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Background: As patients interact with a healthcare service system, patterns of service utilization (PSUs) emerge. These PSUs are embedded in the sparse high-dimensional space of longitudinal cross-continuum health service encounter data. Once extracted, PSUs can provide quality assurance/quality improvement (QA/QI) efforts with the information required to optimize service system structures and functions. This may improve outcomes for complex patients with chronic diseases. Method: Working with longitudinal cross-continuum encounter data from a regional health service system, various pattern detection analyses were conducted, employing (1) graph community detection algorithms, (2) natural language processing (NLP) clustering, and (3) a hybrid NLP–graph method. Result: These approaches produced similar PSUs, as determined from a clinical perspective by clinical subject matter experts and service system operations experts. Conclusions: The similarity in the results provides validation for the methodologies. Moreover, the results stress the need to engage with clinical or service system operations experts, both in providing the taxonomies and ontologies of the service system, the cohort definitions, and determining the level of granularity that produces the most clinically meaningful results. Finally, the uniqueness of each approach provides an opportunity to take advantage of the various analytical capabilities that each approach brings, which will be further explored in our future research.

Abstract We have previously identified a network of higher-order brain regions particularly vulnerable to the ageing process, schizophrenia and Alzheimer’s disease. However, it remains unknown what the genetic influences on this fragile brain network are, and whether it can be altered by the most common modifiable risk factors for dementia. Here, in ~40,000 UK Biobank participants, we first show significant genome-wide associations between this brain network and seven genetic clusters implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s disease, and with the two antigens of the XG blood group located in the pseudoautosomal region of the sex chromosomes. We further reveal that the most deleterious modifiable risk factors for this vulnerable brain network are diabetes, nitrogen dioxide – a proxy for traffic-related air pollution – and alcohol intake frequency. The extent of these associations was uncovered by examining these modifiable risk factors in a single model to assess the unique contribution of each on the vulnerable brain network, above and beyond the dominating effects of age and sex. These results provide a comprehensive picture of the role played by genetic and modifiable risk factors on these fragile parts of the brain.

Abstract Background MCL-1 is a prosurvival B-cell lymphoma 2 family protein that plays a critical role in tumor maintenance and survival and can act as a resistance factor to multiple anticancer therapies. Herein, we describe the generation and characterization of the highly potent and selective MCL-1 inhibitor ABBV-467 and present findings from a first-in-human trial that included patients with relapsed/refractory multiple myeloma (NCT04178902). Methods Binding of ABBV-467 to human MCL-1 was assessed in multiple cell lines. The ability of ABBV-467 to induce tumor growth inhibition was investigated in xenograft models of human multiple myeloma and acute myelogenous leukemia. The first-in-human study was a multicenter, open-label, dose-escalation study assessing safety, pharmacokinetics, and efficacy of ABBV-467 monotherapy. Results Here we show that administration of ABBV-467 to MCL-1-dependent tumor cell lines triggers rapid and mechanism-based apoptosis. In vivo, intermittent dosing of ABBV-467 as monotherapy or in combination with venetoclax inhibits the growth of xenografts from human hematologic cancers. Results from a clinical trial evaluating ABBV-467 in patients with multiple myeloma based on these preclinical data indicate that treatment with ABBV-467 can result in disease control (seen in 1 patient), but may also cause increases in cardiac troponin levels in the plasma in some patients (seen in 4 of 8 patients), without other corresponding cardiac findings. Conclusions The selectivity of ABBV-467 suggests that treatment-induced troponin release is a consequence of MCL-1 inhibition and therefore may represent a class effect of MCL-1 inhibitors in human patients.

High head rice and low chalky grain percentages are key grain quality traits selected in developing rice cultivars. The objectives of this research were to characterize the phenotypic variation of head rice and chalky grain percentages in a diverse collection of rice accessions, identify single nucleotide polymorphism (SNP) markers associated with each of these traits using genome-wide association studies (GWAS), and identify putative candidate genes linked to the SNPs identified by GWAS. Diverse rice varieties, landraces, and breeding lines were grown at the Texas A&M AgriLife Research Center in Beaumont. Head rice percentages (HRP) and chalky grain percentages (CGP) of 195 and 199 non-waxy accessions were estimated in 2018 and 2019, respectively. Phenotypic data were analyzed along with 854,832 SNPs using three statistical models: mixed linear model (MLM), multi-locus mixed model (MLMM), and fixed and random model circulating probability unification (FarmCPU). Significant variations in HRP and CGP were observed between rice accessions. Two significant marker-trait associations (MTAs) were detected on chromosomes 1 and 2, respectively, based on best linear unbiased prediction (BLUP) values in 2018, while in 2019, one SNP was significantly associated with HRP in each of chromosomes 6, 8, 9, and 11, and two in chromosome 7. CGP was significantly associated with five SNPs located in chromosomes 2, 4, 6, and 8 in the 2018 study and ten SNPs in chromosomes 1, 2, 3, 4, 7, 8, 11, and 12 in the 2019 study. The SNPs are located within or linked to putative candidate genes involved in HRP and CGP. This study reports five and ten novel MTAs for HRP and CGP, respectively, while three and five MTAs co-located with previously reported quantitative trait loci for HRP and CGP, respectively. The validation of candidate genes for their roles in determining HRP and CGP is necessary to design functional molecular markers that can be used to effectively develop rice cultivars with desirable grain quality.

