The effects of functional training on physical fitness and skill-related performance among basketball players: a systematic review.

Background: Evidence suggests that functional training (FT) positively impacts physical fitness and sports performance. However, a systematic review addressing the effects of FT on basketball players remains absent. This systematic review aims to explore the influence of FT on physical fitness and skill-related performance in basketball players. Methods: We searched six databases: Web of Science, Scopus, PubMed, China National Knowledge Infrastructure (CNKI), EBSCOhost, and Google Scholar. The search utilized a combination of keywords related to FT, physical fitness, and basketball. The Eligibility Criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines were followed in this systematic review. Results: 11 studies were ultimately included in this review, collectively recruiting 333 basketball players. These studies demonstrated that FT significantly improved muscle strength, linear speed, cardiovascular endurance, flexibility, balance, and muscular endurance. However, the effects of FT on power, change-of-direction speed, and basketball-related performance were inconsistent. Most studies showed FT significantly improves these three variables, but a small number of studies did not find positive effects of FT using specific tests including standing long jump, Sargent jump, touch high, lane agility, lateral shuffle, dribbling line drill, and free-throw tests. Conclusion: FT is an effective training method for enhancing physical fitness including muscle strength, linear speed, cardiovascular endurance, flexibility, balance, and muscular endurance. However, the effects of FT on power, change-of-direction speed, and basketball-related performance were divergent. Some tests were not improved after FT potentially due to the short program lengths and training session durations, varied athletic levels of players examined, and different foci of the FT exercises administered. The collective evidence suggests FT programs, especially the specific exercises prescribed, should be tailored to the desired training objectives. More studies investigating the effects of FT on physical fitness and basketball-related performance with established tests are encouraged in the future to expand the current evidence base. Systematic Review Registration: https://inplasy.com/, Identifier INPLASY202360072.

PPARG-mediated autophagy activation alleviates inflammation in rheumatoid arthritis.

INTRODUCTION: Rheumatoid arthritis (RA) is a systemic inflammatory autoimmune disease characterized by joint inflammation and bone damage, that not only restricts patient activity but also tends to be accompanied by a series of complications, seriously affecting patient prognosis. Peroxisome proliferator-activated receptor gamma (PPARG), a receptor that controls cellular metabolism, regulates the function of immune cells and stromal cells. Previous studies have shown that PPARG is closely related to the regulation of inflammation. However, the role of PPARG in regulating the pathological processes of RA is poorly understood. MATERIALS AND METHODS: PPARG expression was examined in the synovial tissues and peripheral blood mononuclear cells (PBMCs) from RA patients and the paw of collagen-induced arthritis (CIA) model rats. Molecular biology experiments were designed to examine the effect of PPARG and cannabidiol (CBD) on RAW264.7 cells and CIA rats. RESULTS: The results reveal that PPARG accelerates reactive oxygen species (ROS) clearance by promoting autophagy, thereby inhibiting ROS-mediated macrophage polarization and NLRP3 inflammasome activation. Notably, CBD may be a promising candidate for understanding the mechanism by which PPARG regulates autophagy-mediated inflammation. CONCLUSIONS: Taken together, these findings indicate that PPARG may have a role for distinguishing between RA patients and healthy control, and for distinguishing RA activity; moreover, PPARG could be a novel pharmacological target for alleviating RA through the mediation of autophagy. CBD can act as a PPARG agonist that alleviates the inflammatory progression of RA.

Dihydroartemisinin alleviates erosive bone destruction by modifying local Treg cells in inflamed joints: A novel role in the treatment of rheumatoid arthritis.

