagram indicated a shift away from a baseline demersal assemblage of 50 yr ago. Centroid positions for the five most collected species indicated that three benthic fishes, Atlantic croaker (Micropogonias undulatus), spot (Leiostomus xanthurus), and hardhead catfish (Arius felis), were more dominant in past demersal assemblages (1954 and 1978). A different situation was shown for planktivorous species collected by trawls with bay anchovy (Anchoa mitchilli) becoming more dominant in recent assemblages and Gulf enhaden (Brevoortia patronus) remaining equally represented in assemblages over time. Changes in fish assemblages from nearshore (beach seine) and pelagic (gill net) habitats were more closely related to environmental fluctuations, though the CCA for beach seine data also indicated a decrease in the dominance of M. undulatus and an increase in the proportion of A. mitchilli over time. The reduced assemblage role of benthic fishes and the marked assemblage change indicated by trawl data suggest that over the last half century demersal habitats in Lake Pontchartrain have been impacted more by multiple anthropogenic stressors than nearshore or pelagic habitats. past demersal assemblages (1954 and 1978). A different situation was shown for planktivorous species collected by trawls with bay anchovy (Anchoa mitchilli) becoming more dominant in recent assemblages and Gulf menhaden (Brevoortia patronus) remaining equally represented in assemblages over time. Changes in fish assemblages from nearshore (beach seine) and pelagic (gill net) habitats were more closely related to environmental fluctuations, though the CCA for beach seine data also indicated a decrease in the dominance of M. undulatus and an increase in the proportion of A. mitchilli over time. The reduced assemblage role of benthic fishes and the marked assemblage change indicated by trawl data suggest that over the last half century demersal habitats in Lake Pontchartrain have been impacted more by multiple anthropogenic stressors than nearshore or pelagic habitats

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages