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The Bronze Age was a time of technological, socioeconomic, and political transformation in Europe. Since Bronze Age socioeconomic institutions were rooted in the landscape, they can be investigated using a settlement ecology approach to how people positioned themselves relative to the environment and each other. Transylvania is home to a rare combination of mineral resources, trade infrastructures, and productive agropastoral land, all of which were critical to Bronze Age societies. This study combines size-and rank-size analyses to suggest that there were several shifts in how people positioned themselves across settlements in Transylvania during the Bronze Age. This research contributes to a broader understanding of the factors that inform where people choose to settle down and the consequences those decisions have on the development of social, economic, and political institutions.

The archaeological rescue excavations occasioned by the construction of the Lot no. 1 of the Highway no. 10, Sebeș-Turda, highlighted an unexpected Bronze Age necropolis belonging to Wietenberg Culture. The Bronze Age necropolis was delimited between 6+600 and 6+650 kilometers, and located on the southwestern part of the Site no. 6, right above the early Vinča settlement defensive trenches (Fig. 1-2). With 74 excavated funerary complexes, the partially excavated Wietenberg cemetery is one of the largest in Transylvania. According the radiocarbon data presented in this study, the necropolis was used in the Middle Bronze Age (1780-1690 cal. BC), associated with the Wietenberg culture (phase II), and is contemporary with the end of the cemetery from Sebeș-Între Răstoace located approximately 7.5 km South - South-West, on the Sebeș River terraces.

Interest in ecoacoustics has resulted in an influx of acoustic data and novel methodologies to classify and relate landscape sound activity to biodiversity and ecosystem health. However, indicators used to summarize sound and quantify the effects of disturbances on biodiversity can be inconsistent when applied across ecological gradients. This study used an acoustic dataset of 487,148 min from 746 sites collected over 4 years across Sonoma County, California, USA, by citizen scientists. We built a custom labeled dataset of soundscape components and applied a deep learning framework to test our ability to predict these soundscape components: human noise (Anthropophony), wildlife vocalizations (Biophony), weather phenomena (Geophony), Quiet periods, and microphone Interference. These soundscape components allowed us to balance predicting variation in environmental recordings and relative time to build a custom labeled dataset. We used these data to quantify soundscape patterns across space and time that could be useful for environmental planning, ecosystem conservation and restoration, and biodiversity monitoring. We describe a pre-trained convolutional neural network, fine-tuned with our sound reference data, with classification achieving an overall F0.75-score of 0.88, precision of 0.94, and recall of 0.80 across the five target soundscape components. We deployed the model to predict soundscape components for all acoustic data and assess their hourly patterns. We noted an increase in Biophony in the early morning and evening, coinciding with peak animal community vocalization (e.g., dawn chorus). Anthropophony increased during morning/daylight hours and was lowest in the evenings, coinciding with diurnal patterns in human activity. Further, we examined soundscape patterns related to geographic properties at recording sites. Anthropophony decreased with increasing distance to major roads, while Quiet increased. Biophony and Quiet were comparable to Anthropophony at more urban/developed and agriculture/barren sites, while Biophony and Quiet were significantly higher than Anthropophony at less-developed shrubland, oak woodland, and conifer forest sites. These results demonstrate that acoustic classification of broad soundscape components is possible with small datasets, and classifications can be applied to a large acoustic dataset to gain ecological knowledge.