Treg cell-based therapy has exhibited promising efficacy in combatting rheumatoid arthritis (RA). Dihydroartemisinin (DHA) exerts broad immunomodulatory effects across various diseases, with its recent spotlight on T-cell regulation in autoimmune conditions. The modulation of DHA on Treg cells and its therapeutic role in RA has yet to be fully elucidated. This study seeks to unveil the influence of DHA on Treg cells in RA and furnish innovative substantiation for the potential of DHA to ameliorate RA. To this end, we initially scrutinized the impact of DHA-modulated Treg cells on osteoclast (OC) formation in vitro using Treg cell-bone marrow-derived monocyte (BMM) coculture systems. Subsequently, employing the collagen-induced arthritis (CIA) rat model, we validated the efficacy of DHA and probed its influence on Treg cells in the spleen and popliteal lymph nodes (PLN). Finally, leveraging deep proteomic analysis with data-independent acquisition (DIA) and parallel accumulation-serial fragmentation (PASEF) technology, we found the alterations in the Treg cell proteome in PLN by proteomic analysis. Our findings indicate that DHA augmented suppressive Treg cells, thereby impeding OC formation in vitro. Consistently, DHA mitigated erosive joint destruction and osteoclastogenesis by replenishing splenic and joint-draining lymph node Treg cells in CIA rats. Notably, DHA induced alterations in the Treg cell proteome in PLN, manifesting distinct upregulation of alloantigen Col2a1 (Type II collagen alfa 1 chain) and CD8a (T-cell surface glycoprotein CD8 alpha chain) in Treg cells, signifying DHA's targeted modulation of Treg cells, rendering them more adept at sustaining immune tolerance and impeding bone erosion. These results unveil a novel facet of DHA in the treatment of RA.

Metal complexes bearing EGFR-inhibiting ligands as promising anticancer agents.

Overexpression of the epidermal growth factor receptor (EGFR, erbB1) has been observed in a wide range of solid tumors and has frequently been associated with poor prognosis. As a result, EGFR inhibition has become an attractive anticancer drug design strategy, and a large number of small molecular inhibitors have been developed. Despite the widespread clinical use of EGFR tyrosine kinase inhibitors (TKIs), their drug resistance, inadequate accumulation in tumors, and severe side effects have spurred the search for better antitumor drugs. Metal complexes have attracted much attention because of their different mechanisms compared with EGFR-TKIs. Therefore, the combination of metals and inhibitors is a promising anticancer strategy. For example, Ru and Pt centers are introduced to design complexes with double or multiple targets, while Au complexes are combined with inhibitors to overcome drug resistance. Co complexes are designed as prodrugs with weak side effects and enhanced targeting by the hypoxia activation strategy, and other metals such as Rh and Fe enhance the anticancer effect of the complexes. In addition, the introduction of Ga center is beneficial to the development of nuclear imaging tracers. In this paper, metal EGFR-TKI complexes in the last 15 years are reviewed, their mechanisms are briefly introduced, and their advantages are summarized.

Metal-Phenolic-Mediated Assembly of Functional Small Molecules into Nanoparticles: Assembly and Bioapplications.

Small molecules, including therapeutic drugs and tracer molecules, play a vital role in biological processing, disease treatment and diagnosis, and have inspired various nanobiotechnology approaches to realize their biological function, particularly in drug delivery. Desirable features of a delivery system for functional small molecules (FSMs) include high biocompatibility, high loading capacity, and simple manufacturing processes, without the need for chemical modification of the FSM itself. Herein, we report a simple and versatile approach, based on metal-phenolic-mediated assembly, for assembling FSMs into nanoparticles (i.e., FSM-MPN NPs) under aqueous and ambient conditions. We demonstrate loading of anticancer drugs, latency reversal agents, and fluorophores at up to ~80 % that is mostly facilitated by π and hydrophobic interactions between the FSM and nanoparticle components. Secondary nanoparticle engineering involving coating with a polyphenol-antibody thin film or sequential co-loading of multiple FSMs enables cancer cell targeting and combination delivery, respectively. Incorporating fluorophores into FSM-MPN NPs enables the visualization of biodistribution at different time points, revealing that most of these NPs are retained in the kidney and heart 24 h post intravenous administration. This work provides a viable pathway for the rational design of small molecule nanoparticle delivery platforms for diverse biological applications.

Simultaneous Activation of Immunogenic Cell Death and cGAS-STING Pathway by Liver- and Mitochondria-Targeted Gold(I) Complexes for Chemoimmunotherapy of Hepatocellular Carcinoma.

