Ethiopian Crop Type 2020 (EthCT2020) dataset: Crop type data for environmental and agricultural remote sensing applications in complex Ethiopian smallholder wheat-based farming systems (Meher season 2020/21).

Crop type observation is crucial for various environmental and agricultural remote sensing applications including land use and land cover mapping, crop growth monitoring, crop modelling, yield forecasting, disease surveillance, and climate modelling. Quality-controlled georeferenced crop type information is essential for calibrating and validating machine learning algorithms. However, publicly available field data is scarce, particularly in the highly dynamic smallholder farming systems of sub-Saharan Africa. For the 2020/21 main cropping season (Meher), the Ethiopian Crop Type 2020 (EthCT2020) dataset compiled from multiple sources provides 2,793 harmonized, quality-controlled, and georeferenced in-situ samples on annual crop types (7 crop groups; 22 crop classes) at smallholder field level across the complex and highly fragmented agricultural landscape of Ethiopia. The focus was on rainfed, wheat-based farming systems. A nationwide ground data collection campaign (GDCC; Source 1) was designed using a stratification approach based on wheat crop calendar information, and 1,263 in-situ data samples were collected in selected sampling regions. This in-situ data pool was enriched with 1,530 wheat samples extracted from a) the Wheat Rust Toolbox (WRTB; Source 2; 734 samples), a database for wheat disease surveillance data [1] and b) an inhouse farm household survey database (FHSD; Source 3; 796 samples). Obtained field data was labelled according to the Joint Experiment for Crop Assessment and Monitoring (JECAM) guidelines for cropland and crop type definition and field data collection [2] and the FAO Indicative Crop Classification [3]. The EthCT2020 dataset underwent extensive processing including data harmonization, mixed pixel assessment through visual interpretation using 5 m Planet satellite image composites, and quality-control using Sentinel-2 NDVI homogeneity analysis. The EthCT2020 dataset is unique in terms of crop diversity, pixel purity, and spatial accuracy while targeting a countrywide distribution. It is representative of Ethiopia's complex and highly fragmented agricultural landscape and can be useful for developing new machine learning algorithms for land use land cover mapping, crop type mapping, agricultural monitoring, and yield forecasting in smallholder cropping systems. The dataset can also serve as a baseline input parameter for crop models, climate models, and crop disease and pest forecasting systems.

LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic ß cells.

Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning ß cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and ß cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human ß cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in ß cells to maintain appropriate insulin release.

Hierarchical cluster analysis and nonlinear mixed-effects modelling for candidate biomarker detection in preclinical models of cancer.

BACKGROUND: Preclinical models of cancer can be of translational benefit when assessing how different biomarkers are regulated in response to particular treatments. Detection of molecular biomarkers in preclinical models of cancer is difficult due inter-animal variability in responses, combined with limited accessibility of longitudinal data. METHODS: Nonlinear mixed-effects modelling (NLME) was used to analyse tumour growth data based on expected tumour growth rates observed 7 days after initial doses (DD7) of Radiotherapy (RT) and Combination of RT with DNA Damage Response Inhibitors (DDRi). Cox regression was performed to confirm an association between DD7 and survival. Hierarchical Cluster Analysis (HCA) was then used to identify candidate biomarkers impacting responses to RT and RT/DDRi and these were validated using NLME. RESULTS: Cox regression confirmed significant associations between DD7 and survival. HCA of RT treated samples, combined with NLME confirmed significant associations between DD7 and Cluster specific CD8+ Ki67 MFI, as well as DD7 and cluster specific Natural Killer cell density in RT treated mice. CONCLUSION: Application of NLME, as well as HCA of candidate biomarkers may provide additional avenues to assess the effect of RT in MC38 syngeneic tumour models. Additional studies would need to be conducted to confirm association between DD7 and biomarkers in RT/DDRi treated mice.

GLP1R and GIPR expression and signaling in pancreatic alpha cells, beta cells and delta cells.

