IL-33-ST2 Axis in Liver Disease: Progression and Challenge

The new member of the IL-1 family, interleukin-33 (IL-33), participates in the progression of a variety of diseases through binding with its receptor ST2. Recently, much clinical evidence and experimental data have indicated that IL-33 is associated with various liver diseases. This review primarily addresses the relationship between IL-33 and several hepatic diseases. IL-33 can alleviate high-fat diet- (HFD-) induced hepatic steatosis and insulin resistance, and IL-33 acts as an alarmin, which quickly triggers the immune system to respond to virus invasion and toxic damage to the liver. However, when liver injury is chronic, IL-33 promotes Th2 reactions and hepatic stellate cell (HSC) activity, facilitating progression to liver fibrosis. The complicated functions of IL-33 should be considered before its clinical application

IL-23 inhibitor enhances the effects of PTEN DNA-loaded lipid nanoparticles for metastatic CRPC therapy

Introduction: Metastatic castration-resistant prostate cancer (mCRPC) patients face challenges due to limited treatment options. About 50% of patients with mCRPC have a functional loss of phosphatase and tensin homology deleted on chromosome 10 (PTEN), leading to tumor progression, metastasis, and immune suppression. Moreover, elevated IL-23 produced by myeloid-derived suppressor cells (MDSCs) is found in CRPC patients, driving tumor progression. Therefore, a combination strategy based on PTEN restoration and IL-23 inhibition may block CRPC progression and metastasis.Methods: The antitumor effect of restoring PTEN expression combined with the IL-23 inhibitor Apilimod was studied in a mouse model of bone metastasis CRPC and mouse prostate cancer RM-1 cells. To verify the targeting ability of PTEN DNA coated with lipid nanoparticles (LNP@PTEN) in vitro and in vivo. In addition, RT-qPCR and flow cytometry were used to investigate the related mechanisms of the antitumor effect of LNP@PTEN combined with Apilimod.Results: LNPs exhibited significant tumor-targeting and tumor accumulation capabilities both in vitro and in vivo, enhancing PTEN expression and therapeutic efficacy. Additionally, the combination of LNP@PTEN with the IL-23 inhibitor Apilimod demonstrated enhanced inhibition of tumor growth, invasion, and metastasis (particularly secondary organ metastasis) compared to other groups, and extended the survival of mice to 41 days, providing a degree of bone protection. These effects may be attributed to the PTEN function restoration combined with IL-23 inhibition, which help reverse immune suppression in the tumor microenvironment by reducing MDSCs recruitment and increasing the CD8+/CD4+ T cell ratio.Discussion: In summary, these findings highlight the potential of LNPs for delivering gene therapeutic agents. And the combination of LNP@PTEN with Apilimod could achieve anti-tumor effects and improve tumor microenvironment. This combinational strategy opens new avenues for the treatment of mCRPC

MiR26a reverses enzalutamide resistance in a bone-tumor targeted system with an enhanced effect on bone metastatic CRPC

Resistance to androgen receptor (AR) inhibitors, including enzalutamide (Enz), as well as bone metastasis, are major challenges for castration-resistant prostate cancer (CRPC) treatment. In this study, we identified that miR26a can restore Enz sensitivity and inhibit bone metastatic CRPC. To achieve the highest combination effect of miR26a and Enz, we developed a cancer-targeted nano-system (Bm@PT/Enz-miR26a) using bone marrow mesenchymal stem cell (BMSC) membrane and T140 peptide to co-deliver Enz and miR26a. The in vitro/in vivo results demonstrated that miR26a can reverse Enz resistance and synergistically shrink tumor growth, invasion, and metastasis (especially secondary metastasis) in both subcutaneous and bone metastatic CRPC mouse models. We also found that the EZH2/SFRP1/WNT5A axis may be involved in this role. These findings open new avenues for treating bone metastatic and Enz-resistant CRPC.Peer reviewe

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology

Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models

Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper we discuss the SW/HW co-designed solution for high-performance distributed training of large-scale DLRMs. We introduce a high-performance scalable software stack based on PyTorch and pair it with the new evolution of Zion platform, namely ZionEX. We demonstrate the capability to train very large DLRMs with up to 12 Trillion parameters and show that we can attain 40X speedup in terms of time to solution over previous systems. We achieve this by (i) designing the ZionEX platform with dedicated scale-out network, provisioned with high bandwidth, optimal topology and efficient transport (ii) implementing an optimized PyTorch-based training stack supporting both model and data parallelism (iii) developing sharding algorithms capable of hierarchical partitioning of the embedding tables along row, column dimensions and load balancing them across multiple workers; (iv) adding high-performance core operators while retaining flexibility to support optimizers with fully deterministic updates (v) leveraging reduced precision communications, multi-level memory hierarchy (HBM+DDR+SSD) and pipelining. Furthermore, we develop and briefly comment on distributed data ingestion and other supporting services that are required for the robust and efficient end-to-end training in production environments

Clinical characteristics and outcomes in patients with traumatic brain injury in China: a prospective, multicentre, longitudinal, observational study

Background Large-scale studies are required to better characterise traumatic brain injury (TBI) and to identify the most effective treatment approaches for TBI. However, evidence is scarce and mostly originates from high-income countries. We aimed to describe the existing care for patients with TBI and the outcomes in China. Methods The Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China registry is a prospective, multicentre, longitudinal, observational study done in 56 neurosurgical centres across China. We collected data of patients who were admitted to hospital with a clinical diagnosis of TBI and an indication for CT. Patients who were discharged directly from the emergency room were excluded. The primary endpoint was survival on discharge. Prognostic analyses were applied to identify predictors of mortality. Variations in mortality were compared between centres and provinces within China. Mortality was compared with expected mortality, estimated using the CRASH basic model. This study was registered with ClinicalTrials.gov, NCT02210221. Findings From Dec 22, 2014, to Aug 1, 2017, 13 627 patients with TBI from 56 centres were enrolled in the registry. Data from 13 138 patients from 52 hospitals in 22 provinces of China were analysed. Most patients were male (9782 [74%]), with a median age of 48 years (IQR 33–61). The median Glasgow Coma Scale (GCS) score was 13 (IQR 9–15), and the leading cause of injury was road-traffic incident (6548 [50%]). Overall, 637 (5%) patients died, including 552 (20%) patients with severe TBI. Age, GCS score, injury severity score, pupillary light reflex, CT findings (compressed basal cistern and midline shift ≥5 mm), presence of hypoxia, systemic hypotension, altitude higher than >500 m, and GDP per capita were significantly associated with survival in all patients with TBI. Variation in mortality existed between centres and regions. The expected 14-day mortality was 1116 (13%), but 544 (7%) deaths within 14 days were observed (observed to expected ratio 0·49 [95% CI 0·45–0·53]). Interpretation The results show differences in mortality between centres and regions across China, which indicates potential for identifying best practices through comparative effectiveness research. The risk factors identified in prognostic analyses might contribute to developing benchmarks for assessing quality of care. Funding None

Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research

No abstract available