Induction of immunogenic cell death (ICD) and activation of the cyclic GMP-AMP synthase stimulator of interferon gene (cGAS-STING) pathway are two potent anticancer immunotherapeutic strategies in hepatocellular carcinoma (HCC). Herein, 12 liver- and mitochondria-targeting gold(I) complexes (9a-9l) were designed and synthesized. The superior complex 9b produced a considerable amount of reactive oxygen species (ROS) and facilitated DNA excretion, the ROS-induced ICD and DNA activated the cGAS-STING pathway, both of which evoked an intense anticancer immune response in vitro and in vivo. Importantly, 9b strongly inhibited tumor growth in a patient-derived xenograft model of HCC. Overall, we present the first case of simultaneous ICD induction and cGAS-STING pathway activation within the same gold-based small molecule, which may provide an innovative strategy for designing chemoimmunotherapies for HCC.

False Correlation Reduction for Offline Reinforcement Learning.

Offline reinforcement learning (RL) harnesses the power of massive datasets for resolving sequential decision problems. Most existing papers only discuss defending against out-of-distribution (OOD) actions while we investigate a broader issue, the false correlations between epistemic uncertainty and decision-making, an essential factor that causes suboptimality. In this paper, we propose falSe COrrelation REduction (SCORE) for offline RL, a practically effective and theoretically provable algorithm. We empirically show that SCORE achieves the SoTA performance with 3.1x acceleration on various tasks in a standard benchmark (D4RL). The proposed algorithm introduces an annealing behavior cloning regularizer to help produce a high-quality estimation of uncertainty which is critical for eliminating false correlations from suboptimality. Theoretically, we justify the rationality of the proposed method and prove its convergence to the optimal policy with a sublinear rate under mild assumptions.

Deciphering the pivotal role of people with high-frequency occupational animal exposure in antibiotic resistance transmission between humans and animals.

BACKGROUND: The spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) among humans and food-producing animals has been widely reported. However, the transmission routes and associated risk factors remain incompletely understood. METHODS: Here, we used commensal Escherichia coli bacteria strains from faeces of pigs and local citizens [HEG: high exposure group (pig breeders, butchers or restaurant chefs) and LEG: low exposure group (other occupations)] to explore the dynamics of ARB and ARG transmission between animals and humans. RESULTS: Most ARGs (96%) present in pigs were shared with humans. Carriage rates of the shared ARGs suggest two transmission patterns among pigs, the HEG and LEG: one pattern was highest in pigs, gradually decreasing in the HEG and LEG (e.g. floR and cmlA1); the other pattern was increasing from pigs to the HEG but then decreasing in the LEG (e.g. mcr-1.1). Carriage rates of the HEG were higher than in the LEG in both patterns, implicating the HEG as a crucial medium in transmitting ARB and ARGs between food-producing animals and humans. Moreover, frequent inter/intragroup transmission via strains, plasmids and/or mobile elements was evident. Carriage of mcr-1.1 on human-gut-prevalent plasmids possibly promoted its enrichment in the HEG. CONCLUSIONS: The HEG is a crucial factor in transmitting ARB and ARGs between food-producing animals and humans. Rational measures to contain the risks of occupational exposure are urgently needed to keep dissemination of antibiotic resistance in check and safeguard public health.

Synthetic artificial intelligence using generative adversarial network for retinal imaging in detection of age-related macular degeneration.

