Cassava Spirit and the Seed of History: On Garden Cosmology in Indigenous Amazonia

This article concerns the practice of cassava gardening among the indigenous Makushi people of Amazonian Guyana. By focusing on the cassava garden (mîî) as a primary site of multispecies engagement, I explore some of the heterogeneous modes that people–plant relationships take in everyday life and ritual practice. Plants, for the Makushi, are typically thought of as ‘persons’ (pemon), and gardening is predicated upon maintaining relationships of interspecies care via regular human–plant communication. In the idiom of human kinship, cassava plants are spoken of as being ‘children’ (more yamî’), both of human gardeners and Cassava Mama, the tutelary spirit of cultivated plants. Human–plant communication is both verbal, in the form of poetic language (taren) and songs (eremu), and embodied, in the form of tactile engagement and substance-based transfers. It is in the cultivation of communicative relationships with plants and their spirits, I argue, that Makushi gardeners create and nourish human persons and, ultimately, reproduce society. I go on to address the anthropological problem of plant animism in Amazonia, arguing that a more embodied, sensorial and, following Strathern, ‘immanentist’ notion of spirit is required to better account for the complex entanglement of bodies and souls that undergirds human–plant interpenetration in indigenous Amazonia. In dialogue with literature from the multispecies turn, I suggest that an anthropology beyond the human, much like Makushi gardening, might usefully be thought of as a process of more-than-human ontogenesis

The Nature of Sweetness: An Indigenous Fermentation Complex in Amazonian Guyana

This chapter is an ethnographic case study of the fermentation of cassava beer among the indigenous Makushi people of southern Guyana. The chapter constitutes the first in-depth anthropological study of parakari, a unique kind of cassava beer fermented via the cultivation of a domesticated species of saprotrophic fungus (Rhizopus sp.). Herein, the author explores Makushi theories and practices of fermentation, and, more broadly, the ways in which alcoholic drinks operate as catalysts for processes of social and cosmic reproduction and transformation in indigenous Amazonia. For the Makushi, as it is argued, the production and consumption of cassava beer is understood as a more-than-human process of person-making, harnessing the vibrant agency of a diversity of vegetal, animal, microbial, and spiritual entities and forces. Fermentation, in this frame, is treated both as a sociotechnical system and an ecosystem

Sensory ecologies, plant-persons, and multinatural landscapes in Amazonia

Seeking to generate a deeper methodological and theoretical dialogue between botanical science and anthropology, this paper summarizes interdisciplinary approaches to human–plant interactions we have described as “sensory ecology” and “phytoethnography”, applying these concepts to vital questions about human–plant relations in Amazonia. Building on this work, we broaden the scope of our investigations by considering their relevance to the field of historical ecology. In particular, we discuss Eduardo Viveiros de Castro’s concept of “multinaturalism” and explore how it can be applied to understanding management and domestication of forest landscapes in Amazonia by Indigenous Peoples

Sensory Ecology, Bioeconomy, and the Age of COVID: A Parallax View of Indigenous and Scientific Knowledge

Drawing on original ethnobotanical and anthropological research among Indigenous peoples across the Amazon, we examine synergies and dissonances between Indigenous and Western scientific knowledge about the environment, resource use, and sustainability. By focusing on the sensory dimension of Indigenous engagements with the environment—an approach we have described as “sensory ecology” and explored through the method of “phytoethnography”—we promote a symmetrical dialogue between Indigenous and scientific understandings around such phenomena as animal–plant mutualisms, phytochemical toxicity, sustainable forest management in “multinatural” landscapes, and the emergence of new diseases like the novel coronavirus SARS‐CoV‐2 (COVID‐19). Drawing examples from our own and other published works, we explore the possibilities and limitations of a “parallax view” attempting to hold Indigenous and scientific knowledge in focus simultaneously. As the concept of “bioeconomy” emerges as a key alternative for sustainable development of the Amazon, we encourage a critical and urgent engagement between dominant Western conceptions and Indigenous Amazonian knowledge, practices, and cultural values. Cognitive science, which has long contributed to studies of Indigenous categorization and conceptualization of the natural world, continues to play an important role in building bridges of mutual communication and respect between Indigenous and scientific approaches to sustainability and biodiversity conservation

Voltage-Gated Sodium Channel Modulation by a New Spider Toxin Ssp1a Isolated From an Australian Theraphosid

Given the important role of voltage-gated sodium (NaV) channel-modulating spider toxins in elucidating the function, pharmacology, and mechanism of action of therapeutically relevant NaV channels, we screened the venom from Australian theraphosid species against the human pain target hNaV1.7. Using assay-guided fractionation, we isolated a 33-residue inhibitor cystine knot (ICK) peptide (Ssp1a) belonging to the NaSpTx1 family. Recombinant Ssp1a (rSsp1a) inhibited neuronal hNaV subtypes with a rank order of potency hNaV1.7 > 1.6 > 1.2 > 1.3 > 1.1. rSsp1a inhibited hNaV1.7, hNaV1.2 and hNaV1.3 without significantly altering the voltage-dependence of activation, inactivation, or delay in recovery from inactivation. However, rSsp1a demonstrated voltage-dependent inhibition at hNaV1.7 and rSsp1a-bound hNaV1.7 opened at extreme depolarizations, suggesting rSsp1a likely interacted with voltage-sensing domain II (VSD II) of hNaV1.7 to trap the channel in its resting state. Nuclear magnetic resonance spectroscopy revealed key structural features of Ssp1a, including an amphipathic surface with hydrophobic and charged patches shown by docking studies to comprise the interacting surface. This study provides the basis for future structure-function studies to guide the development of subtype selective inhibitors