Future rice systems must produce more grain while minimizing the negative environmental impacts. A key question is how to orient agricultural research & development (R&D) programs at national to global scales to maximize the return on investment. Here we assess yield gap and resource-use efficiency (including water, pesticides, nitrogen, labor, energy, and associated global warming potential) across 32 rice cropping systems covering half of global rice harvested area. We show that achieving high yields and high resource-use efficiencies are not conflicting goals. Most cropping systems have room for increasing yield, resource-use efficiency, or both. In aggregate, current total rice production could be increased by 32%, and excess nitrogen almost eliminated, by focusing on a relatively small number of cropping systems with either large yield gaps or poor resource-use efficiencies. This study provides essential strategic insight on yield gap and resource-use efficiency for prioritizing national and global agricultural R&D investments to ensure adequate rice supply while minimizing negative environmental impact in coming decades.

Deep learning has increasingly been applied to supervised learning tasks in astronomy, such as classifying images of galaxies based on their apparent shape (i.e., galaxy morphology classification) to gain insight regarding the evolution of galaxies. In this work, we examine the effect of pretraining on the performance of the classical AlexNet convolutional neural network (CNN) in classifying images of 14,034 galaxies from the Sloan Digital Sky Survey Data Release 4. Pretraining involves designing and training CNNs on large labeled image datasets unrelated to astronomy, which takes advantage of the vast amounts of such data available compared to the relatively small amount of labeled galaxy images. We show a statistically significant benefit of using pretraining, both in terms of improved overall classification success and reduced computational cost to achieve such performance.

Background and purposePeriventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings.MethodsParticipants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC.ResultsIn the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype.ConclusionsOur study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

Abstract Background Grain yield is a complex trait that results from interaction between underlying phenotypic traits and climatic, edaphic, and biotic variables. In rice, main culm panicle node number (MCPNN; the node number on which the panicle is borne) and maximum node production rate (MNPR; the number of leaves that emerge per degree-day > 10°C) are primary phenotypic plant traits that have significant positive direct effects on yield-related traits. Degree-days to heading (DDTH), which has a significant positive effect on grain yield, is influenced by the interaction between MCPNN and MNPR. The objective of this research is to assess the phenotypic variation of MCPNN, MNPR, and DDTH in a panel of diverse rice accessions, determine regions in the rice genome associated with these traits using genome-wide association studies (GWAS), and identify putative candidate genes that control these traits. Results Considerable variation was observed for the three traits in a 220-genotype diverse rice population. MCPNN ranged from 8.1 to 20.9 nodes in 2018 and from 9.9 to 21.0 nodes in 2019. MNPR ranged from 0.0097 to 0.0214 nodes/degree day > 10°C in 2018 and from 0.0108 to 0.0193 nodes/degree-day > 10°C in 2019. DDTH ranged from 713 to 2,345 degree-days > 10°C in 2018 and from 778 to 2,404 degree-days > 10°C in 2019. Thirteen significant (P < 2.91 x 10-7) trait-single nucleotide polymorphism (SNP) associations were identified using the multilocus mixed linear model for GWAS. Significant associations between MCPNN and three SNPs in chromosome 2 (S02_12032235, S02_11971745, and S02_12030176) were detected with both the 2018 and best linear unbiased prediction (BLUP) datasets. Nine SNPs in chromosome 6 (S06_1970442, S06_2310856, S06_2550351, S06_1968653, S06_2296852, S06_1968680, S06_1968681, S06_1970597, and S06_1970602) were significantly associated with MNPR in the 2019 dataset. One SNP in chromosome 11 (S11_29358169) was significantly associated with the DDTH in the BLUP dataset. Conclusions This study identifies SNP markers that are putatively associated with MCPNN, MNPR, and DDTH. Some of these SNPs were located within or near gene models, which identify possible candidate genes involved in these traits. Validation of the putative candidate genes through expression and gene editing analyses are necessary to confirm their roles in regulating MCPNN, MNPR, and DDTH. Identifying the underlying genetic basis for primary phenotypic traits MCPNN and MNPR could lead to the development of fast and efficient approaches for their estimation, such as marker-assisted selection and gene editing, which is essential in increasing breeding efficiency and enhancing grain yield in rice. On the other hand, DDTH is a resultant variable that is highly affected by nitrogen and water management, plant density, and several other factors.

Statins have shown promise as anticancer agents in experimental and epidemiologic research. However, any benefit that they provide is likely context-dependent, for example, applicable only to certain cancers or in combination with specific anticancer drugs. We report that inhibition of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) using statins enhances the proapoptotic activity of the B cell lymphoma-2 (BCL2) inhibitor venetoclax (ABT-199) in primary leukemia and lymphoma cells but not in normal human peripheral blood mononuclear cells. By blocking mevalonate production, HMGCR inhibition suppressed protein geranylgeranylation, resulting in up-regulation of proapoptotic protein p53 up-regulated modulator of apoptosis (PUMA). In support of these findings, dynamic BH3 profiling confirmed that statins primed cells for apoptosis. Furthermore, in retrospective analyses of three clinical studies of chronic lymphocytic leukemia, background statin use was associated with enhanced response to venetoclax, as demonstrated by more frequent complete responses. Together, this work provides mechanistic justification and clinical evidence to warrant prospective clinical investigation of this combination in hematologic malignancies.

