Machine learning for spatial stratification of progressive cardiovascular dysfunction in a murine model of type 2 diabetes mellitus.

Speckle tracking echocardiography (STE) has been utilized to evaluate independent spatial alterations in the diabetic heart, but the progressive manifestation of regional and segmental cardiac dysfunction in the type 2 diabetic (T2DM) heart remains understudied. Therefore, the objective of this study was to elucidate if machine learning could be utilized to reliably describe patterns of the progressive regional and segmental dysfunction that are associated with the development of cardiac contractile dysfunction in the T2DM heart. Non-invasive conventional echocardiography and STE datasets were utilized to segregate mice into two pre-determined groups, wild-type and Db/Db, at 5, 12, 20, and 25 weeks. A support vector machine model, which classifies data using a single line, or hyperplane, that best separates each class, and a ReliefF algorithm, which ranks features by how well each feature lends to the classification of data, were used to identify and rank cardiac regions, segments, and features by their ability to identify cardiac dysfunction. STE features more accurately segregated animals as diabetic or non-diabetic when compared with conventional echocardiography, and the ReliefF algorithm efficiently ranked STE features by their ability to identify cardiac dysfunction. The Septal region, and the AntSeptum segment, best identified cardiac dysfunction at 5, 20, and 25 weeks, with the AntSeptum also containing the greatest number of features which differed between diabetic and non-diabetic mice. Cardiac dysfunction manifests in a spatial and temporal fashion, and is defined by patterns of regional and segmental dysfunction in the T2DM heart which are identifiable using machine learning methodologies. Further, machine learning identified the Septal region and AntSeptum segment as locales of interest for therapeutic interventions aimed at ameliorating cardiac dysfunction in T2DM, suggesting that machine learning may provide a more thorough approach to managing contractile data with the intention of identifying experimental and therapeutic targets.

Inter-annual Persistence of Canopy Fungi Driven by Abundance Despite High Spatial Turnover.

While it is now well established that fungal community composition varies spatially at a variety of scales, temporal turnover of fungi is less well understood. Here we studied inter-annual community compositional changes of fungi in a rainforest tree canopy environment. We tracked fungal community shifts over 3 years in three substrate types (live bryophytes, dead bryophytes, and host tree bark) and compared these changes to amounts of community turnover seen at small spatial scales in the same system. The effect of substrate type on fungal community composition was stronger than that of sampling year, which was very small but significant. Although levels of temporal turnover varied among substrates, with greater turnover in live bryophytes than other substrates, the amount of turnover from year to year was comparable to what is seen at spatial distances between 5 and 9 cm for the same substrate. Stability of communities was largely driven by a few fungi with high relative abundances. A majority of fungal occurrences were at low relative abundances (≤ 0.1%). These fungi tended to be short lived and persisted to following years ≤ 50% of the time, depending on substrate. Their presence and persistence are likely impacted by stochastic processes like dispersal limitation and disturbance. Most samples contained only one or a few fungi at high relative abundance (≥ 10%) that persisted half or more of the time. These more abundant and persistent fungi are expected to have sustained functional interactions within the canopy ecosystem.

N6-methyladenosine (M6A) in fetal offspring modifies mitochondrial gene expression following gestational nano-TiO2 inhalation exposure.