Glucagon-like peptide-1 receptor (GLP1R) and glucose-dependent insulinotropic polypeptide receptor (GIPR) are transmembrane receptors involved in insulin, glucagon and somatostatin secretion from the pancreatic islet. Therapeutic targeting of GLP1R and GIPR restores blood glucose levels in part by influencing beta cell, alpha cell and delta cell function. Despite the importance of the incretin-mimetics for diabetes therapy, our understanding of GLP1R and GIPR expression patterns and signaling within the islet remain incomplete. Here, we present the evidence for GLP1R and GIPR expression in the major islet cell types, before addressing signaling pathway(s) engaged, as well as their influence on cell survival and function. While GLP1R is largely a beta cell-specific marker within the islet, GIPR is expressed in alpha cells, beta cells, and (possibly) delta cells. GLP1R and GIPR engage Gs-coupled pathways in most settings, although the exact outcome on hormone release depends on paracrine communication and promiscuous signaling. Biased agonism away from beta-arrestin is an emerging concept for improving therapeutic efficacy, and is also relevant for GLP1R/GIPR dual agonism. Lastly, dual agonists exert multiple effects on islet function through GIPR > GLP1R imbalance, increased GLP1R surface expression and cAMP signaling, as well as beneficial alpha cell-beta cell-delta cell crosstalk.

Synchronizing beta cells in the pancreas.

The secretion of insulin from the pancreas relies on both gap junctions and subpopulations of beta cells with specific intrinsic properties.

The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia.

Very high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties' response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS-NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.

Fine-tuned photochromic sulfonylureas for optical control of beta cell Ca2+ fluxes.

We previously developed, synthesized and tested light-activated sulfonylureas for optical control of KATP channels and pancreatic beta cell activity in vitro and in vivo. Such technology relies on installation of azobenzene photoswitches onto the sulfonylurea backbone, affording light-dependent isomerization, alteration in ligand affinity for SUR1 and hence KATP channel conductance. Inspired by molecular dynamics simulations and to further improve photoswitching characteristics, we set out to develop a novel push-pull closed ring azobenzene unit, before installing this on the sulfonylurea glimepiride as a small molecule recipient. Three fine-tuned, light-activated sulfonylureas were synthesized, encompassing azetidine, pyrrolidine and piperidine closed rings. Azetidine-, pyrrolidine- and piperidine-based sulfonylureas all increased beta cell Ca2+ -spiking activity upon continuous blue light illumination, similarly to first generation JB253. Notably, the pyrrolidine-based sulfonylurea showed superior switch OFF performance to JB253. As such, third generation sulfonylureas afford more precise optical control over primary pancreatic beta cells, and showcase the potential of pyrrolidine-azobenzenes as chemical photoswitches across drug classes.

Mixed effects modeling of radiotherapy in combination with immune checkpoint blockade or inhibitors of the DNA damage response pathway.

Dosage optimization to maximize efficacy and minimize toxicity is a potential issue when administering radiotherapy (RT) in combination with immune checkpoint blockade (ICB) or inhibitors of the DNA Damage Response Pathway (DDRi) in the clinic. Preclinical models and mathematical modeling can help identify ideal dosage schedules to observe beneficial effects of a tri-therapy. The aim of this study is to describe a mathematical model to capture the impact of RT in combination with inhibitors of the DNA Damage Response Pathway or blockade of the immune checkpoint protein - programmed death ligand 1 (PD-L1). This model describes how RT mediated activation of antigen presenting cells can induce an increase in cytolytic T cells capable of targeting tumor cells, and how combination drugs can potentiate the immune response by inhibiting the rate of T cell exhaustion. The model was fitted using preclinical data, where MC38 tumors were treated in vivo with RT alone or in combination with anti-PD-L1 as well as with either olaparib or the ataxia telangiectasia mutated (ATM) inhibitor-AZD0156. The model successfully described the observed data and goodness-of-fit, using visual predictive checks also confirmed a successful internal model validation for each treatment modality. The results demonstrated that the anti-PD-L1 effect in combination with RT was maximal in vivo and any additional benefit of DDRi at the given dosage and schedule used was undetectable. Model fit results indicated AZD0156 to be a more potent DDRi than olaparib. Simulations of alternative doses indicated that reducing efficacy of anti-PD-L1 by 68% would potentially provide evidence for a benefit of ATM inhibition in combination with ICB and increase the relative efficacy of tri-therapy.

Radiation in Combination with Immune Checkpoint Blockade and DNA Damage Response Inhibitors in Mice: Dosage Optimization in MC38 Syngeneic Tumors via Modelling and Simulation.

