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The Isles Dernieres Barrier Island Refuge in Louisiana, USA, constitutes a major colonial waterbird breeding site, and several restoration projects have been undertaken to sustain waterbird populations on the refuge. However, very little is known about food resources that colonial waterbirds depend on in the Gulf of Mexico. Royal (Thalasseus maximus) and Sandwich (T. sandvicensis) tern diet composition was investigated to determine important food resources during the breeding period. Regurgitated prey items in the 2013 and 2014 breeding seasons were used to compare diet composition, prey item frequency, and prey item mass among four groups: Royal Tern adults, Royal Tern chicks, Sandwich Tern adults, and Sandwich Tern chicks. The two most frequent prey items were Atlantic croaker (Micropogonias undulatus) and bay anchovy (Anchoa mitchilli). Royal Tern adults consumed significantly more Sciaenids than any other tern group, and Sandwich Tern adults consumed more Engraulids than any other tern group. Royal and Sandwich tern adults partitioned food resources by prey species and prey size, while chick diet showed more overlap in prey species composition. Royal and Sandwich tern diet closely reflected the species composition of trawls from nearby waters, suggesting opportunistic prey selection. The diets of both tern species contained a variety of demersal prey items indicating use of discards from local fisheries activities. Interactions between breeding waterbirds and fisheries in coastal Louisiana may be an important conservation consideration with profound implications on breeding abundance and breeding success of waterbirds.

Gull-billed Terns (Gelochelidon nilotica) have historically demonstrated variability in nest-site selection and reproductive success throughout their breeding range. However, few studies have investigated the breeding parameters of Gull-billed Tern populations on barrier islands in the northern Gulf of Mexico, USA. The main objective of this study was to investigate annual variability of breeding population size, hatching success, and causes of nest failure during eight breeding seasons (2009–2016). Annual variation was observed in colony sizes (Range = 1–68 nests), colony locations (among five islands), and hatching success (0–93%). Mean hatching success was 56% and flooding was the main cause of failure, accounting for 64% of all failed nests. Additionally, nest site habitat characteristics were compared between successful and unsuccessful Gull-billed Tern nests. Nest substrate composition differed between successful and failed nests, and successful nests were also associated with higher elevation, greater distance from the high tide line, and less vegetative cover. There was considerable variation in Gull-billed Tern breeding population size and hatching success, which may be attributable to the dynamic nature of barrier island habitats. Long-term monitoring is required to better understand the breeding dynamics of Gull-billed Terns, but conservation efforts should consider maintaining island habitats that are protected from flooding and have adequate nesting substrate, minimal vegetation, and limited disturbance from humans and predators.

Bacterial communities associated with roots impact the health and nutrition of the host plant. The dynamics of these microbial assemblies over the plant life cycle are, however, not well understood. Here, we use dense temporal sampling of 1,510 samples from root spatial compartments to characterize the bacterial and archaeal components of the root-associated microbiota of field grown rice (Oryza sativa) over the course of 3 consecutive growing seasons, as well as 2 sites in diverse geographic regions. The root microbiota was found to be highly dynamic during the vegetative phase of plant growth and then stabilized compositionally for the remainder of the life cycle. Bacterial and archaeal taxa conserved between field sites were defined as predictive features of rice plant age by modeling using a random forest approach. The age-prediction models revealed that drought-stressed plants have developmentally immature microbiota compared to unstressed plants. Further, by using genotypes with varying developmental rates, we show that shifts in the microbiome are correlated with rates of developmental transitions rather than age alone, such that different microbiota compositions reflect juvenile and adult life stages. These results suggest a model for successional dynamics of the root-associated microbiota over the plant life cycle.

Since the introduction of integrated histological and molecular diagnoses by the 2016 World Health Organization (WHO) Classification of Tumors of the Nervous System, an increasing number of molecular markers have been found to have prognostic significance in infiltrating gliomas, many of which have now become incorporated as diagnostic criteria in the 2021 WHO Classification. This has increased the applicability of targeted-next generation sequencing in the diagnostic work-up of neuropathology specimens and in addition, raises the question of whether targeted sequencing can, in practice, reliably replace older, more traditional diagnostic methods such as immunohistochemistry and fluorescence in-situ hybridization. Here, we demonstrate that the Oncomine Cancer Gene Mutation Panel v2 assay targeted-next generation sequencing panel for solid tumors is not only superior to IHC in detecting mutation in IDH1/2 and TP53 but can also predict 1p/19q co-deletion with high sensitivity and specificity relative to fluorescence in-situ hybridization by looking at average copy number of genes sequenced on 1p, 1q, 19p, and 19q. Along with detecting the same molecular data obtained from older methods, targeted-next generation sequencing with an RNA sequencing component provides additional information regarding the presence of RNA based alterations that have diagnostic significance and possible therapeutic implications. From this work, we advocate for expanded use of targeted-next generation sequencing over more traditional methods for the detection of important molecular alterations as a part of the standard diagnostic work up for CNS neoplasms.

We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. This version introduces vision understanding abilities, a wider coverage of languages and longer context - at least 128K tokens. We also change the architecture of the model to reduce the KV-cache memory that tends to explode with long context. This is achieved by increasing the ratio of local to global attention layers, and keeping the span on local attention short. The Gemma 3 models are trained with distillation and achieve superior performance to Gemma 2 for both pre-trained and instruction finetuned versions. In particular, our novel post-training recipe significantly improves the math, chat, instruction-following and multilingual abilities, making Gemma3-4B-IT competitive with Gemma2-27B-IT and Gemma3-27B-IT comparable to Gemini-1.5-Pro across benchmarks. We release all our models to the community.