N6-methyladenosine (m6A) is the most prominent epitranscriptomic modification to RNA in eukaryotes, but it's role in adaptive changes within the gestational environment are poorly understood. We propose that gestational exposure to nano titanium dioxide (TiO2) contributes to cardiac m6A methylation in fetal offspring and influences mitochondrial gene expression. 10-week-old pregnant female FVB/NJ wild-type mice underwent 6 nonconsecutive days of whole-body inhalation exposure beginning on gestational day (GD) 5. Mice were exposed to filtered room air or nano-TiO2 with a target aerosol mass concentration of 12 mg/m3. At GD 15 mice were humanely killed and cardiac RNA and mitochondrial proteins extracted. Immunoprecipitation with m6A antibodies was performed followed by sequencing of immunoprecipitant (m6A) and input (mRNA) on the Illumina NextSeq 2000. Protein extraction, preparation, and LC-MS/MS were used for mitochondrial protein quantification. There were no differences in maternal or fetal pup weights, number of pups, or pup heart weights between exposure and control groups. Transcriptomic sequencing revealed 3648 differentially expressed mRNA in nano-TiO2 exposed mice (Padj ≤ 0.05). Transcripts involved in mitochondrial bioenergetics were significantly downregulated (83 of 85 genes). 921 transcripts revealed significant m6A methylation sites (Padj ≤ 0.10). 311 of the 921 mRNA were identified to have both 1) significantly altered expression and 2) differentially methylated sites. Mitochondrial proteomics revealed decreased expression of ATP Synthase subunits in the exposed group (P ≤ 0.05). The lack of m6A modifications to mitochondrial transcripts suggests a mechanism for decreased transcript stability and reduced protein expression due to gestational nano-TiO2 inhalation exposure.

Manipulation of the miR-378a/mt-ATP6 regulatory axis rescues ATP synthase in the diabetic heart and offers a novel role for lncRNA Kcnq1ot1.

Diabetes mellitus has been linked to an increase in mitochondrial microRNA-378a (miR-378a) content. Enhanced miR-378a content has been associated with a reduction in mitochondrial genome-encoded mt-ATP6 abundance, supporting the hypothesis that miR-378a inhibition may be a therapeutic option for maintaining ATP synthase functionality during diabetes mellitus. Evidence also suggests that long noncoding RNAs (lncRNAs), including lncRNA potassium voltage-gated channel subfamily Q member 1 overlapping transcript 1 (Kcnq1ot1), participate in regulatory axes with microRNAs (miRs). Prediction analyses indicate that Kcnq1ot1 has the potential to bind miR-378a. This study aimed to determine if loss of miR-378a in a genetic mouse model could ameliorate cardiac dysfunction in type 2 diabetes mellitus (T2DM) and to ascertain whether Kcnq1ot1 interacts with miR-378a to impact ATP synthase functionality by preserving mt-ATP6 levels. MiR-378a was significantly higher in patients with T2DM and 25-wk-old Db/Db mouse mitochondria, whereas mt-ATP6 and Kcnq1ot1 levels were significantly reduced when compared with controls. Twenty-five-week-old miR-378a knockout Db/Db mice displayed preserved mt-ATP6 and ATP synthase protein content, ATP synthase activity, and preserved cardiac function, implicating miR-378a as a potential therapeutic target in T2DM. Assessments following overexpression of the 500-bp Kcnq1ot1 fragment in established mouse cardiomyocyte cell line (HL-1) cardiomyocytes overexpressing miR-378a revealed that Kcnq1ot1 may bind and significantly reduce miR-378a levels, and rescue mt-ATP6 and ATP synthase protein content. Together, these data suggest that Kcnq1ot1 and miR-378a may act as constituents in an axis that regulates mt-ATP6 content, and that manipulation of this axis may provide benefit to ATP synthase functionality in type 2 diabetic heart.

Epiphytic fungal communities vary by substrate type and at submetre spatial scales.

Fungal species have numerous important environmental functions. Where these functions occur will depend on how fungi are spatially distributed, but the spatial structures of fungal communities are largely unknown, especially in understudied hyperdiverse tropical tree canopy systems. Here we explore fungal communities in a Costa Rican tropical rainforest canopy, with a focus on local-scale spatial structure and substrate specificity of fungi. Samples of ~1 cm3 were collected from 135 points along five adjacent tree branches, with intersample distances from 1 to 800 cm, and dissected into four substrates: outer host tree bark, inner bark, dead bryophytes and living bryophytes. We sequenced the ITS2 region to characterize total fungal communities. Fungal community composition and diversity varied among substrate types, even when multiple substrates were in direct contact. Fungi were most diverse in living bryophytes, with 39% of all operational taxonomic units (OTUs) found exclusively in this substrate, and the least diverse in inner bark. Fungal communities had significant positive spatial autocorrelation and distance decay of similarity only at distances less than 1 m. Similarity among samples declined by half in less than 10 cm, and even at these short distances, similarities were low with few OTUs shared among samples. These results indicate that community turnover is high and occurs at very small spatial scales, with any two locations sharing very few fungi in common. High heterogeneity of fungal communities in space and among substrates may have implications for the distributions, population dynamics and diversity of other tree canopy organisms, including epiphytic plants.