Clinical trials assessing the impact of radiotherapy (RT) in combination with DNA damage response pathway inhibitors (DDRis) and/or immune checkpoint blockade are currently ongoing. However, current methods for optimizing dosage and schedule are limited. A mathematical model was developed to capture the impacts of RT in combination with DDRi and/or anti-PD-L1 [immune checkpoint inhibitor (ICI)] on tumor immune interactions in the MC38 syngeneic tumor model. The model was fitted to datasets that assessed the impact of RT in combination with the DNA protein kinase inhibitor (DNAPKi) AZD7648. The model was further fitted to datasets from studies that were used to assess both RT/ICI combinations as well as RT/ICI combinations followed by concurrent administration of the poly ADP ribose polymerase inhibitor (PARPi) olaparib. Nonlinear mixed-effects modeling was performed followed by internal validation with visual predictive checks (VPC). Simulations of alternative dosage regimens and scheduling were performed to identify optimal candidate dosage regimens of RT/DNAPKi and RT/PARPi/ICI. Model fits and VPCs confirmed a successful internal validation for both datasets and demonstrated very small differences in the median, lower, and upper percentile values of tumor diameters between RT/ICI and RT/PARPi/ICI, which indicated that the triple combination of RT/PARPi/ICI at the given dosage and schedule does not provide additional benefit compared with ICI in combination with RT. Simulation of alternative dosage regimens indicated that lowering the dosage of ICI to between 2 and 4 mg/kg could induce similar benefits to the full dosage regimen, which could be of translational benefit. SIGNIFICANCE STATEMENT: This work provides a mixed-effects model framework to quantify the effects of combination radiotherapy/DNA damage response pathway inhibitors/immune checkpoint inhibitors in preclinical tumor models and identify optimal dosage regimens, which could be of translational benefit.

Architecture of androgen receptor pathways amplifying glucagon-like peptide-1 insulinotropic action in male pancreatic ß cells.

Male mice lacking the androgen receptor (AR) in pancreatic ß cells exhibit blunted glucose-stimulated insulin secretion (GSIS), leading to hyperglycemia. Testosterone activates an extranuclear AR in ß cells to amplify glucagon-like peptide-1 (GLP-1) insulinotropic action. Here, we examined the architecture of AR targets that regulate GLP-1 insulinotropic action in male ß cells. Testosterone cooperates with GLP-1 to enhance cAMP production at the plasma membrane and endosomes via: (1) increased mitochondrial production of CO2, activating the HCO3--sensitive soluble adenylate cyclase; and (2) increased Gαs recruitment to GLP-1 receptor and AR complexes, activating transmembrane adenylate cyclase. Additionally, testosterone enhances GSIS in human islets via a focal adhesion kinase/SRC/phosphatidylinositol 3-kinase/mammalian target of rapamycin complex 2 actin remodeling cascade. We describe the testosterone-stimulated AR interactome, transcriptome, proteome, and metabolome that contribute to these effects. This study identifies AR genomic and non-genomic actions that enhance GLP-1-stimulated insulin exocytosis in male ß cells.

Hypothalamic and brainstem glucose-dependent insulinotropic polypeptide receptor neurons employ distinct mechanisms to affect feeding.

Central glucose-dependent insulinotropic polypeptide (GIP) receptor (GIPR) signaling is critical in GIP-based therapeutics' ability to lower body weight, but pathways leveraged by GIPR pharmacology in the brain remain incompletely understood. We explored the role of Gipr neurons in the hypothalamus and dorsal vagal complex (DVC) - brain regions critical to the control of energy balance. Hypothalamic Gipr expression was not necessary for the synergistic effect of GIPR/GLP-1R coagonism on body weight. While chemogenetic stimulation of both hypothalamic and DVC Gipr neurons suppressed food intake, activation of DVC Gipr neurons reduced ambulatory activity and induced conditioned taste avoidance, while there was no effect of a short-acting GIPR agonist (GIPRA). Within the DVC, Gipr neurons of the nucleus tractus solitarius (NTS), but not the area postrema (AP), projected to distal brain regions and were transcriptomically distinct. Peripherally dosed fluorescent GIPRAs revealed that access was restricted to circumventricular organs in the CNS. These data demonstrate that Gipr neurons in the hypothalamus, AP, and NTS differ in their connectivity, transcriptomic profile, peripheral accessibility, and appetite-controlling mechanisms. These results highlight the heterogeneity of the central GIPR signaling axis and suggest that studies into the effects of GIP pharmacology on feeding behavior should consider the interplay of multiple regulatory pathways.

PEPITEM modulates leukocyte trafficking to reduce obesity-induced inflammation.

