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Background Machado-Joseph disease is the most common autosomal dominant hereditary ataxia worldwide without effective treatment. Mesenchymal stem cells (MSCs) could slow the disease progression, but side effects limited their clinical application. Besides, MSC-derived exosomes exerted similar efficacy and have many advantages over MSCs. The aim of this study was to examine the efficacy of MSC-derived exosomes in YACMJD84.2 mice. Methods Rotarod performance was evaluated every 2 weeks after a presymptomatic administration of intravenous MSC-derived exosomes twice in YACMJD84.2 mice. Loss of Purkinje cells, relative expression level of Bcl-2/Bax, cerebellar myelin loss, and neuroinflammation were assessed 8 weeks following treatment. Results MSC-derived exosomes were isolated and purified through anion exchange chromatography. Better coordination in rotarod performance was maintained for 6 weeks in YACMJD84.2 mice with exosomal treatment, compared with those without exosomal treatment. Neuropathological changes including loss of Purkinje cells, cerebellar myelin loss, and neuroinflammation were also attenuated 8 weeks after exosomal treatment. The higher relative ratio of Bcl-2/Bax was consistent with the attenuation of loss of Purkinje cells. Conclusions MSC-derived exosomes could promote rotarod performance and attenuate neuropathology, including loss of Purkinje cells, cerebellar myelin loss, and neuroinflammation. Therefore, MSC-derived exosomes have a great potential in the treatment of Machado-Joseph disease.

Metamaterial systems have opened new, unexpected, and exciting paths for the design of acoustic devices that only few years ago were considered completely out of reach. However, the development of an efficient design methodology still remains challenging due to highly intensive search in the design space required by the conventional optimization-based approaches. To address this issue, this study develops two machine learning (ML)-based approaches for the design of one-dimensional periodic and non-periodic metamaterial systems. For periodic metamaterials, a reinforcement learning (RL)-based approach is proposed to design a metamaterial that can achieve user-defined frequency band gaps. This RL-based approach surpasses conventional optimization-based methods in the reduction of computation cost when a near-optimal solution is acceptable. Leveraging the capability of exploration in RL, the proposed approach does not require any training datasets generation and therefore can be deployed for online metamaterial design. For non-periodic metamaterials, a neural network (NN)-based approach capable of learning the behavior of individual material units is presented. By assembling the NN representation of individual material units, a surrogate model of the whole metamaterial is employed to determine the properties of the resulting assembly. Interestingly, the proposed approach is capable of modeling different metamaterial assemblies satisfying user-defined properties while requiring only a one-time network training procedure. Also, the NN-based approach does not need a pre-defined number of material unit cells, and it works when the physical model of the unit cell is not well understood, or the situation where only the sensor measurements of the unit cell are available. The robustness of the proposed two approaches is validated through numerical simulations and design examples.

Statins play an important role in the treatment of diabetic nephropathy. Increasing attention has been given to the relationship between statins and insulin resistance, but many randomized controlled trials confirm that the therapeutic effects of statins on diabetic nephropathy are more beneficial than harmful. However, further confirmation of whether the beneficial effects of chronic statin administration on diabetic nephropathy outweigh the detrimental effects is urgently needed. Here, we find that long-term statin administration may increase insulin resistance, interfere with lipid metabolism, leads to inflammation and fibrosis, and ultimately fuel diabetic nephropathy progression in diabetic mice. Mechanistically, activation of insulin-regulated phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin signaling pathway leads to increased fatty acid synthesis. Furthermore, statins administration increases lipid uptake and inhibits fatty acid oxidation, leading to lipid deposition. Here we show that long-term statins administration exacerbates diabetic nephropathy via ectopic fat deposition in diabetic mice. Huang et al. investigated the effects of long-term statins administration in a mouse model for diabetes and found that it can worsen insulin resistance, renal inflammation and fibrosis. Statins increased renal lipid uptake and inhibited fatty acid oxidation, contributing to diabetic nephropathy.

