Improving wildlife tracking using 3D information

The monitoring of wildlife populations is of growing importance due to the worldwide endangerment of many species, global climate change, and land cover change. Wildlife monitoring by camera traps is an established and non-invasive standard approach to quantify species diversity, estimate occupancy and relative abundance and track animal behaviour in 24/7 documentation. We propose a novel wildlife-specific 3D multi-object tracking workflow using inexpensive stereo camera traps. By embedding carefully efficient 2D methods into the overall 3D workflow, we avoid, on the one hand, costly processing of complex 3D data structures, i.e., 3D point clouds but on the other hand outperform significantly typical 2D tracking approaches with our overall 3D workflow in terms of international established multi-object tracking metrics, i.e., with respect to the reliability and accuracy of the tracking results. The code is available at https://github.com/m-klasen/3d_wildlife-tracking     

Measuring tree-ring widths using the CooRecorder software application

We present a brief overview of how to measure tree-ring widths in the software application CooRecorder (Cybis Elektronik & Data AB) for tree-ring analysis complementing two video tutorials. The first tutorial covers the basics of opening files, measuring ring widths, preliminary crossdating with a reference chronology, and setting dates. The second tutorial covers setting earlywood-latewood boundaries, measuring across cracks, inserting locally absent or missing rings, manual adjustments, and metadata. The video tutorials can be found here https://www.youtube.com/watch?v=c-GNKHVUj9I and here https://www.youtube.com/watch?v=xO7Phc93xyM&t=3s. Videos have been closed-captioned in English. Video is also accessible via Mendeley Data, https://doi.org/10.17632/r3v7236kkz.1.     

Automated distance estimation for wildlife camera trapping

The ongoing biodiversity crisis calls for accurate estimation of animal density and abundance to identify sources of biodiversity decline and effectiveness of conservation interventions. Camera traps together with abundance estimation methods are often employed for this purpose. The necessary distances between camera and observed animals are traditionally derived in a laborious, fully manual or semi-automatic process. Both approaches require reference image material, which is both difficult to acquire and not available for existing datasets. We propose a fully automatic approach we call AUtomated DIstance esTimation (AUDIT) to estimate camera-to-animal distances. We leverage existing state-of-the-art relative monocular depth estimation and combine it with a novel alignment procedure to estimate metric distances. AUDIT is fully automated and requires neither the comparison of observations in camera trap imagery with reference images nor capturing of reference image material at all. AUDIT therefore relieves biologists and ecologists from a significant workload.We evaluate AUDIT on a zoo scenario dataset unseen during training where we achieve a mean absolute distance estimation error over all animal instances of only 0.9864 m and mean relative error (REL) of 0.113. The code and usage instructions are available at https://github.com/PJ-cs/DistanceEstimationTracking     

Dual function of the CHS3-CSA1 immune receptor pair

Plant nucleotide-binding leucine-rich repeat (NLR) receptors mediate specific recognition of pathogen effectors to initiate effector-triggered immunity. Recently, studies by Schulze et al., Yang et al., and Gu et al. collectively show that the Arabidopsis (Arabidopsis thaliana) NLR pair CHS3-CSA1 acts through two distinct activation modes to recognize different pathogen effectors, thus revealing the dual function of the CHS3-CSA1 pair in plant disease resistance.     

A comprehensive review on the phytochemistry,pharmacokinetics, and antidiabetic effect of Ginseng