Introduction: Age-related macular degeneration (AMD) is one of the leading causes of vision impairment globally and early detection is crucial to prevent vision loss. However, the screening of AMD is resource dependent and demands experienced healthcare providers. Recently, deep learning (DL) systems have shown the potential for effective detection of various eye diseases from retinal fundus images, but the development of such robust systems requires a large amount of datasets, which could be limited by prevalence of the disease and privacy of patient. As in the case of AMD, the advanced phenotype is often scarce for conducting DL analysis, which may be tackled via generating synthetic images using Generative Adversarial Networks (GANs). This study aims to develop GAN-synthesized fundus photos with AMD lesions, and to assess the realness of these images with an objective scale. Methods: To build our GAN models, a total of 125,012 fundus photos were used from a real-world non-AMD phenotypical dataset. StyleGAN2 and human-in-the-loop (HITL) method were then applied to synthesize fundus images with AMD features. To objectively assess the quality of the synthesized images, we proposed a novel realness scale based on the frequency of the broken vessels observed in the fundus photos. Four residents conducted two rounds of gradings on 300 images to distinguish real from synthetic images, based on their subjective impression and the objective scale respectively. Results and discussion: The introduction of HITL training increased the percentage of synthetic images with AMD lesions, despite the limited number of AMD images in the initial training dataset. Qualitatively, the synthesized images have been proven to be robust in that our residents had limited ability to distinguish real from synthetic ones, as evidenced by an overall accuracy of 0.66 (95% CI: 0.61-0.66) and Cohen's kappa of 0.320. For the non-referable AMD classes (no or early AMD), the accuracy was only 0.51. With the objective scale, the overall accuracy improved to 0.72. In conclusion, GAN models built with HITL training are capable of producing realistic-looking fundus images that could fool human experts, while our objective realness scale based on broken vessels can help identifying the synthetic fundus photos.

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study.

Purpose: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery. Chatbots could fill a pivotal role in the dissemination and easy accessibility of accurate information in a pandemic. In this study, we developed a multi-lingual NLP-based AI chatbot, DR-COVID, which responds accurately to open-ended, COVID-19 related questions. This was used to facilitate pandemic education and healthcare delivery. Methods: First, we developed DR-COVID with an ensemble NLP model on the Telegram platform (https://t.me/drcovid_nlp_chatbot). Second, we evaluated various performance metrics. Third, we evaluated multi-lingual text-to-text translation to Chinese, Malay, Tamil, Filipino, Thai, Japanese, French, Spanish, and Portuguese. We utilized 2,728 training questions and 821 test questions in English. Primary outcome measurements were (A) overall and top 3 accuracies; (B) Area Under the Curve (AUC), precision, recall, and F1 score. Overall accuracy referred to a correct response for the top answer, whereas top 3 accuracy referred to an appropriate response for any one answer amongst the top 3 answers. AUC and its relevant matrices were obtained from the Receiver Operation Characteristics (ROC) curve. Secondary outcomes were (A) multi-lingual accuracy; (B) comparison to enterprise-grade chatbot systems. The sharing of training and testing datasets on an open-source platform will also contribute to existing data. Results: Our NLP model, utilizing the ensemble architecture, achieved overall and top 3 accuracies of 0.838 [95% confidence interval (CI): 0.826-0.851] and 0.922 [95% CI: 0.913-0.932] respectively. For overall and top 3 results, AUC scores of 0.917 [95% CI: 0.911-0.925] and 0.960 [95% CI: 0.955-0.964] were achieved respectively. We achieved multi-linguicism with nine non-English languages, with Portuguese performing the best overall at 0.900. Lastly, DR-COVID generated answers more accurately and quickly than other chatbots, within 1.12-2.15 s across three devices tested. Conclusion: DR-COVID is a clinically effective NLP-based conversational AI chatbot, and a promising solution for healthcare delivery in the pandemic era.

Emergence of blaIMI-2- and blaIMI-16-Producing Enterobacter asburiae in the Aquaculture Environment of Jiangsu, China.

Carbapenem-resistant Enterobacteriaceae strains have emerged as a serious threat to global public health. In recent years, blaIMI, a carbapenemase gene that drew less attention before, has been increasingly detected in both clinical and environmental settings. However, the environmental distribution and transmission of blaIMI, especially in aquaculture, require systematic investigation. In this study, the blaIMI gene was detected in fish (n = 1), sewage (n = 1), river water (n = 1), and aquaculture pond water samples (n = 17) collected from Jiangsu, China, demonstrating a relatively high sample-positive ratio of 12.4% (20/161). Thirteen blaIMI-2- or blaIMI-16-carrying Enterobacter asburiae strains were isolated from blaIMI-positive samples of aquatic products and aquaculture ponds. We also identified a novel transposon (Tn7441) carrying blaIMI-16 and a conserved region containing several truncated insertion sequence (IS) elements harboring blaIMI-2, all of which may play important roles in blaIMI mobilization. The occurrence of blaIMI-carrying Enterobacter asburiae in aquaculture-related water samples and fish samples highlights the risk of transmission of blaIMI-carrying strains through the food chain and the need for effective measures to prevent further dissemination. IMPORTANCE IMI carbapenemases have been detected in clinical isolates of many bacterial species with systemic infection and cause a further burden on clinical treatment in China, but their source and distribution are still unclear. The study systematically investigated the distribution and transmission of the blaIMI gene in aquaculture-related water bodies and aquatic products in Jiangsu Province, China, which is famous for its rich water resources and developed aquaculture industry. The relatively high prevalence of blaIMI in aquaculture samples and the identification of novel mobile elements harboring blaIMI enhance our knowledge of blaIMI gene distribution and highlight the public health risk and urgency of surveillance of aquaculture water systems in China.

