Few studies have examined the role of early vs. later environment in the development of life history (LH) strategies, whether age at sexual debut mediates LH development, or whether LH indicators contribute to environmental stress in adulthood. In the current study, we addressed these gaps cross-culturally using data from Jenu Kurubas who live in the rural outskirts of Mysore (n = 133), India, and mixed-caste peri-urban residents in Mysore city (n = 222). Research took place from October 2016-July 2017. First, participants engaged in semi-structured interviews to formulate quantitative measures of current environmental stress (n = 60). Next, participants (n = 355) completed structured questionnaires that measured demographics; early and current environmental stress; and LH indicators including age at sexual debut, facets of impulsivity, education, and number of children. Structural equation modeling was used to test for the developmental cascade reported in Western studies of psychosocial acceleration (e.g., indirect effect of early environmental stress on number of children through age at sexual debut). Consistent with Western findings, environmental stress appeared to hasten sexual debut, decrease self-regulation and educational attainment, and increase current environmental stress in the peri-urban sample. Early environmental stress forecasted younger age at sexual debut in both samples; however, no other effects of early environmental stress nor any associations with current environmental stress were consistent between samples. Although age at sexual debut appeared to translate early environmental stress into greater numbers of children and current environmental stress in the peri-urban and rural samples, respectively, it was associated with different outcomes between the samples and forecasted adult environment only in the rural sample. Taken together, our findings indicate more research is needed to determine whether the developmental cascade suggested by most applications of LH theory to humans generalizes across cultures and rural and periurban environments.

Accumulating evidence suggests that iron homeostasis is disturbed in tumors. We aimed at clarifying the distribution of iron in renal cell carcinoma (RCC). Considering the pivotal role of macrophages for iron homeostasis and their association with poor clinical outcome, we investigated the role of macrophage-secreted iron for tumor progression by applying a novel chelation approach. We applied flow cytometry and multiplex-immunohistochemistry to detect iron-dependent markers and analyzed iron distribution with atomic absorption spectrometry in patients diagnosed with RCC. We further analyzed the functional significance of iron by applying a novel extracellular chelator using RCC cell lines as well as patient-derived primary cells. The expression of iron-regulated genes was significantly elevated in tumors compared to adjacent healthy tissue. Iron retention was detected in tumor cells, whereas tumor-associated macrophages showed an iron-release phenotype accompanied by enhanced expression of ferroportin. We found increased iron amounts in extracellular fluids, which in turn stimulated tumor cell proliferation and migration. In vitro, macrophage-derived iron showed pro-tumor functions, whereas application of an extracellular chelator blocked these effects. Our study provides new insights in iron distribution and iron-handling in RCC. Chelators that specifically scavenge iron in the extracellular space confirmed the importance of macrophage-secreted iron in promoting tumor growth.

Real-time sensing of proteins, especially in wearable devices, remains a substantial challenge due to the need to convert a binding event into a measurable signal that is compatible with the chosen analytical instrumentation. Impedance spectroscopy enables real-time detection via either measuring electrostatic interactions or electron transfer reactions while simultaneously being amenable to miniaturization for integration into wearable form-factors. To create a more robust methodology for optimizing impedance-based sensors, additional fundamental studies exploring components influencing the design and implementation of these sensors are needed. This investigation addresses a sub-set of these issues by combining optical and electrochemical characterization to validate impedance-based sensor performance as a function of (1) biorecognition element density, (2) self-assembled monolayer chain length, (3) self-assembled monolayer charge density, (4) the electrochemical sensing mechanism and (5) the redox reporter selection. Using a pre-existing lysozyme aptamer and lysozyme analyte combination, we demonstrate a number of design criteria to advance the state-of-the-art in protein sensing. For this model system we demonstrated the following: First, denser self-assembled monolayers yielded substantially improved sensing results. Second, self-assembled monolayer composition, including both thickness and charge density, changed the observed peak position and peak current. Third, single frequency measurements, while less informative, can be optimized to replace multi-frequency measurements and in some cases (such as that with zwitterionic self-assembled monolayers) are preferred. Finally, various redox reporters traditionally not used in impedance sensing should be further explored. Collectively, these results can help limit bottlenecks associated with device development, enabling realization of next-generation impedance-based biosensing with customize sensor design for the specific application.

