Despite their discovery in the early 20th century and intensive study over the last twenty years, nicotinic acetylcholine receptors (nAChRs) are still far from being well understood. Only a few chemical entities targeting nAChRs are currently undergoing clinical trials, and even fewer have reached the marketplace. In our efforts to discover novel and truly selective nAChR ligands, we designed and synthesized a series of chiral cyclopropane-containing α4β2-specific ligands that display low nanomolar binding affinities and excellent subtype selectivity, while acting as partial agonists at α4β2-nAChRs. Their favorable antidepressant-like properties were demonstrated in the classical mouse forced swim test. Preliminary ADMET studies and broad screening towards other common neurotransmitter receptors were also carried out to further evaluate their safety profile and eliminate their potential off-target activity. These highly potent cyclopropane ligands possess superior subtype selectivity compared to other α4β2-nAChR agonists reported to date, including the marketed drug varenicline, and therefore may fully satisfy the crucial prerequisite for avoiding adverse side effects. These novel chemical entities could potentially be advanced to the clinic as new drug candidates for treating depression.

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Immune checkpoint blockade (ICB) has a limited effect on colorectal cancer, underlining the requirement of co-targeting the complementary mechanisms. Here, we identified prostaglandin E2 (PGE 2) receptor 4 (EP4) as the master regulator of immunosuppressive myeloid cells (IMCs), which are the major driver of resistance to ICB therapy. PGE 2-bound EP4 promotes the differentiation of immunosuppressive M2 macrophages and myeloid-derived suppressor cells (MDSCs) and reduces the expansion of immunostimulated M1 macrophages. To explore the immunotherapeutic role of EP4 signaling, we developed a novel and selective EP4 antagonist TP-16. TP-16 effectively blocked the function of IMCs and enhanced cytotoxic T-cellmediated tumor elimination in vivo. Cell co-culture experiments revealed that TP-16 promoted T-cell proliferation, which was impaired by tumor-derived CD11b + myeloid cells. Notably, TP-16 and anti-PD-1 combination therapy significantly impeded tumor progression and prolonged mice survival. We further demonstrated that TP-16 increased responsiveness to anti-PD-1 therapy in an IMC-related spontaneous colorectal cancer mouse model. In summary, this study demonstrates that inhibition of EP4-expressing IMCs may offer a potential strategy for enhancing the efficacy of immunotherapy for colorectal cancer.

Prostaglandin E2 (PGE2), a major cyclooxygenase-2 (COX-2) product, is highly secreted by the osteoblast lineage in the subchondral bone tissue of osteoarthritis (OA) patients. However, NSAIDs, including COX-2 inhibitors, have severe side effects during OA treatment. Therefore, the identification of novel drug targets of PGE2 signaling in OA progression is urgently needed. Osteoclasts play a critical role in subchondral bone homeostasis and OA-related pain. However, the mechanisms by which PGE2 regulates osteoclast function and subsequently subchondral bone homeostasis are largely unknown. Here, we show that PGE2 acts via EP4 receptors on osteoclasts during the progression of OA and OA-related pain. Our data show that while PGE2 mediates migration and osteoclastogenesis via its EP2 and EP4 receptors, tissue-specific knockout of only the EP4 receptor in osteoclasts (EP4LysM) reduced disease progression and osteophyte formation in a murine model of OA. Furthermore, OA-related pain was alleviated in the EP4LysM mice, with reduced Netrin-1 secretion and CGRP-positive sensory innervation of the subchondral bone. The expression of platelet-derived growth factor-BB (PDGF-BB) was also lower in the EP4LysM mice, which resulted in reduced type H blood vessel formation in subchondral bone. Importantly, we identified a novel potent EP4 antagonist, HL-43, which showed in vitro and in vivo effects consistent with those observed in the EP4LysM mice. Finally, we showed that the Gαs/PI3K/AKT/MAPK signaling pathway is downstream of EP4 activation via PGE2 in osteoclasts. Together, our data demonstrate that PGE2/EP4 signaling in osteoclasts mediates angiogenesis and sensory neuron innervation in subchondral bone, promoting OA progression and pain, and that inhibition of EP4 with HL-43 has therapeutic potential in OA.