Caveolin-1 in vascular health and glaucoma: A critical vascular regulator and potential therapeutic target.

Caveolin-1 (Cav-1) is an integral scaffolding membrane protein found in most cell types. Cav-1 has been found to contribute significantly to ocular function, with mutations of Cav-1 being associated with a genetic risk of glaucoma development. Raised intraocular pressure (IOP) is a major modifiable risk factor for glaucoma. Cav-1 may be involved in both IOP-dependent and independent mechanisms involving vascular dysregulation. Systemic vascular diseases including hypertension, diabetes and hyperlipidaemia, have been shown to be associated with glaucoma development. Cav-1 is closely interlinked with endothelial nitric oxide synthase pathways that mediate vascular function and prevent cardiovascular diseases. Endothelial nitric oxide synthase and endothelin-1 are key vasoactive molecules expressed in retinal blood vessels that function to autoregulate ocular blood flow (OBF). Disruptions in the homeostasis of OBF have led to a growing concept of impaired neurovascular coupling in glaucoma. The imbalance between perfusion and neuronal stimulation arising from Cav-1 depletion may result in relative ischemia of the optic nerve head and glaucomatous injury. OBF is also governed by circadian variation in IOP and systemic blood pressure (BP). Cav-1 has been shown to influence central BP variability and other circadian rhythms such as the diurnal phagolysosomal digestion of photoreceptor fragments and toxic substrates to maintain ocular health. Overall, the vast implications of Cav-1 on various ocular mechanisms leading to glaucoma suggest a potential for new therapeutics to enhance Cav-1 expression, which has seen success in other neurodegenerative diseases.

Design, synthesis and structure-activity relationship of N-phenyl aromatic amide derivatives as novel xanthine oxidase inhibitors.

Our previous studies suggested that N-phenyl aromatic amides are a class of promising xanthine oxidase (XO) inhibitor chemotypes. In this effort, several series of N-phenyl aromatic amide derivatives (4a-h, 5-9, 12i-w, 13n, 13o, 13r, 13s, 13t and 13u) were designed and synthesized to carry out an extensive structure-activity relationship (SAR). The investigation provided some valuable SAR information and identified N-(3-(1H-imidazol-1-yl)-4-((2-methylbenzyl)oxy)phenyl)-1H-imidazole-4-carboxamide (12r, IC50 = 0.028 µM) as the most potent XO inhibitor with close in vitro potency to that of topiroxostat (IC50 = 0.017 µM). Molecular docking and molecular dynamics simulation rationalized the binding affinity through a series of strong interactions with the residues Glu1261, Asn768, Thr1010, Arg880, Glu802, etc. In vivo hypouricemic studies also suggested that the uric acid lowering effect of compound 12r was improved compared with the lead g25 (30.61 % vs 22.4 % reduction in uric acid levels at 1 h; 25.91 % vs 21.7 % reduction in AUC of uric acid) . Pharmacokinetic studies revealed that compound 12r presented a short t1/2 of 0.25 h after oral administration. In addition, 12r has non-cytotoxicity against normal cell HK-2. This work may provide some insights for further development of novel amide-based XO inhibitors.

Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning.