Summer monsoon (June-September) precipitation is crucial for agricultural activities in India. Extremes during the monsoon season can have deleterious effects on water availability and agriculture in the region. Here, we show that hot and dry extremes during the summer monsoon season significantly impact food production in India and find that they tend to occur during El Nino years during the observed record of 1951-2018. We then use an ensemble of climate simulations for the historic (1971-2000) and future (2006-2100) that capture this coupling between El Nino and the Indian monsoon to show that the frequency of concurrent hot and dry extremes increases by a factor of 1.5 under continued greenhouse warming during the 21st century. Despite projections of summer monsoon intensification on the order of similar to 10%, the rise in surface air temperatures as well as increase in rainfall variability contributes to more severe hot and dry monsoon extremes over India, thereby posing a substantial challenge to future food security in India.

Wildfire danger assessment is essential for operational allocation of fire management resources; with longer lead prediction, the more efficiently can resources be allocated regionally. Traditional studies focus on meteorological forecasts and fire danger index models (e.g., National Fire Danger Rating System-NFDRS) for predicting fire danger. Meteorological forecasts, however, lose accuracy beyond 10 days; as such, there is no quantifiable method for predicting fire danger beyond 10 days. While some recent studies have statistically related hydrologic parameters and past wildfire area burned or occurrence to fire, no study has used these parameters to develop a monthly spatially distributed predictive model in the contiguous United States. Thus, the objective of this study is to introduce Fire Danger from Earth Observations (FDEO), which uses satellite data over the contiguous United States (CONUS) to enable two-month lead time prediction of wildfire danger, a sufficient lead time for planning purposes and relocating resources. In this study, we use satellite observations of land cover type, vapor pressure deficit, surface soil moisture, and the enhanced vegetation index, together with the United States Forest Service (USFS) verified and validated fire database (FPA) to develop spatially gridded probabilistic predictions of fire danger, defined as expected area burned as a deviation from "normal". The results show that the model predicts spatial patterns of fire danger with 52% overall accuracy over the 2004-2013 record, and up to 75% overall accuracy during the fire season. Overall accuracy is defined as number of pixels with correctly predicted fire probability classes divided by the total number of the studied pixels. This overall accuracy is the first quantified result of two-month lead prediction of fire danger and demonstrates the potential utility of using diverse observational data sets for use in operational fire management resource allocation in the CONUS.

Objectives: To determine the feasibility of integrating pre-intubation ultrasound into airway course and assess emergency medicine (EM) residents'confidence and comfort level in using ultrasound for pre-intubation hemodynamic stabilization and identifying cricothyroid membrane after the training session. Materials and methods:This is a retrospective study. Pre-intubation ultrasound training was delivered with the following ultrasound components (didactics and hands-on sessions using human models) to EM residents: (1) sonoanatomy and scanning technique to identify cricothyroid membrane and (2) pre-intubation echocardiography for recognition of acute right ventricular failure and pre-intubation hemodynamic stabilization. Results: A total of 56 EM residents participated In this study. Only 21% [95% confidence interval (CI), 10-31%] reported using ultrasound for pre-intubation hemodynamic stabilization. After the training session, 89% (95% CI, 81-97%) reported that ultrasound-based teaching increased their knowledge of pre-intubation hemodynamic stabilization compared with traditional teaching methods. On a scale of 1 (low) through 10 (high), the average comfort level for integrating ultrasound findings into medical decision making for pre-intubation hemodynamic stabilization was 6.8 (95% CI, 6.3-7.3). Seventy-nine percent (95% CI, 68-89%) reported that focused training in airway ultrasound is adequate to identify cricothyroid membrane. On a scale of 1 (low) through 10 (high), the average confidence level for identifying cricothyroid membrane using ultrasound was 6.6 (95% CI, 6.1-7.1). Conclusion: At our institution, we successfully integrated pre-intubation ultrasound into an airway course. Emergency medicine residents had a moderate level of comfort and confidence level using ultrasound for pre-intubation hemodynamic stabilization and identifying cricothyroid membrane after the training session.