Dysregulation of leukocyte trafficking, lipid metabolism, and other metabolic processes are the hallmarks that underpin and drive pathology in obesity. Current clinical management targets alternations in lifestyle choices (e.g. exercise, weight loss) to limit the impact of the disease. Crucially, re-gaining control over the pathogenic cellular and molecular processes may offer an alternative, complementary strategy for obese patients. Here we investigate the impact of the immunopeptide, PEPITEM, on pancreas homeostasis and leukocyte trafficking in mice on high-fed obesogenic diet (HFD). Both prophylactic and therapeutic treatment with PEPITEM alleviated the effects of HFD on the pancreas, reducing pancreatic beta cell size. Moreover, PEPITEM treatment also limited T-cell trafficking (CD4+ T-cells and KLRG1+ CD3+ T-cells) to obese visceral, but not subcutaneous, adipose tissue. Similarly, PEPITEM treatment reduced macrophage numbers within the peritoneal cavity of mice on HFD diet at both 6 and 12 weeks. By contrast, PEPITEM therapy elevated numbers of T and B cells were observed in the secondary lymphoid tissues (e.g. spleen and inguinal lymph node) when compared to the untreated HFD controls. Collectively our data highlights the potential for PEPITEM as a novel therapy to combat the systemic low-grade inflammation experienced in obesity and minimize the impact of obesity on pancreatic homeostasis. Thus, offering an alternative strategy to reduce the risk of developing obesity-related co-morbidities, such as type 2 diabetes mellitus, in individuals at high risk and struggling to control their weight through lifestyle modifications.

Acid-Resistant BODIPY Amino Acids for Peptide-Based Fluorescence Imaging of GPR54 Receptors in Pancreatic Islets.

The G protein-coupled kisspeptin receptor (GPR54 or KISS1R) is an important mediator in reproduction, metabolism and cancer biology; however, there are limited fluorescent probes or antibodies for direct imaging of these receptors in cells and intact tissues, which can help to interrogate their multiple biological roles. Herein, we describe the rational design and characterization of a new acid-resistant BODIPY-based amino acid (Trp-BODIPY PLUS), and its implementation for solid-phase synthesis of fluorescent bioactive peptides. Trp-BODIPY PLUS retains the binding capabilities of both short linear and cyclic peptides and displays notable turn-on fluorescence emission upon target binding for wash-free imaging. Finally, we employed Trp-BODIPY PLUS to prepare some of the first fluorogenic kisspeptin-based probes and visualized the expression and localization of GPR54 receptors in human cells and in whole mouse pancreatic islets by fluorescence imaging.

Spatial distribution of heterogeneity as a modulator of collective dynamics in pancreatic beta-cell networks and beyond.

We study the impact of spatial distribution of heterogeneity on collective dynamics in gap-junction coupled beta-cell networks comprised on cells from two populations that differ in their intrinsic excitability. Initially, these populations are uniformly and randomly distributed throughout the networks. We develop and apply an iterative algorithm for perturbing the arrangement of the network such that cells from the same population are increasingly likely to be adjacent to one another. We find that the global input strength, or network drive, necessary to transition the network from a state of quiescence to a state of synchronised and oscillatory activity decreases as network sortedness increases. Moreover, for weak coupling, we find that regimes of partial synchronisation and wave propagation arise, which depend both on network drive and network sortedness. We then demonstrate the utility of this algorithm for studying the distribution of heterogeneity in general networks, for which we use Watts-Strogatz networks as a case study. This work highlights the importance of heterogeneity in node dynamics in establishing collective rhythms in complex, excitable networks and has implications for a wide range of real-world systems that exhibit such heterogeneity.

Revealing the tissue-level complexity of endogenous glucagon-like peptide-1 receptor expression and signaling.

The glucagon-like peptide-1 receptor (GLP1R) is a class B G protein-coupled receptor (GPCR) involved in glucose homeostasis and food intake. GLP1R agonists (GLP1RA) are widely used in the treatment of diabetes and obesity, yet visualizing the endogenous localization, organization and dynamics of a GPCR has so far remained out of reach. In the present study, we generate mice harboring an enzyme self-label genome-edited into the endogenous Glp1r locus. We also rationally design and test various fluorescent dyes, spanning cyan to far-red wavelengths, for labeling performance in tissue. By combining these technologies, we show that endogenous GLP1R can be specifically and sensitively detected in primary tissue using multiple colors. Longitudinal analysis of GLP1R dynamics reveals heterogeneous recruitment of neighboring cell subpopulations into signaling and trafficking, with differences observed between GLP1RA classes and dual agonists. At the nanoscopic level, GLP1Rs are found to possess higher organization, undergoing GLP1RA-dependent membrane diffusion. Together, these results show the utility of enzyme self-labels for visualization and interrogation of endogenous proteins, and provide insight into the biology of a class B GPCR in primary cells and tissue.

GC-Globulin/Vitamin D-Binding Protein Is Required for Pancreatic α-Cell Adaptation to Metabolic Stress.