BackgroundRadix Ginseng, one of the well-known medicinal herbs, has been used in the management of diabetes and its complications for more than 1000 years.PurposeThe aim of this review is devoted to summarize the phytochemistry and pharmacokinetics of Ginseng, and provide evidence for the antidiabetic effects of Ginseng and its ingredients as well as the underlying mechanisms involved.MethodsFor the purpose of this review, the following databases were consulted: the PubMed Database (https://pubmed.ncbi.nlm.nih.gov), Chinese National Knowledge Infrastructure (http://www.cnki.net), National Science and Technology Library (http://www.nstl.gov.cn/), Wanfang Data (http://www.wanfangdata.com.cn/) and the Web of Science Database (http://apps.webofknowledge.com/).ResultsGinseng exhibits glucose-lowering effects in different diabetic animal models. In addition, Ginseng may prevent the development of diabetic complications, including liver, pancreas, adipose tissue, skeletal muscle, nephropathy, cardiomyopathy, retinopathy, atherosclerosis and others. The main ingredients of Ginseng include ginsenosides and polysaccharides. The underlying mechanisms whereby this herb exerts antidiabetic activities may be attributed to the regulation of multiple signaling pathways, including IRS1/PI3K/AKT, LKB1/AMPK/FoxO1, AGEs/RAGE, MAPK/ERK, NF-κB, PPARδ/STAT3, cAMP/PKA/CERB and HIF-1α/VEGF, etc. The pharmacokinetic profiles of ginsenosides provide valuable information on therapeutic efficacy of Ginseng in diabetes. Although Ginseng is well-tolerated, dietary consumption of this herb should follow the doctors’ advice.ConclusionGinseng may offer an alternative strategy in protection against diabetes and its complications through the regulations of the multi-targets via various signaling pathways. Efforts to understand the underlying mechanisms with strictly-controlled animal models, combined with well-designed clinical trials and pharmacokinetic evaluation, will be important subjects of the further investigations and weigh in translational value of this herb in diabetes management.     

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.     

Phytochromes and flowering: legumes do it another way

Phytochromes have a crucial role in the regulation of flowering in many plants, but the underlying molecular mechanisms vary among species. Recently, Lin et al. described a unique phytochrome A (phyA)-controlled photoperiodic flowering pathway in soybean (Glycine max), revealing a novel mechanism for photoperiodic regulation of flowering.     

The most abundant mammals on Earth

New estimates of global mammal abundance that use relationships between traits, estimates of range size, and International Union for Conservation of Nature’s (IUCN’s) Red List categories to predict the biomass of thousands of species have been developed by Greenspoon et al. This approach and some of the challenges that contribute to these estimates are summarized here.     

A novel module regulating ROS in NLR-mediated immunity

The regulatory mechanisms of apoplastic reactive oxygen species (ROS) production during pattern-triggered immunity (PTI) are well known. However, how ROS levels are regulated during effector-triggered immunity (ETI) remains largely unknown. Recently, Zhang et al. discovered that MAPK-Alfin-like 7 module enhances nucleotide-binding, leucine-rich repeat receptor (NLR)-mediated immunity by negatively regulating genes encoding ROS scavenging enzymes, deepening our understanding of ROS control during ETI in plants.     

How to build and install your own CaptuRING

CaptuRING is a reliable and affordable tool to transform tree-ring samples into digital images combining open source software and do-it-yourself philosophies. A Raspberry Pi runs the system through an Arduino board that controls the wood sample movement across a linear screw at the time that a digital camera takes sequential high resolution (>4500 dpi) images from a wood sample. Here, we present three video tutorials, with English and Spanish subtitles, to construct and install CaptuRING (github.com/CambiumRG/CaptuRING) from scratch. First video tutorial explains the necessary components and how to assemble them to construct the CaptuRING platform, second tutorial covers Arduino board and Raspberry Pi connections, and the third tutorial is devoted to hardware configuration, software installation and CaptuRING use.     

Deep learning-based method for predicting and classifying the binding affinity of protein-protein complexes

Protein-protein interactions (PPIs) play a critical role in various biological processes. Accurately estimating the binding affinity of PPIs is essential for understanding the underlying molecular recognition mechanisms. In this study, we employed a deep learning approach to predict the binding affinity (ΔG) of protein-protein complexes. To this end, we compiled a dataset of 903 protein-protein complexes, each with its corresponding experimental binding affinity, which belong to six functional classes. We extracted 8 to 20 non-redundant features from the sequence information as well as the predicted three-dimensional structures using feature selection methods for each protein functional class. Our method showed an overall mean absolute error of 1.05 kcal/mol and a correlation of 0.79 between experimental and predicted ΔG values. Additionally, we evaluated our model for discriminating high and low affinity protein-protein complexes and it achieved an accuracy of 87% with an F1 score of 0.86 using 10-fold cross-validation on the selected features. Our approach presents an efficient tool for studying PPIs and provides crucial insights into the underlying mechanisms of the molecular recognition process. The web server can be freely accessed at https://web.iitm.ac.in/bioinfo2/DeepPPAPred/index.html     

ParaSiteDB – A user-friendly database for managing a parasitological collection

ParaSiteDB is an application for arranging and managing a parasitological collection. It has been designed to provide a user-friendly, easily manageable and searchable site and is suitable for small to bigger collections.The source code of the application is available on GitHub: https://github.com/goobar4/aacrg.The demonstration version of the application is available on https://syrota.info/wormbasehttp://syrota.info/wormbase.     