Enhanced antioxidant capacity prevents epitranscriptomic and cardiac alterations in adult offspring gestationally-exposed to ENM.

Maternal engineered nanomaterial (ENM) exposure during gestation has been associated with negative long-term effects on cardiovascular health in progeny. Here, we evaluate an epitranscriptomic mechanism that contributes to these chronic ramifications and whether overexpression of mitochondrial phospholipid hydroperoxide glutathione peroxidase (mPHGPx) can preserve cardiovascular function and bioenergetics in offspring following gestational nano-titanium dioxide (TiO2) inhalation exposure. Wild-type (WT) and mPHGPx (Tg) dams were exposed to nano-TiO2 aerosols with a mass concentration of 12.01 ± 0.50 mg/m3 starting from gestational day (GD) 5 for 360 mins/day for 6 nonconsecutive days over 8 days. Echocardiography was performed in pregnant dams, adult (11-week old) and fetal (GD 14) progeny. Mitochondrial function and global N6-methyladenosine (m6A) content were assessed in adult progeny. MPHGPx enzymatic function was further evaluated in adult progeny and m6A-RNA immunoprecipitation (RIP) was combined with RT-qPCR to evaluate m6A content in the 3'-UTR. Following gestational ENM exposure, global longitudinal strain (GLS) was 32% lower in WT adult offspring of WT dams, with preservation in WT offspring of Tg dams. MPHGPx activity was significantly reduced in WT offspring (29%) of WT ENM-exposed dams, but preserved in the progeny of Tg dams. M6A-RIP-qPCR for the SEC insertion sequence region of mPHGPx revealed hypermethylation in WT offspring from ENM-exposed WT dams, which was thwarted in the presence of the maternal transgene. Our findings implicate that m6A hypermethylation of mPHGPx may be culpable for diminished antioxidant capacity and resultant mitochondrial and cardiac deficits that persist into adulthood following gestational ENM inhalation exposure.

Cardiovascular adaptations to particle inhalation exposure: molecular mechanisms of the toxicology.

Ambient air, occupational settings, and the use and distribution of consumer products all serve as conduits for toxicant exposure through inhalation. While the pulmonary system remains a primary target following inhalation exposure, cardiovascular implications are exceptionally culpable for increased morbidity and mortality. The epidemiological evidence for cardiovascular dysfunction resulting from acute or chronic inhalation exposure to particulate matter has been well documented, but the mechanisms driving the resulting disturbances remain elusive. In the current review, we aim to summarize the cellular and molecular mechanisms that are directly linked to cardiovascular health following exposure to a variety of inhaled toxicants. The purpose of this review is to provide a comprehensive overview of the biochemical changes in the cardiovascular system following particle inhalation exposure and to highlight potential biomarkers that exist across multiple exposure paradigms. We attempt to integrate these molecular signatures in an effort to provide direction for future investigations. This review also characterizes how molecular responses are modified in at-risk populations, specifically the impact of environmental exposure during critical windows of development. Maternal exposure to particulate matter during gestation can lead to fetal epigenetic reprogramming, resulting in long-term deficits to the cardiovascular system. In both direct and indirect (gestational) exposures, connecting the biochemical mechanisms with functional deficits outlines pathways that can be targeted for future therapeutic intervention. Ultimately, future investigations integrating "omics"-based approaches will better elucidate the mechanisms that are altered by xenobiotic inhalation exposure, identify biomarkers, and guide in clinical decision making.

Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics.