PURPOSE: In spite of advances in therapy for some subtypes, group 3 medulloblastoma continues to portend a poor prognosis. A subpopulation of medulloblastoma cells expressing the cell surface marker CD133 have been posited as possible stem cell like cancer cells (SCLCC), a potential source of drug resistance and relapse. Retinoids have been shown to affect SCLCC in other brain tumors. Based on these findings, we hypothesized that the CD133-enriched cell population group 3 medulloblastoma cells would be sensitive to the novel rexinoid, UAB30. METHODS: Human medulloblastoma cell lines were studied. Cell sorting based on CD133 expression was performed. Both in vitro and in vivo extreme limiting dilution assays were completed to establish CD133 as a SCLCC marker in these cell lines. Cells were treated with either retinoic acid (RA) or UAB30 and sphere forming capacity and CD133 expression were assessed. Immunoblotting was used to assess changes in stem cell markers. Finally, mice injected with CD133-enriched or CD133-depleted cells were treated with UAB30. RESULTS: CD133-enriched cells more readily formed tumorspheres in vitro at lower cell concentrations and formed tumors in vivo at low cell numbers. Treatment with RA or UAB30 decreased CD133 expression, decreased tumorsphere formation, and decreased expression of cancer stem cell markers. In vivo studies demonstrated that tumors from both CD133-enriched and CD133-depleted cells were sensitive to treatment with UAB30. CONCLUSIONS: CD133 is a marker for medulloblastoma SCLCCs. Both CD133-enriched and CD133-depleted medulloblastoma cell populations demonstrated sensitivity to UAB30, indicating its potential as a therapeutic option for group 3 medulloblastoma.

Selenium (Se) hyperaccumulator plants can concentrate the toxic element Se up to 1% of shoot (DW) which is known to protect hyperaccumulator plants from generalist herbivores. There is evidence for Se-resistant insect herbivores capable of feeding upon hyperaccumulators. In this study, resistance to Se was investigated in seed chalcids and seed beetles found consuming seeds inside pods of Se-hyperaccumulator species Astragalus bisulcatus and Stanleya pinnata. Selenium accumulation, localization and speciation were determined in seeds collected from hyperaccumulators in a seleniferous habitat and in seed herbivores. Astragalus bisulcatus seeds were consumed by seed beetle larvae (Acanthoscelides fraterculus Horn, Coleoptera: Bruchidae) and seed chalcid larvae (Bruchophagus mexicanus, Hymenoptera: Eurytomidae). Stanleya pinnata seeds were consumed by an unidentified seed chalcid larva. Micro X-ray absorption near-edge structure (µXANES) and micro-X-Ray Fluorescence mapping (µXRF) demonstrated Se was mostly organic C-Se-C forms in seeds of both hyperaccumulators, and S. pinnata seeds contained ∼24% elemental Se. Liquid chromatography-mass spectrometry of Se-compounds in S. pinnata seeds detected the C-Se-C compound seleno-cystathionine while previous studies of A. bisulcatus seeds detected the C-Se-C compounds methyl-selenocysteine and γ-glutamyl-methyl-selenocysteine. Micro-XRF and µXANES revealed Se ingested from hyperaccumulator seeds redistributed throughout seed herbivore tissues, and portions of seed C-Se-C were biotransformed into selenocysteine, selenocystine, selenodiglutathione, selenate and selenite. Astragalus bisulcatus seeds contained on average 5,750 µg Se g(-1), however adult beetles and adult chalcid wasps emerging from A. bisulcatus seed pods contained 4-6 µg Se g(-1). Stanleya pinnata seeds contained 1,329 µg Se g(-1) on average; however chalcid wasp larvae and adults emerging from S. pinnata seed pods contained 9 and 47 µg Se g(-1). The results suggest Se resistant seed herbivores exclude Se, greatly reducing tissue accumulation; this explains their ability to consume high-Se seeds without suffering toxicity, allowing them to occupy the unique niche offered by Se hyperaccumulator plants.

