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Regulatory T cells (Treg) play a critical role in immune homeostasis by suppressing several aspects of the immune response. Herein, Glycoprotein A repetitions predominant (GARP), the docking receptor for latent transforming growth factor (LTGF-β), which promotes its activation, plays a crucial role in maintaining Treg mediated immune tolerance. After activation, Treg uniquely express GARP on their surfaces. Due to its location and function, GARP may represent an important target for immunotherapeutic approaches, including the inhibition of Treg suppression in cancer or the enhancement of suppression in autoimmunity. In the present review, we will clarify the cellular and molecular regulation of GARP expression not only in human Treg but also in other cells present in the tumor microenvironment. We will also examine the overall roles of GARP in the regulation of the immune system. Furthermore, we will explore potential applications of GARP as a predictive and therapeutic biomarker as well as the targeting of GARP itself in immunotherapeutic approaches.

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Climate change represents an intractable problem which urges a prompt intervention to be resolved. One of climate change's most destructive calamities is flash flooding. On that caveat, this study tries to identify the zones most susceptible to flash floods by utilizing machine learning technique. Initially, a digital elevation model (DEM) has been utilized to delineate a basin located in the city of New Cairo, Egypt, where the flash floods occur frequently. Subsequentially, 12 flood causative factors were calculated and mapped via ArcMap. Furthermore, the depth of runoff was calculated via HEC-RAS and employed as a flood causative factor. Additionally, both flooded points and flood causative factors have been employed by utilizing the “GARP”* approach to produce the Flood Hazard Map (FHM). The state-of-art in this study is to predict the hazard degree of flash floods by utilizing the simulated runoff depth which has been used as flood causative factor in the selected machine learning technique. The FHM anticipated approximately 20% of the total area to have a very high hazard of floods, whereas, more than two-thirds of the study area has expected to have low and very low flood hazard. In addition, the receiver operating characteristic “ROC” approach has been applied to examine the FHM, which estimated the area under curve as 96.88%. Finally, decision-makers can utilize the generated map to better comprehend repercussion of flooding and make adequate preparations to alleviate this risk. *GARP: “Genetic Algorithm for Rule-set Prediction”.

Due to the importance of both environmental protection and economic development, environmental auditing and accounting is a crucial subject. To assess the acceptable amount of environmental deterioration and the level of development, a detailed analysis of the benefits and costs of environmental harm is required. This paper provides guidelines on economic, social, and environmental issues for green accounting and reporting practises (GARPs) in the Indian automobile industry. A critical aspect in GARP is the implementation and evaluation of key performance indicators (KPIs). The data analysis for this work uses both qualitative and quantitative methodologies. A systematic questionnaire was utilised to gather the data, and barriers were found using the MINITAB analysis of variance (ANOVA) programme. The reliability of the identified KPI was tested using reliability analysis. The weights of KPI are calculated by analytical hierarchical process (AHP) analysis. The study report identified the lack of knowledge and inadequate strategic planning as significant barriers with a mean value of 3.53 and 3.3, and the calculated index value by AHP analysis for economic, social, and environmental factors is 0.364, 0.342, and 0.294. The identified weight of each GARP-KPI helps to automobile industries with self-assessment. It also supports improving the present situation by comparing the organisations on the basis of the KPI of GARP. This method compares the entire GARP performance and serves as a useful manual for an organisation looking to improve its green audit and reporting procedures.

Human regulatory T cells (Tregs) suppress other T cells by converting the latent, inactive form of TGF-β1 into active TGF-β1. In Tregs, TGF-β1 activation requires GARP, a transmembrane protein that binds and presents latent TGF-β1 on the surface of Tregs stimulated through their T cell receptor. However, GARP is not sufficient because transduction of GARP in non-Treg T cells does not induce active TGF-β1 production. RGD-binding integrins were shown to activate TGF-β1 in several non-T cell types. Here we show that αVβ8 dimers are present on stimulated human Tregs but not in other T cells, and that antibodies against αV or β8 subunits block TGF-β1 activation in vitro. We also show that αV and β8 interact with GARP/latent TGF-β1 complexes in human Tregs. Finally, a blocking antibody against β8 inhibited immunosuppression by human Tregs in a model of xenogeneic graft-vs.-host disease induced by the transfer of human T cells in immunodeficient mice. These results show that TGF-β1 activation on the surface of human Tregs implies an interaction between the integrin αVβ8 and GARP/latent TGF-β1 complexes. Immunosuppression by human Tregs can be inhibited by antibodies against GARP or against the integrin β8 subunit. Such antibodies may prove beneficial against cancer or chronic infections.

In the tumor microenvironment (TME), the transforming growth factor-β (TGF-β) and programmed cell death receptor 1 (PD-1)/programmed death ligand 1 (PD-L1) signaling axes are complementary, nonredundant immunosuppressive signaling pathways. Studies have revealed that active TGF-β is mainly released from the glycoprotein A repetitions predominant (GARP)-TGF-β complex on the surface of activated regulatory T cells (Tregs), B cells, natural killer (NK) cells, and tumor cells. The currently available antibodies or fusion proteins that target TGF-β are limited in their abilities to simultaneously block TGF-β release and neutralize active TGF-β in the TME, thus limiting their antitumor effects. We designed and constructed a bispecific, trifunctional antibody, namely, BPB-101, that specifically targets the GARP-TGF-β complex and/or small latent complex (SLC), active TGF-β, and PD-L1. The binding ability of BPB-101 to the different antigens was determined by ELISA, FACS, and biolayer interferometry (BLI). The blocking ability of BPB-101 to the TGF-β and PD-1/PD-L1 signaling axes was determined by reporter gene assay (RGA). The antitumor effect and biosafety of BPB-101 were determined in a transgenic mouse tumor model and cynomolgus monkeys, respectively. Stability assessments, including stability in serum, after exposure to light, after repeated freeze-thaw cycles, and after high-temperature stress tests had been completed to evaluate the stability of BPB-101. BPB-101 bound efficiently to different antigenic proteins: the GARP-TGF-β complex and/or SLC, active TGF-β, and PD-L1. Data showed that BPB-101 not only effectively inhibited the release of TGF-β from human Tregs, but also blocked both the TGF-β and PD-1/PD-L1 signaling pathways. In an MC38-hPD-L1 tumor-bearing C57BL/6-hGARP mouse model, BPB-101 at a dose of 5 mg/kg significantly inhibited tumor growth, with a complete elimination rate of 50%. Stability assessments confirmed the robustness of BPB-101. Furthermore, BPB-101 showed a favorable safety profile in nonhuman primate (NHP) toxicity studies. BPB-101 is a potentially promising therapeutic candidate that may address unmet clinical needs in cancer immunotherapy, thus, BPB-101 warrants further clinical investigation.