BACKGROUND: Diabetes mellitus is a chronic disease that impacts an increasing percentage of people each year. Among its comorbidities, diabetics are two to four times more likely to develop cardiovascular diseases. While HbA1c remains the primary diagnostic for diabetics, its ability to predict long-term, health outcomes across diverse demographics, ethnic groups, and at a personalized level are limited. The purpose of this study was to provide a model for precision medicine through the implementation of machine-learning algorithms using multiple cardiac biomarkers as a means for predicting diabetes mellitus development. METHODS: Right atrial appendages from 50 patients, 30 non-diabetic and 20 type 2 diabetic, were procured from the WVU Ruby Memorial Hospital. Machine-learning was applied to physiological, biochemical, and sequencing data for each patient. Supervised learning implementing SHapley Additive exPlanations (SHAP) allowed binary (no diabetes or type 2 diabetes) and multiple classification (no diabetes, prediabetes, and type 2 diabetes) of the patient cohort with and without the inclusion of HbA1c levels. Findings were validated through Logistic Regression (LR), Linear Discriminant Analysis (LDA), Gaussian Naïve Bayes (NB), Support Vector Machine (SVM), and Classification and Regression Tree (CART) models with tenfold cross validation. RESULTS: Total nuclear methylation and hydroxymethylation were highly correlated to diabetic status, with nuclear methylation and mitochondrial electron transport chain (ETC) activities achieving superior testing accuracies in the predictive model (~ 84% testing, binary). Mitochondrial DNA SNPs found in the D-Loop region (SNP-73G, -16126C, and -16362C) were highly associated with diabetes mellitus. The CpG island of transcription factor A, mitochondrial (TFAM) revealed CpG24 (chr10:58385262, P = 0.003) and CpG29 (chr10:58385324, P = 0.001) as markers correlating with diabetic progression. When combining the most predictive factors from each set, total nuclear methylation and CpG24 methylation were the best diagnostic measures in both binary and multiple classification sets. CONCLUSIONS: Using machine-learning, we were able to identify novel as well as the most relevant biomarkers associated with type 2 diabetes mellitus by integrating physiological, biochemical, and sequencing datasets. Ultimately, this approach may be used as a guideline for future investigations into disease pathogenesis and novel biomarker discovery.

Field-Based Estimates of Global Warming Potential in Bioenergy Systems of Hawaii: Crop Choice and Deficit Irrigation.

Replacing fossil fuel with biofuel is environmentally viable from a climate change perspective only if the net greenhouse gas (GHG) footprint of the system is reduced. The effects of replacing annual arable crops with perennial bioenergy feedstocks on net GHG production and soil carbon (C) stock are critical to the system-level balance. Here, we compared GHG flux, crop yield, root biomass, and soil C stock under two potential tropical, perennial grass biofuel feedstocks: conventional sugarcane and ratoon-harvested, zero-tillage napiergrass. Evaluations were conducted at two irrigation levels, 100% of plantation application and at a 50% deficit. Peaks and troughs of GHG emission followed agronomic events such as ratoon harvest of napiergrass and fertilization. Yet, net GHG flux was dominated by carbon dioxide (CO2), as methane was oxidized and nitrous oxide (N2O) emission was very low even following fertilization. High N2O fluxes that frequently negate other greenhouse gas benefits that come from replacing fossil fuels with agronomic forms of bioenergy were mitigated by efficient water and fertilizer management, including direct injection of fertilizer into buried irrigation lines. From soil intensively cultivated for a century in sugarcane, soil C stock and root biomass increased rapidly following cultivation in grasses selected for robust root systems and drought tolerance. The net soil C increase over the two-year crop cycle was three-fold greater than the annualized soil surface CO2 flux. Deficit irrigation reduced yield, but increased soil C accumulation as proportionately more photosynthetic resources were allocated belowground. In the first two years of cultivation napiergrass did not increase net greenhouse warming potential (GWP) compared to sugarcane, and has the advantage of multiple ratoon harvests per year and less negative effects of deficit irrigation to yield.

Climate-associated population declines reverse recovery and threaten future of an iconic high-elevation plant.