Background: Pediatric gastroenteropancreatic neuroendocrine tumors are exceedingly rare, resulting in most pediatric treatment recommendations being based on data derived from adults. Trametinib is a kinase inhibitor that targets MEK1/2 and has been employed in the treatment of cancers harboring mutations in the Ras pathway. Methods: We utilized an established human pediatric gastroenteropancreatic neuroendocrine-like tumor patient-derived xenograft (PDX) with a known NRAS mutation to study the effects of MEK inhibition. We evaluated the effects of trametinib on proliferation, motility, and tumor growth in vivo. We created an intraperitoneal metastatic model of this PDX, characterized both the phenotype and the genotype of the metastatic PDX and again, investigated the effects of MEK inhibition. Results: We found target engagement with decreased ERK1/2 phosphorylation with trametinib treatment. Trametinib led to decreased in vitro cell growth and motility, and decreased tumor growth and increased animal survival in a murine flank tumor model. Finally, we demonstrated that trametinib was able to significantly decrease gastroenteropancreatic neuroendocrine intraperitoneal tumor metastasis. Conclusions: The results of these studies support the further investigation of MEK inhibition in pediatric NRAS mutated solid tumors.

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction in hourly mean absolute scaled error and a 3% reduction in daily mean absolute scaled error.

Increased environmental threats require proper monitoring of animal communities to understand where and when changes occur. Ecoacoustic tools that quantify natural acoustic environments use a combination of biophony (animal sound) and geophony (wind, rain, and other natural phenomena) to represent the natural soundscape and, in comparison to anthropophony (technological human sound) can highlight valuable landscapes to both human and animal communities. However, recording these sounds requires intensive deployment of recording devices and storage and interpretation of large amounts of data, resulting in large data gaps across the landscape and periods in which recordings are absent. Interpolating ecoacoustic metrics like biophony, geophony, anthropophony, and acoustic indices can bridge these gaps in observations and provide insight across larger spatial extents and during periods of interest. Here, we use seven ecoacoustic metrics and acoustically-derived bird species richness across a heterogeneous landscape composed of densely urbanized, suburban, rural, protected, and recently burned lands in Sonoma County, California, U.S.A., to explore spatiotemporal patterns in ecoacoustic measurements. Predictive models of ecoacoustic metrics driven by land-use/land-cover, remotely-sensed vegetation structure, anthropogenic impact, climate, geomorphology, and phenology variables capture landscape and daily differences in ecoacoustic patterns with varying performance (avg. R ^2 = 0.38 ± 0.11) depending on metric and period-of-day and provide interpretable patterns in sound related to human activity, weather phenomena, and animal activity. We also offer a case study on the use of the data-driven prediction of biophony to capture changes in soniferous species activity before (1–2 years prior) and after (1–2 years post) wildfires in our study area and find that biophony may depict the reorganization of acoustic communities following wildfires. This is demonstrated by an upward trend in activity 1–2 years post-wildfire, particularly in more severely burned areas. Overall, we provide evidence of the importance of climate, spaceborne-lidar-derived forest structure, and phenological time series characteristics when modeling ecoacoustic metrics to upscale site observations and map ecoacoustic biodiversity in areas without prior acoustic data collection. Resulting maps can identify areas of attention where changes in animal communities occur at the edge of human and natural disturbances.

Ecoacoustic monitoring has proliferated as autonomous recording units (ARU) have become more accessible. ARUs provide a non-invasive, passive method to assess ecosystem dynamics related to vocalizing animal behavior and human activity. With the ever-increasing volume of acoustic data, the field has grappled with summarizing ecologically meaningful patterns in recordings. Almost 70 acoustic indices have been developed that offer summarized measurements of bioacoustic activity and ecosystem conditions. However, their systematic relationships to ecologically meaningful patterns in varying sonic conditions are inconsistent and lead to non-trivial interpretations. We used an acoustic dataset of over 725,000 min of recordings across 1,195 sites in Sonoma County, California, to evaluate the relationship between 15 established acoustic indices and sonic conditions summarized using five soundscape components classified using a convolutional neural network: anthropophony (anthropogenic sounds), biophony (biotic sounds), geophony (wind and rain), quiet (lack of emergent sound), and interference (ARU feedback). We used generalized additive models to assess acoustic indices and biophony as ecoacoustic indicators of avian diversity. Models that included soundscape components explained acoustic indices with varying degrees of performance (avg. adj-R2 = 0.61 ± 0.16; n = 1,195). For example, we found the normalized difference soundscape index was the most sensitive index to biophony while being less influenced by ambient sound. However, all indices were affected by non-biotic sound sources to varying degrees. We found that biophony and acoustic indices combined were highly predictive in modeling bird species richness (deviance = 65.8%; RMSE = 3.9 species; n = 1,185 sites) for targeted, morning-only recording periods. Our analyses demonstrate the confounding effects of non-biotic soundscape components on acoustic indices, and we recommend that applications be based on anticipated sonic environments. For instance, in the presence of extensive rain and wind, we suggest using an index minimally affected by geophony. Furthermore, we provide evidence that a measure of biodiversity (bird species richness) is related to the aggregate biotic acoustic activity (biophony). This established relationship adds to recent work that identifies biophony as a reliable and generalizable ecoacoustic measure of biodiversity.