Synthesis, pharmacological and structural characterization of novel conopressins from Conus miliaris

Cone snails produce a fast-acting and often paralyzing venom, largely dominated by disulfide-rich conotoxins targeting ion channels. Although disulfide-poor conopeptides are usually minor components of cone snail venoms, their ability to target key membrane receptors such as GPCRs make them highly valuable as drug lead compounds. From the venom gland transcriptome of Conus miliaris, we report here on the discovery and characterization of two conopressins, which are nonapeptide ligands of the vasopressin/oxytocin receptor family. These novel sequence variants show unusual features, including a charge inversion at the critical position 8, with an aspartate instead of a highly conserved lysine or arginine residue. Both the amidated and acid C-terminal analogues were synthesized, followed by pharmacological characterization on human and zebrafish receptors and structural investigation by NMR. Whereas conopressin-M1 showed weak and only partial agonist activity at hV1bR (amidated form only) and ZFV1a1R (both amidated and acid form), both conopressin-M2 analogues acted as full agonists at the ZFV2 receptor with low micromolar a�nity. Together with the NMR structures of amidated conopressins-M1, -M2 and -G, this study provides novel structure-activity relationship information that may help in the design of more selective ligands

Quantification of root water uptake in soil using X-ray Computed Tomography and image based modelling

Spatially averaged models of root-soil interactions are often used to calculate plant water uptake. Using a combination of X-ray Computed Tomography (CT) and image based modelling we tested the accuracy of this spatial averaging by directly calculating plant water uptake for young wheat plants in two soil types. The root system was imaged using X-ray CT at 2, 4, 6, 8 and 12 days after transplanting. The roots were segmented using semi-automated root tracking for speed and reproducibility. The segmented geometries were converted to a mesh suitable for the numerical solution of Richards’ equation. Richards’ equation was parameterised using existing pore scale studies of soil hydraulic properties in the rhizosphere of wheat plants. Image based modelling allows the spatial distribution of water around the root to be visualised and the fluxes into the root to be calculated. By comparing the results obtained through image based modelling to spatially averaged models, the impact of root architecture and geometry in water uptake was quantified. We observed that the spatially averaged models performed well in comparison to the image based models with <2% difference in uptake. However, the spatial averaging loses important information regarding the spatial distribution of water near the root system

python-ags4: A Python library to read, write, and validate AGS4 geodata files

Data gathered from geotechnical, geoenvironmental, and geophysical investigations can be broadly described as “geodata”. The AGS4 data format (Association of Geotechnical and Geoenvironmental Specialists, 2011, 2017, 2021b, 2022) is one of the most widely used data transmittal formats for geodata and is used across the world. It is a plain text format consisting of multiple tables of comma-separated values, tied together with a robust data schema and a comprehensive suite of validation rules. The basic structure of an AGS4 file is shown in Figure 1. Figure 1: Simplified schematic of AGS4 data structure Source: Association of Geotechnical and Geoenvironmental Specialists (2022) python-ags4 is a Python library that provides functionality to read, write, and validate AGS4 geodata files. It provides users with a gateway to access the full power of the Python ecosystem to explore, analyze, and visualize geodata. Pandas DataFrame (The pandas development team, 2020) is the primary data structure used within the library, therefore it can handle relatively large datasets reasonably fast. The data validation module checks the file for compliance with the validation rules and provides a detailed error report. An example error report is shown in Figure 2

Prognostic microRNA signatures derived from The Cancer Genome Atlas for head and neck squamous cell carcinomas

Identification of novel prognostic biomarkers typically requires a large dataset which provides sufficient statistical power for discovery research. To this end, we took advantage of the high‐throughput data from The Cancer Genome Atlas (TCGA) to identify a set of prognostic biomarkers in head and neck squamous cell carcinomas (HNSCC) including oropharyngeal squamous cell carcinoma (OPSCC) and other subtypes. In this study, we analyzed miRNA‐seq data obtained from TCGA patients to identify prognostic biomarkers for OPSCC. The identified miRNAs were further tested with an independent cohort. miRNA‐seq data from TCGA was also analyzed to identify prognostic miRNAs in oral cavity squamous cell carcinoma (OSCC) and laryngeal squamous cell carcinoma (LSCC). Our study identified that miR‐193b‐3p and miR‐455‐5p were positively associated with survival, and miR‐92a‐3p and miR‐497‐5p were negatively associated with survival in OPSCC. A combined expression signature of these four miRNAs was prognostic of overall survival in OPSCC, and more importantly, this signature was validated in an independent OPSCC cohort. Furthermore, we identified four miRNAs each in OSCC and LSCC that were prognostic of survival, and combined signatures were specific for subtypes of HNSCC. A robust 4‐miRNA prognostic signature in OPSCC, as well as prognostic signatures in other subtypes of HNSCC, was developed using sequencing data from TCGA as the primary source. This demonstrates the power of using TCGA as a potential resource to develop prognostic tools for improving individualized patient care