Efficient exploration remains a challenging problem in reinforcement learning, especially for tasks where extrinsic rewards from environments are sparse or even totally disregarded. Significant advances based on intrinsic motivation show promising results in simple environments but often get stuck in environments with multimodal and stochastic dynamics. In this work, we propose a variational dynamic model based on the conditional variational inference to model the multimodality and stochasticity. We consider the environmental state-action transition as a conditional generative process by generating the next-state prediction under the condition of the current state, action, and latent variable, which provides a better understanding of the dynamics and leads to a better performance in exploration. We derive an upper bound of the negative log likelihood of the environmental transition and use such an upper bound as the intrinsic reward for exploration, which allows the agent to learn skills by self-supervised exploration without observing extrinsic rewards. We evaluate the proposed method on several image-based simulation tasks and a real robotic manipulating task. Our method outperforms several state-of-the-art environment model-based exploration approaches.

Addressing Hindsight Bias in Multigoal Reinforcement Learning.

Multigoal reinforcement learning (RL) extends the typical RL with goal-conditional value functions and policies. One efficient multigoal RL algorithm is the hindsight experience replay (HER). By treating a hindsight goal from failed experiences as the original goal, HER enables the agent to receive rewards frequently. However, a key assumption of HER is that the hindsight goals do not change the likelihood of the sampled transitions and trajectories used in training, which is not the fact according to our analysis. More specifically, we show that using hindsight goals changes such a likelihood and results in a biased learning objective for multigoal RL. We analyze the hindsight bias due to this use of hindsight goals and propose the bias-corrected HER (BHER), an efficient algorithm that corrects the hindsight bias in training. We further show that BHER outperforms several state-of-the-art multigoal RL approaches in challenging robotics tasks.

(E)-2-styrylanthracene-9,10-dione derivatives as novel fluorescent probes: synthesis, photophysical properties and application in mitochondria imaging.

Our previous work firstly reported that (E)-2-styrylanthracene-9,10-dione is a novel fluorescent core (EK01) with the ability of specific mitochondria imaging. In this effort, we mainly focused our attention on the structure-photophysical property relationship and application in cells imaging of this new fluorescent chemotype. A series of the structural derivatives (TZ series) were designed and synthesized by introducing some substituents onto the 2-styryl moiety. The structure-photophysical property relationship analysis suggested that TZ03 is an excellent fluorescent molecular building block with the property of fluorescent "turn-on" effect after the modification of acylation, and TZ07 is an excellent fluorescent dye with a series of advantages such as high fluorescence intensity (Fmax = 4049.0 in CH2Cl2, 25.80 µM), moderate molar extinction coefficients (3.77 × 103-5.93 × 103 mol-1∙L∙cm-1), strong fluorescence quantum yield (Φmax = 0.739 in CH2Cl2), large Stokes shift (99.0 nm-161.8 nm) and well biological tolerance. As a classical D-π-A structure, the ICT characteristic of TZ07 was analyzed through spectroscopy verification and DFT calculations. Furthermore, optimized compound TZ07 was successfully applied in the living cells imaging with the excellent selectivity to mitochondria in a green fluorescent form. It was also suggested that the mechanism of TZ07 targeting mitochondria is independent of mitochondrial membrane potential, but probably related to the mitochondrial complex I. These findings may provide some insights into the development of novel mitochondria-targeted fluorescent probes.

Induction of immunogenic cell death by novel platinum-based anticancer agents.

Traditional platinum-based anticancer drugs, led by cisplatin, play an important role in chemotherapy. However, the development of platinum compounds is limited due to serious toxicity and side effects. In recent years, studies have showed that immunogenic cell death (ICD) may be one of the potential action mechanisms of classical platinum drugs, such as oxaliplatin. This strategy combining chemotherapy and immunotherapy can effectively utilize the body's immune system to help platinum compounds to fight against tumors, and the dose can be appropriately reduced to limit toxic side effects. The induction of ICD by platinum compounds has become a research hotspot and one of the future development directions of metal drugs. Here, the progress of platinum compounds were collected and comprehensively summarized, their capacity of ICD induction and mechanism of action are exposed, providing reference for the design and synthesis of new anticancer platinum ICD inducers.

Monotonic Quantile Network for Worst-Case Offline Reinforcement Learning.