Abstract Despite increasing incidence, treatment for hepatoblastoma has not changed significantly over the past 20 years. Chemotherapeutic strategies continue to rely on cisplatin, as it remains the most active single agent against hepatoblastoma. However, chemoresistance remains a significant challenge with 54–80% of patients developing resistance to chemotherapy after 4–5 cycles of treatment. Stem cell-like cancer cells (SCLCCs) are a subset of cells thought to play a role in chemoresistance and disease recurrence. We have previously demonstrated that Proviral Integration site for Moloney murine leukemia virus (PIM) kinases, specifically PIM3, play a role in hepatoblastoma cell proliferation and tumor growth and maintain the SCLCC phenotype. Here, we describe the development of a cisplatin-resistant hepatoblastoma xenograft model of the human HuH6 cell line and a patient-derived xenograft, COA67. We provide evidence that these cisplatin-resistant cells are enriched for SCLCCs and express PIM3 at higher levels than cisplatin-naïve cells. We demonstrate that PIM inhibition with AZD1208 sensitizes cisplatin-resistant hepatoblastoma cells to cisplatin, enhances cisplatin-mediated apoptosis, and decreases the SCLCC phenotype seen with cisplatin resistance. Together, these findings indicate that PIM inhibition may be a promising adjunct in the treatment of hepatoblastoma to effectively target SCLCCs and potentially decrease chemoresistance and subsequent disease relapse.

Patient-derived xenografts provide significant advantages over long-term passage cell lines when investigating efficacy of treatments for solid tumors. Our laboratory encountered a high-grade, metastatic, neuroendocrine-like tumor from a pediatric patient that presented with a unique genetic profile. In particular, mutations in TYRO3 and ALK were identified. We established a human patient-derived xenoline (PDX) of this tumor for use in the current study. We investigated the effect of crizotinib, a chemotherapeutic known to effectively target both TYRO3 and ALK mutations. Crizotinib effectively decreased viability, proliferation, growth, and the metastatic properties of the PDX tumor through downregulation of STAT3 signaling, but expression of PDGFRß was increased. Sunitinib is a small molecule inhibitor of PDGFRß and was studied in this PDX independently and in combination with crizotinib. Sunitinib alone decreased viability, proliferation, and growth in vitro and decreased tumor growth in vivo. In combination, sunitinib was able to overcome potential crizotinib-induced resistance through downregulation of ERK 1/2 activity and PDGFRß receptor expression; consequently, tumor growth was significantly decreased both in vitro and in vivo. Through the use of the PDX, it was possible to identify crizotinib as a less effective therapeutic for this tumor and suggest that targeting PDGFRß would be more effective. These findings may translate to other solid tumors that present with the same genetic mutations.