Sense the moist and feel the heat: mosquito host and oviposition site detection

Laursen et al. identified coreceptor Ir93a that is required for humidity and thermal sensing in the mosquito species Anopheles gambiae and Aedes aegypti. Behavioural studies with mutant mosquitoes with disrupted Ir93a revealed that they were less attracted to a blood meal source and oviposition site at close distance.     

Leveraging glycoside-targeted metabolomics to gain insight into biological function

In plants, uridine diphosphate (UDP)-dependent glycosyltransferases (UGTs) catalyze glycosylation of secondary metabolites, but assigning physiological functions to UGTs is still a daunting task. The recent study of Wu et al. presents a useful method to resolve this problem by elegantly combining modification-specific metabolomics with isotope tracing.     

Feeding the world sustainably: efficient nitrogen use

Globally, overuse of nitrogen (N) fertilizers in croplands is causing severe environmental pollution. In this context, Gu et al. suggest environmentally friendly and cost-effective N management practices and Hamani et al. highlight the use of microbial inoculants to improve crop yields, while reducing N-associated environmental pollution and N-fertilizer use.     

Pan-genome for pearl millet that beats the heat

A better understanding of crop genomes reveals that structural variations (SVs) are crucial for genetic improvement. A graph-based pan-genome by Yan et al. uncovered 424 085 genomic SVs and provided novel insights into heat tolerance of pearl millet. We discuss how these SVs can fast-track pearl millet breeding under harsh environments.     

Too many candidates: Embedded covariate selection procedure for species distribution modelling with the covsel R package

• 1.Selecting the best subset of covariates out of a panel of many candidates is a key and highly influential stage of the species distribution modelling process. Yet, there is currently no commonly accepted and widely adopted standard approach by which to perform this selection.
• 2.We introduce a two-step “embedded” covariate selection procedure aimed at optimizing the predictive ability and parsimony of species distribution models fitted in a context of high-dimensional candidate covariate space. The procedure combines a collinearity-filtering algorithm (Step A) with three model-specific embedded regularization techniques (Step B), including generalized linear model with elastic net regularization, generalized additive model with null-space penalization, and guided regularized random forest.
• 3.We evaluated the embedded covariate selection procedure through an example application aimed at modelling the habitat suitability of 50 species in Switzerland from a suite of 123 candidate covariates. We demonstrated the ability of the embedded covariate selection procedure to provide significantly more accurate species distribution models as compared to models obtained with alternative procedures. Model performance was independent of the characteristics of the species data, such as the number of occurrence records or their spatial distribution across the study area.
• 4.We implemented and streamlined our embedded covariate selection procedure in the covsel R package, paving the way for a ready-to-use, automated, covariate selection tool that was missing in the field of species distribution modelling. All the information required for installing and running the covsel R package is openly available on the GitHub repository https://github.com/N-SDM/covsel.

     

Unleashing the potential of peptides in agriculture and beyond

Peptides display a broad range of regulatory functions. Ormancey et al. recently identified an important new mechanism – complementary peptides (cPEPs) – that provide a versatile means to control cell functions. We draw a parallel between RNA and peptide biology, and discuss new routes of investigation and industrial applications opened by this work.     

Effector protein structures: a tale of evolutionary relationship

Effector proteins are highly diverse, often lacking similarity in their protein sequences, making it challenging to determine their biological function. Using AlphaFold2 (AF2), Seong and Krasileva recently found that effector structures, but not sequences, share commonality. This helps further understanding of effector evolution across fungal species and reveals unique sequence-unrelated, structurally similar, effector families.