A key challenge in offline reinforcement learning (RL) is how to ensure the learned offline policy is safe, especially in safety-critical domains. In this article, we focus on learning a distributional value function in offline RL and optimizing a worst-case criterion of returns. However, optimizing a distributional value function in offline RL can be hard, since the crossing quantile issue is serious, and the distribution shift problem needs to be addressed. To this end, we propose monotonic quantile network (MQN) with conservative quantile regression (CQR) for risk-averse policy learning. First, we propose an MQN to learn the distribution over returns with non-crossing guarantees of the quantiles. Then, we perform CQR by penalizing the quantile estimation for out-of-distribution (OOD) actions to address the distribution shift in offline RL. Finally, we learn a worst-case policy by optimizing the conditional value-at-risk (CVaR) of the distributional value function. Furthermore, we provide theoretical analysis of the fixed-point convergence in our method. We conduct experiments in both risk-neutral and risk-sensitive offline settings, and the results show that our method obtains safe and conservative behaviors in robotic locomotion tasks.

A possible covalent xanthine oxidase inhibitor TS10: Inhibition mechanism, metabolites identification and PDPK assessment.

Xanthine oxidase (XO) inhibitors are widely used in the control of serum uric acid levels in the clinical management of gout. Our continuous efforts in searching novel amide-based XO inhibitors culminated in the identification of N-(4-((3-cyanobenzyl)oxy)-3-(1H-tetrazol-1-yl)phenyl)isonicotinamide (TS10), which exhibited comparable in vitro inhibition to that of topiroxostat (TS10, IC50 = 0.031 µM; topiroxostat, IC50 = 0.020 µM). According to the molecular modeling, we speculated that, as well as topiroxostat, TS10 would be biotransformed by XO to yield TS10-2-OH. In this work, TS10-2-OH was successfully identified in XO targeted metabolism study, demonstrated that TS10 underwent a covalent binding with XO via a TS10-O-Mo intermediate after anchoring in the XO molybdenum cofactor pocket. Furthermore, TS10-2-OH is a weak active metabolite, and its potency was explained by the molecular docking. In metabolites identification, TS10 could be oxidized by CYP2C9, CYP3A4 and CYP3A5 to generate two mono-hydroxylated metabolites (not TS10-2-OH); and could occur degradation in plasma to mainly generate a hydrolytic metabolite (TS10-hydrolysate). In pharmacokinetic assessment, the low oral system exposure was observed (Cmax = 14.73 ± 2.66 ng/mL and AUClast = 9.17 ± 1.42 h⋅ng/mL), which could be explained by the poor oral absorption property found in excretion studies. Nonetheless, in pharmacodynamic evaluation, TS10 exhibited significant uric acid-lowering effect after oral administration in a dose-dependent manner. Briefly, in addition to allopurinol and topiroxostat, TS10 is possibly another explicitly mechanism-based XO inhibitor with powerful covalent inhibition.

Design, synthesis and biological evaluation of N-(4-alkoxy-3-(1H-tetrazol-1-yl)phenyl) heterocyclic aromatic amide derivatives as xanthine oxidase inhibitors.

Xanthine oxidase (XO) is a flavoprotein that exists in various organisms and can catalyze the uric acid formation in the human body. Based on the amide framework of N-(4-((3-cyanobenzyl)oxy)-3-(1H-tetrazol-1-yl)phenyl)isonicotinamide (compound 1) reported in our previous work, a series of N-(4-alkoxy-3-(1H-tetrazol-1-yl)phenyl) heterocyclic aromatic amide derivatives were designed, synthesized and evaluated as novel amide-based XO inhibitors. Structure-activity relationship campaign identified the most promising compound g25 (IC50 = 0.022 µM), which possesses a special 1H-imidazole-5-carboxamide scaffold and presented comparable XO inhibitory potency to topiroxostat (IC50 = 0.017 µM). Enzyme kinetic studies revealed that compound g25 acted as a mixed-type XO inhibitor. Molecular docking and molecular dynamics indicated that imidazole NH of g25 formed two stable hydrogen bonds with Glu1261 residue of XO that provided a vital contribution for the binding affinity. In addition, in vivo activity evaluation demonstrated that compound g25 exhibited obviously hypouricemic effect on a potassium oxonate induced hyperuricemic rat model.