Beneficial plant-microbe interactions offer a sustainable biological solution with the potential to boost low-input food and bioenergy production. A better mechanistic understanding of these complex plant-microbe interactions will be crucial to improving plant production as well as performing basic ecological studies investigating plant-soil-microbe interactions. Here, a detailed description for ecosystem fabrication is presented, using widely available 3D printing technologies, to create controlled laboratory habitats (EcoFABs) for mechanistic studies of plant-microbe interactions within specific environmental conditions. Two sizes of EcoFABs are described that are suited for the investigation of microbial interactions with various plant species, including Arabidopsis thaliana, Brachypodium distachyon, and Panicum virgatum. These flow-through devices allow for controlled manipulation and sampling of root microbiomes, root chemistry as well as imaging of root morphology and microbial localization. This protocol includes the details for maintaining sterile conditions inside EcoFABs and mounting independent LED light systems onto EcoFABs. Detailed methods for addition of different forms of media, including soils, sand, and liquid growth media coupled to the characterization of these systems using imaging and metabolomics are described. Together, these systems enable dynamic and detailed investigation of plant and plant-microbial consortia including the manipulation of microbiome composition (including mutants), the monitoring of plant growth, root morphology, exudate composition, and microbial localization under controlled environmental conditions. We anticipate that these detailed protocols will serve as an important starting point for other researchers, ideally helping create standardized experimental systems for investigating plant-microbe interactions.

Increasing rice yield while improving resource use efficiency is of great importance. This study examines cropping systems globally to highlight areas where rice production can be improved by prioritizing R&D strategies.

Using a novel combination of palaeohabitat modelling and genetic mixture analyses, we identify and assess a sea-level-driven recolonization process following the Last Glacial Maximum (LGM). Our palaeohabitat modelling reveals dramatic changes in estuarine habitat distribution along the coast of California (USA) and Baja California (Mexico). At the LGM (approx. 20 kya), when sea level was approximately 130 m lower, the palaeo-shoreline was too steep for tidal estuarine habitat formation, eliminating this habitat type from regions where it is currently most abundant, and limiting such estuaries to a northern and a southern refugium separated by 1000 km. We assess the recolonization of estuaries formed during post-LGM sea-level rise through examination of refugium-associated alleles and approximate Bayesian computation in three species of estuarine fishes. Results reveal sourcing of modern populations from both refugia, which admix in the newly formed habitat between the refuges. We infer a dramatic peak in habitat area between 15 and 10 kya with subsequent decline. Overall, this approach revealed a previously undocumented dynamic and integrated relationship between sea-level change, coastal processes and population genetics. These results extend glacial refugial dynamics to unglaciated subtropical coasts and have significant implications for biotic response to predicted sea-level rise.

Abstract Background The New Guinean archipelago has been shaped by millions of years of plate tectonic activity combined with long-term fluctuations in climate and sea level. These processes combined with New Guinea’s location at the tectonic junction between the Australian and Pacific plates are inherently linked to the evolution of its rich endemic biota. With the advent of molecular phylogenetics and an increasing amount of geological data, the field of New Guinean biogeography begins to be reinvigorated. Results We inferred a comprehensive dated molecular phylogeny of endemic diving beetles to test historical hypotheses pertaining to the evolution of the New Guinean biota. We used geospatial analysis techniques to compare our phylogenetic results with a newly developed geological terrane map of New Guinea as well as the altitudinal and geographic range of species ( https://arcg.is/189zmz ). Our divergence time estimations indicate a crown age (early diversification) for New Guinea Exocelina beetles in the mid-Miocene ca. 17 Ma, when the New Guinean orogeny was at an early stage. Geographic and geological ancestral state reconstructions suggest an origin of Exocelina ancestors on the eastern part of the New Guinean central range on basement rocks (with a shared affinity with the Australian Plate). Our results do not support the hypothesis of ancestors migrating to the northern margin of the Australian Plate from Pacific terranes that incrementally accreted to New Guinea over time. However, our analyses support to some extent a scenario in which Exocelina ancestors would have been able to colonize back and forth between the amalgamated Australian and Pacific terranes from the Miocene onwards. Our reconstructions also do not support an origin on ultramafic or ophiolite rocks that have been colonized much later in the evolution of the radiation. Macroevolutionary analyses do not support the hypothesis of heterogeneous diversification rates throughout the evolution of this radiation, suggesting instead a continuous slowdown in speciation. Conclusions Overall, our geospatial analysis approach to investigate the links between the location and evolution of New Guinea’s biota with the underlying geology sheds a new light on the patterns and processes of lineage diversification in this exceedingly diverse region of the planet.