Forecasting hydraulic data such as pressure and demand in water distribution system (WDS) is an important task that helps ensure efficient and accurate operations. Despite high-performance data prediction, missing data can still occur, making it difficult to effectively operate WDS. Though the pressure data are directly related to the rules of operation for pumps or valves, few studies have been conducted on pressure data forecasting. This study proposes a new missing and incomplete data control approach based on real pressure data for reliable and efficient WDS operation and maintenance. The proposed approach is: (1) application of source data from high-resolution, real-world pressure data; (2) development of a cross-domain artificial neural network (CDANN), combining the standard artificial neural networks (ANNs) and the cross-domain training approach for missing data control; and (3) analysis of standard data mining according to external factors to improve prediction accuracy. To verify the proposed approach, a real-world network located in South Korea was used, and the forecasting results were evaluated through performance indicators (i.e., overall, special points, and percentage errors). The performance of the CDANN is compared with that of standard ANNs, and CDANN was found to provide better predictions than traditional ANNs.

The incidence of cacao swollen shoot disease (CSSD) in cacao (Theobroma cacao L.) has increased in West Africa since similar to 2000. To investigate the genomic and species diversity of the CSSD-badnaviruses infecting cacao in Cote d'Ivoire and Ghana, symptomatic leaves were subjected to high-throughput sequencing. Among the 30 newly determined genomes, three badnaviruses were identified, Cacao swollen shoot Togo B virus (CSSTBV), Cacao swollen shoot CD virus, and Cacao swollen shoot CE virus (CSSCEV). The phylogenetic trees reconstructed for the reverse transcriptase (RT) and ribonuclease H (RNase H) sequences were incongruent with the complete viral genomes, which had the most robust statistical support. Recombination seems to be involved in the CSSD-badnavirus diversification. The genomic diversity varied among different CSSD-badnaviruses, with CSSTBV showing the lowest nucleotide diversity (pi = 0.06236), and CSSCEV exhibiting the greatest variability (pi = 0.21911). Evidence of strong purifying selection was found in the coding regions of the CSSTBV isolates.

Rationale: Limited information is available on racial/ethnic differences in pulmonary arterial hypertension (PAH). Objectives: Determine effects of race/ethnicity and ancestry on mortality and disease outcomes in diverse patients with PAH. Methods: Patients with Group 1 PAH were included from two national registries with genome-wide data and two local cohorts, and further incorporated in a global meta-analysis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for transplant-free, all-cause mortality in Hispanic patients with non-Hispanic white (NHW) patients as the reference group. Odds ratios (ORs) for inpatient-specific mortality in patients with PAH were also calculated for race/ethnic groups from an additional National Inpatient Sample dataset not included in the meta-analysis. Measurements and Main Results: After covariate adjustment, self-reported Hispanic patients (n = 290) exhibited significantly reduced mortality versus NHW patients (n = 1,970) after global meta-analysis (HR, 0.60 [95% CI, 0.41-0.87]; P = 0.008). Although not significant, increasing Native American genetic ancestry appeared to account for part of the observed mortality benefit (HR, 0.48 [95% CI, 0.23-1.01]; P= 0.053) in the two national registries. Finally, in the National Inpatient Sample, an inpatient mortality benefit was also observed for Hispanic patients (n = 1,524) versus NHW patients (n = 8,829; OR, 0.65 [95% CI, 0.50-0.84]; P = 0.001). An inpatient mortality benefit was observed for Native American patients (n = 185; OR, 0.38 [95% CI, 0.15-0.93]; P= 0.034). Conclusions: This study demonstrates a reproducible survival benefit for Hispanic patients with Group 1 PAH in multiple clinical settings. Our results implicate contributions of genetic ancestry to differential survival in PAH.