Glioblastoma (GB) is notoriously resistant to therapy. GB genesis and progression are driven by glioblastoma stem-like cells (GSCs). One goal for improving treatment efficacy and patient outcomes is targeting GSCs. Currently, there are no universal markers for GSCs. Glycoprotein A repetitions predominant (GARP), an anti-inflammatory protein expressed by activated regulatory T cells, was identified as a possible marker for GSCs. This study evaluated GARP for the detection of human GSCs utilizing a multidimensional experimental design that replicated several features of GB: (1) intratumoral heterogeneity, (2) cellular hierarchy (GSCs with varied degrees of self-renewal and differentiation), and (3) longitudinal GSC evolution during GB recurrence (GSCs from patient-matched newly diagnosed and recurrent GB). Our results indicate that GARP is expressed by GSCs across various cellular states and disease stages. GSCs with an increased GARP expression had reduced self-renewal but no alterations in proliferative capacity or differentiation commitment. Rather, GARP correlated inversely with the expression of GFAP and PDGFR-α, markers of astrocyte or oligodendrocyte differentiation. GARP had an abnormal nuclear localization (GARPNU+) in GSCs and was negatively associated with patient survival. The uniformity of GARP/GARPNU+ expression across different types of GSCs suggests a potential use of GARP as a marker to identify GSCs.

Platelets have been recently described as an important component of the innate and adaptive immunity through their interaction with immune cells. However, information on the platelet–T cell interaction in immune-mediated diseases remains limited. Glycoprotein A repetitions predominant (GARP) expressed on platelets and on activated regulatory T cells (Treg) is involved in the regulation of peripheral immune responses by modulating the bioavailability of transforming growth factor β (TGF-β). Soluble GARP (sGARP) exhibits strong regulatory and anti-inflammatory capacities both in vitro and in vivo, leading to the induction of peripheral Treg. Herein, we investigated the effect of platelet-derived GARP on the differentiation, phenotype, and function of T effector cells. CD4+CD25− T cells cocultured with platelets upregulated FoxP3, the master transcription factor for Treg, were anergic, and were strongly suppressive. These effects were reversed by using a blocking anti-GARP antibody, indicating a dependency on GARP. Importantly, melanoma patients in different stages of disease showed a significant upregulation of GARP on the platelet surface, correlating to a reduced responsiveness to immunotherapy. In conclusion, our data indicate that platelets induce peripheral Treg via GARP. These findings might contribute to diseases such as cancer-associated thrombocytosis, wherein poor prognosis and metastasis are associated with high counts of circulating platelets.

We explore a long-standing prediction in the international business literature that managers' subjective perceptions of political risk – not just the level of risk – are important for how firms manage political risk. The importance attributed to political risk by corporate executives has increased over the last 15 years and our results show that political risk is now considered more important than commodity (input) risk. Our analysis suggests that nearly 50% of firms avoid (not simply reduce) foreign direct investment because of political risk. Using a unique survey-based psychometric evaluation of manager risk aversion, we show that firms with risk averse executives are more likely to avoid investment in politically risky countries – a key implication of behavioral models. This relation is economically stronger when agency problems are more likely to be severe: for example, when executives are less aligned with shareholder value maximization, and when executives are younger (and therefore might put their personal career concerns in front of shareholders' interests). While numerous studies have shown that political risk affects foreign direct investment using objective measures of such risk (electoral uncertainty, conflicts, etc.), our study documents that executives' subjective perceptions of political risk are also important for political risk management.

Several types of cancer spread through the lymphatic system via the sentinel lymph nodes (LNs). Such LN-draining primary tumors, modified by tumor factors, lead to the formation of a metastatic niche associated with an increased number of Foxp3+ regulatory T cells (Tregs). These cells are expected to contribute to the elaboration of an immune-suppressive environment. Activated Tregs express glycoprotein A repetitions predominant (GARP), which binds and presents latent transforming growth factor beta 1 (TGF-β1) at their surface. GARP is also expressed by other non-immune cell types poorly described in LNs. Here, we mapped GARP expression in non-immune cells in human and mouse metastatic LNs. The mining of available (human and murine) scRNA-Seq datasets revealed GARP expression by blood (BEC)/lymphatic (LEC) endothelial, fibroblastic, and perivascular cells. Consistently, through immunostaining and in situ RNA hybridization approaches, GARP was detected in and around blood and lymphatic vessels, in (αSMA+) fibroblasts, and in perivascular cells associated with an abundant matrix. Strikingly, GARP was detected in LECs forming the subcapsular sinus and high endothelial venules (HEVs), two vascular structures localized at the interface between LNs and the afferent lymphatic and blood vessels. Altogether, we here provide the first distribution maps for GARP in human and murine LNs.