Purpose: Immunotherapies targeting immune checkpoint molecules have shown promising treatment for a subset of cancers; however, many “cold” tumors, such as prostate cancer, remain unresponsive. We aimed to identify a potential targetable marker relevant to prostate cancer and develop novel immunotherapy. Experimental Design: Analysis of transcriptomic profiles at single-cell resolution was performed in clinical patients' samples, along with integrated analysis of multiple RNA-sequencing datasets. The antitumor activity of YY001, a novel EP4 antagonist, combined with anti–programmed cell death protein 1 (PD-1) antibody was evaluated both in vitro and in vivo. Results: We identified EP4 (PTGER4) as expressed in epithelial cells and various immune cells and involved in modulating the prostate cancer immune microenvironment. YY001, a novel EP4 antagonist, inhibited the differentiation, maturation, and immunosuppressive function of myeloid-derived suppressor cells (MDSC) while enhancing the proliferation and anticancer functions of T cells. Furthermore, it reversed the infiltration levels of MDSCs and T cells in the tumor microenvironment by overturning the chemokine profile of tumor cells in vitro and in vivo. The combined immunotherapy demonstrated a robust antitumor immune response as indicated by the robust accumulation and activation of CD8+ cytotoxic T cells, with a significantly decreased MDSC ratio and reduced MDSC immunosuppression function. Conclusions: Our study identified EP4 as a specific target for prostate cancer immunotherapy and demonstrated that YY001 inhibited the growth of prostate tumors by regulating the immune microenvironment and strongly synergized with anti–PD-1 antibodies to convert completely unresponsive prostate cancers into responsive cancers, resulting in marked tumor regression, long-term survival, and lasting immunologic memory.

Sharing charging stations are an effective solution for daily usage of electric vehicles charging, however, the area with high demand cannot provide enough stations while there are plenty of stations left idle in remote areas with less demand. The core of the problem is the imbalance of demand and supply. In other word, we need to allocate the charging station to the appropriate locations to balance demand and supply. This study aims to solve the problem of locating charging stations for public electric vehicles (PUEVs), to improve the sharing charging level. We take into consideration the factors affecting charging station locations including mileage, PUEV distribution and passenger distribution. A Non-deterministic Polynomial (NP) model aiming to minimize the total vehicle service distance is developed. We use an agent-based model to simulate the optimized charging station location based on Anylogic. Through a case study of Beijing, we test the model in five situations. This paper concludes that priority, mileage, PUEV distribution and passenger distribution are the key factors affecting the location of PUEV charging stations, with exogenous variables such as the type of circuit and the voltage drawn as constants. The results of one situation show that the existing layout of the charging stations is unreasonable when charging frequency is sharply variant; this paper optimizes the existing location by improving the constraint for the smallest number of charging stations; the proposed model can be used for EV charging stations' location in densely populated metropolis.INDEX TERMS Agent, charging frequency, sharing charging, electric vehicles, location.

Mercaptoacetamide-based ligands have been designed as a new class of histone deacetylase (HDAC) inhibitors for possible use in the treatment of neurodegenerative diseases. The thiol group of these compounds provides a key binding element for interaction with the catalytic zinc ion, and thus differs from the more typically employed hydroxamic acid based zinc binding groups. Herein we disclose the chemistry and biology of some substituted mercaptoacetamides with the intention of increasing HDAC6 isoform selectivity while maintaining potency similar to their hydroxamic acid analogues. The introduction of a stereocenter α to the thiol group was found to have a considerable impact on HDAC inhibitor potency. These new compounds were also profiled for their therapeutic potential in an in vitro model of stress-induced neuronal injury and were found to act as nontoxic neuroprotective agents.

Objective: Saliva glucose has been widely used in diagnosing and monitoring diabetes, but the saliva collection method will affect saliva glucose concentration. So, this study aims to identify the ideal saliva collection method. Method: A total amount of six saliva collection methods were employed in 80 healthy participants in the morning. Besides, three unstimulated saliva methods were employed in another 30 healthy participants in the morning; in the meantime the blood glucose of these 30 participants was detected with a Roche blood glucose meter. The glucose oxidase method with 2, 4, 6-tribromo-3-hydroxybenzoic acid (TBHBA) as the chromogen has been improved to be suitable for healthy people, through the selection of the optimal pH value and ionic strength of the reaction system. This method was used for the detection of saliva glucose. Results: The improved method obtained absorbance at the wavelength of 520 nm, and the optimized parameter combination was pH 6.5 and 5 mg/dL NaCl. The lower limit of glucose detection was 0.1 mg/dL. Unstimulated saliva glucose concentration was higher than stimulated saliva glucose concentration. Unstimulated parotid saliva glucose concentration was the highest. Besides, unstimulated saliva glucose has a better normal distribution effect. Meantime, it was found that unstimulated parotid saliva was the most highly correlated with blood glucose (R2 = 0.707). Conclusions: the saliva collection method was an important factor that affected saliva glucose concentration. Unstimulated parotid saliva was the most highly correlated with blood glucose, which provided a reference for prediction of diabetes mellitus.