Although climate change is predicted to place mountain-top and other narrowly endemic species at severe risk of extinction, the ecological processes involved in such extinctions are still poorly resolved. In addition, much of this biodiversity loss will likely go unobserved, and therefore largely unappreciated. The Haleakala silversword is restricted to a single volcano summit in Hawai'i, but is a highly charismatic giant rosette plant that is viewed by 1-2 million visitors annually. We link detailed local climate data to a lengthy demographic record, and combine both with a population-wide assessment of recent plant mortality and recruitment, to show that after decades of strong recovery following successful management, this iconic species has entered a period of substantial climate-associated decline. Mortality has been highest at the lower end of the distributional range, where most silverswords occur, and the strong association of annual population growth rates with patterns of precipitation suggests an increasing frequency of lethal water stress. Local climate data confirm trends toward warmer and drier conditions on the mountain, and signify a bleak outlook for silverswords if these trends continue. The silversword example foreshadows trouble for diversity in other biological hotspots, and illustrates how even well-protected and relatively abundant species may succumb to climate-induced stresses.

Richness and species composition of arboreal arthropods affected by nutrients and predators: a press experiment.

A longstanding goal for ecologists is to understand the processes that maintain biological diversity in communities, yet few studies have investigated the combined effects of predators and resources on biodiversity in natural ecosystems. We fertilized nutrient limited plots and excluded insectivorous birds in a randomized block design, and examined the impacts on arthropods associated with the dominant tree in the Hawaiian Islands, Metrosideros polymorpha (Myrtaceae). After 33 months, the species load (per foliage mass) of herbivores and carnivores increased with fertilization, but rarified richness (standardized to abundance) did not change. Fertilization depressed species richness of arboreal detritivores, and carnivore richness dropped in caged, unfertilized plots, both because of the increased dominance of common, introduced species with treatments. Herbivore species abundance distributions were more equitable than other trophic levels following treatments, and fertilization added specialized native species without changing relativized species richness. Overall, bird removal and nutrient addition treatments on arthropod richness acted largely independently, but with countervailing influences that obscured distinct top-down and bottom-up effects on different trophic levels. This study demonstrates that species composition, biological invasions, and the individuality of species traits may complicate efforts to predict the interactive effects of resources and predation on species diversity in food webs.

Impacts of biological control and invasive species on a non-target native Hawaiian insect.

The potential for classical biological control to cause unintended harm to native species was evaluated in the case of the endemic Hawaiian koa bug, Coleotichus blackburniae White (Hemiptera: Scutelleridae), and parasitoids introduced to Hawaii for control of an agricultural pest, the southern green stink bug, Nezara viridula (L.) (Hemiptera: Pentatomidae). Parasitism of C. blackburniae eggs, nymphs and adults by biocontrol agents was quantified across a wide range of habitats and compared to other sources of mortality. Egg mortality due to the biocontrol agent Trissolcus basalis Wollaston (Hymenoptera: Scelionidae) was low (maximum 26%) and confined to elevations below 500 m on a single host plant. Predation, mainly by alien spiders and ants, was the greatest source of egg mortality (maximum 87%). Parasitism of adult C. blackburniae by the biocontrol agent Trichopoda pilipes (F.) (Diptera: Tachinidae) was near zero at 21 of 24 sites surveyed. Three sites with high bug density had higher levels of T. pilipes parasitism, reaching maxima of 70% among adult female bugs, 100% among males and 50% among fifth instars. Male-biased parasitism indicated that T. pilipes is adapted to using male aggregation pheromone for finding C. blackburniae hosts. The relative impacts of biocontrol agents and other sources of mortality were compared using life tables. Invasive species, particularly generalist egg predators, had the greatest impacts on C. blackburniae populations. Effects of intentionally introduced parasitoids were relatively minor, although the tachinid T. pilipes showed potential for large impacts at individual sites. In retrospect, non-target attacks by biological control agents on C. blackburniae were predictable, but the environmental range and magnitude of impacts would have been difficult to foresee.