Abstract Patient-derived xenografts (PDXs) provide an opportunity to evaluate the effects of therapies in an environment that more closely resembles the human condition than that seen with long-term passage cell lines. In the current studies, we investigated the effects of FAK inhibition on two neuroblastoma PDXs in vitro. Cells were treated with two small molecule inhibitors of FAK, PF-573,228 (PF) and 1,2,4,5-benzentetraamine tetrahydrochloride (Y15). Following FAK inhibition, cell survival and proliferation decreased significantly and cell cycle arrest was seen in both cell lines. Migration and invasion assays were used to determine the effect of FAK inhibition on cell motility, which decreased significantly in both cell lines in the presence of either inhibitor. Finally, tumor cell stemness following FAK inhibition was evaluated with extreme limiting dilution assays as well as with immunoblotting and quantitative real-time PCR for the expression of stem cell markers. FAK inhibition decreased formation of tumorspheres and resulted in a corresponding decrease in established stem cell markers. FAK inhibition decreased many characteristics of the malignant phenotype, including cancer stem cell like features in neuroblastoma PDXs, making FAK a candidate for further investigation as a potential target for neuroblastoma therapy.

Retinoic acid (RA) therapy has been utilized as maintenance therapy for high-risk neuroblastoma, but over half of patients treated with RA relapse. Neuroblastoma stem cell-like cancer cells (SCLCCs) are a subpopulation of cells characterized by the expression of the cell surface marker CD133 and are hypothesized to contribute to drug resistance and disease relapse. A novel rexinoid compound, 9-cis-UAB30 (UAB30), was developed having the same anti-tumor effects as RA but a more favorable toxicity profile. In the current study, we investigated the efficacy of UAB30 in neuroblastoma patient-derived xenografts (PDX). Two PDXs, COA3 and COA6, were utilized and alterations in the malignant phenotype were assessed following treatment with RA or UAB30. UAB30 significantly decreased proliferation, viability, and motility of both PDXs. UAB30 induced cell-cycle arrest as demonstrated by the significant increase in percentage of cells in G1 (COA6: 33.7 ± 0.7 vs. 43.3 ± 0.7%, control vs. UAB30) and decrease in percentage of cells in S phase (COA6: 44.7 ± 1.2 vs. 38.6 ± 1%, control vs. UAB30). UAB30 led to differentiation of PDX cells, as evidenced by the increase in neurite outgrowth and mRNA abundance of differentiation markers. CD133 expression was decreased by 40% in COA6 cells after UAB30. The ability to form tumorspheres and mRNA abundance of known stemness markers were also significantly decreased following treatment with UAB30, further indicating decreased cancer cell stemness. These results provide evidence that UAB30 decreased tumorigenicity and cancer cell stemness in neuroblastoma PDXs, warranting further exploration as therapy for high-risk neuroblastoma.

Investigation of the mechanisms responsible for aggressive neuroblastoma and its poor prognosis is critical to identify novel therapeutic targets and improve survival. Enhancer of Zeste Homolog 2 (EZH2) is known to play a key role in supporting the malignant phenotype in several cancer types and knockdown of EZH2 has been shown to decrease tumorigenesis in neuroblastoma cells. We hypothesized that the EZH2 inhibitor, GSK343, would affect cell proliferation and viability in human neuroblastoma. We utilized four long-term passage neuroblastoma cell lines and two patient-derived xenolines (PDX) to investigate the effects of the EZH2 inhibitor, GSK343, on viability, motility, stemness and in vivo tumor growth. Immunoblotting confirmed target knockdown. Treatment with GSK343 led to significantly decreased neuroblastoma cell viability, migration and invasion, and stemness. GSK343 treatment of mice bearing SK-N-BE(2) neuroblastoma tumors resulted in a significant decrease in tumor growth compared to vehicle-treated animals. GSK343 decreased viability, and motility in long-term passage neuroblastoma cell lines and decreased stemness in neuroblastoma PDX cells. These data demonstrate that further investigation into the mechanisms responsible for the anti-tumor effects seen with EZH2 inhibitors in neuroblastoma cells is warranted.