GC-globulin (GC), or vitamin D-binding protein, is a multifunctional protein involved in the transport of circulating vitamin 25(OH)D and fatty acids, as well as actin scavenging. In the pancreatic islets, the gene encoding GC, GC/Gc, is highly localized to glucagon-secreting α-cells. Despite this, the role of GC in α-cell function is poorly understood. We previously showed that GC is essential for α-cell morphology, electrical activity, and glucagon secretion. We now show that loss of GC exacerbates α-cell failure during metabolic stress. High-fat diet-fed GC-/- mice have basal hyperglucagonemia, which is associated with decreased α-cell size, impaired glucagon secretion and Ca2+ fluxes, and changes in glucose-dependent F-actin remodelling. Impairments in glucagon secretion can be rescued using exogenous GC to replenish α-cell GC levels, increase glucagon granule area, and restore the F-actin cytoskeleton. Lastly, GC levels decrease in α-cells of donors with type 2 diabetes, which is associated with changes in α-cell mass, morphology, and glucagon expression. Together, these data demonstrate an important role for GC in α-cell adaptation to metabolic stress.

Median eminence blood flow influences food intake by regulating ghrelin access to the metabolic brain.

Central integration of peripheral appetite-regulating signals ensures maintenance of energy homeostasis. Thus, plasticity of circulating molecule access to neuronal circuits involved in feeding behavior plays a key role in the adaptive response to metabolic changes. However, the mechanisms involved remain poorly understood despite their relevance for therapeutic development. Here, we investigated the role of median eminence mural cells, including smooth muscle cells and pericytes, in modulating gut hormone effects on orexigenic/anorexigenic circuits. We found that conditional activation of median eminence vascular cells impinged on local blood flow velocity and altered ghrelin-stimulated food intake by delaying ghrelin access to target neurons. Thus, activation of median eminence vascular cells modulates food intake in response to peripheral ghrelin by reducing local blood flow velocity and access to the metabolic brain.

Acid-Resistant BODIPY Amino Acids for Peptide-Based Fluorescence Imaging of GPR54 Receptors in Pancreatic Islets.

The G protein-coupled kisspeptin receptor (GPR54 or KISS1R) is an important mediator in reproduction, metabolism and cancer biology; however, there are limited fluorescent probes or antibodies for direct imaging of these receptors in cells and intact tissues, which can help to interrogate their multiple biological roles. Herein, we describe the rational design and characterization of a new acid-resistant BODIPY-based amino acid (Trp-BODIPY PLUS), and its implementation for solid-phase synthesis of fluorescent bioactive peptides. Trp-BODIPY PLUS retains the binding capabilities of both short linear and cyclic peptides and displays notable turn-on fluorescence emission upon target binding for wash-free imaging. Finally, we employed Trp-BODIPY PLUS to prepare some of the first fluorogenic kisspeptin-based probes and visualized the expression and localization of GPR54 receptors in human cells and in whole mouse pancreatic islets by fluorescence imaging.

Enzyme self-label-bound ATTO700 in single-molecule and super-resolution microscopy.

Herein, we evaluate near-infrared ATTO700 as an acceptor in SNAP- and Halo-tag protein labelling for Förster Resonance Energy Transfer (FRET) by ensemble and single molecule measurements. Microscopy of cell surface proteins in live cells is perfomed including super-resolution stimulated emission by depletion (STED) nanoscopy.

Functional architecture of pancreatic islets identifies a population of first responder cells that drive the first-phase calcium response.

Insulin-secreting ß-cells are functionally heterogeneous. Whether there exist cells driving the first-phase calcium response in individual islets, has not been examined. We examine "first responder" cells, defined by the earliest [Ca2+] response during first-phase [Ca2+] elevation, distinct from previously identified "hub" and "leader" cells. We used islets isolated from Mip-CreER; Rosa-Stop-Lox-Stop-GCamP6s mice (ß-GCamP6s) that show ß-cell-specific GCamP6s expression following tamoxifen-induced CreER-mediated recombination. First responder cells showed characteristics of high membrane excitability and lower electrical coupling to their neighbors. The first-phase response time of ß-cells in the islet was spatially organized, dependent on the cell's distance to the first responder cell, and consistent over time up to approximately 24 h. When first responder cells were laser ablated, the first-phase [Ca2+] was slowed down, diminished, and discoordinated compared to random cell ablation. Cells that were next earliest to respond often took over the role of the first responder upon ablation. In summary, we discover and characterize a distinct first responder ß-cell state, critical for the islet first-phase response to glucose.