Background:Evidence from both clinical and experimental research indicates that the immune-brain interaction plays a pivotal role in the pathophysiology of depression. A multi-protein complex of the innate immune system, the NLRP3 inflammasome regulates cleavage and secretion of proinflammatory cytokine interleukin-1β. The inflammasome detects various pathogen-associated molecule patterns and damage-associated molecule patterns, which then leads to a series of immune-inflammatory reactions.Methods:To explore the role of inflammasome activation in the underlying biological mechanisms of depression, we established a mouse model of depression with unpredictable chronic mild stress.Results:Mice subjected to chronic mild stress for 4 weeks had significantly higher serum corticosterone levels, serum interleukin-1β levels, and hippocampal active interleukin-1β protein levels. They also displayed depressive-like symptoms, including decreased sucrose preference and increased immobility time. Moreover, the hippocampi of chronic mild stress-exposed mice had significantly higher activity of caspase-1, which accompanied by higher protein levels of NLRP3 and the apoptotic speck-containing protein with a card. Pretreatment with the NLRP3 inflammasome inhibitor VX-765 decreased serum and hippocampal levels of interleukin-1β protein and significantly moderated the depressive-like behaviors induced by chronic mild stress.Conclusions:These data suggest the NLRP3 inflammasome mediates stress-induced depression via immune activation. Future procedures targeting the NLRP3 inflammasome may have promising effects in the prevention and treatment of depression.

Drug discovery campaigns against COVID-19 are beginning to target the SARS-CoV-2 RNA genome. The highly conserved frameshift stimulation element (FSE), required for balanced expression of viral proteins, is a particularly attractive SARS-CoV-2 RNA target. Here we present a 6.9 Å resolution cryo-EM structure of the FSE (88 nucleotides, ~28 kDa), validated through an RNA nanostructure tagging method. The tertiary structure presents a topologically complex fold in which the 5′ end is threaded through a ring formed inside a three-stem pseudoknot. Guided by this structure, we develop antisense oligonucleotides that impair FSE function in frameshifting assays and knock down SARS-CoV-2 virus replication in A549-ACE2 cells at 100 nM concentration. The frameshift stimulation element (FSE) of coronaviruses is an RNA structure that is required for balanced expression of viral proteins and is thus a promising drug target. A structure of the SARS-CoV-2 FSE serves as a guide for the development of antisense oligonucleotides that impair virus replication.

Atherosclerosis is a major cardiovascular disease that causes ischemia of the heart, brain, or extremities, and can lead to infarction. The hypolipidemic agent atorvastatin calcium (Ato) alleviates atherosclerosis by reducing plasma lipid and inflammatory factors. However, the low bioavailability of Ato limits its widespread use and clinical effectiveness. Curcumin (Cur), a natural polyphenol with antioxidation and anti-inflammation bioactivities, has potential anti-atherosclerosis activity and may reduce Ato-induced cytotoxicity. Liposomes modified using a targeting ligand (E-selectin-binding peptide) were prepared to co-deliver Ato and Cur to dysfunctional endothelial cells (ECs) overexpressing E-selectin. Molecules involved in the inhibition of adhesion (E-selectin and intercellular cell adhesion molecule-1 [ICAM-1]) and inflammation (IL-6 and monocyte chemotactic protein 1 [MCP-1]) in human aortic endothelial cells were evaluated using real-time quantitative PCR, flow cytometry, and immunofluorescence staining. The antiatherosclerosis effects of liposomes co-loaded with Ato and Cur in vivo were evaluated using ApoE knockout (ApoE ) mice. Targeted liposomes delivered Ato and Cur to dysfunctional ECs, resulting in synergistic suppression of adhesion molecules (E-selectin and ICAM-1) and plasma lipid levels. Moreover, this treatment reduced foam cell formation and the secretion of inflammatory factors (IL-6 and MCP-1) by blocking monocyte migration into the intima. In addition, Cur successfully reduced Ato-inducible cytotoxicity. Both in vitro and in vivo experiments demonstrated that cell-targeted co-delivery of Ato and Cur to dysfunctional ECs drastically reduces atherosclerotic lesions with fewer side effects than either Ato or Cur alone.

Diabetic cardiomyopathy is a primary myocardial injury induced by diabetes with complex pathogenesis. In this study, we identify disordered cardiac retinol metabolism in type 2 diabetic male mice and patients characterized by retinol overload, all-trans retinoic acid deficiency. By supplementing type 2 diabetic male mice with retinol or all-trans retinoic acid, we demonstrate that both cardiac retinol overload and all-trans retinoic acid deficiency promote diabetic cardiomyopathy. Mechanistically, by constructing cardiomyocyte-specific conditional retinol dehydrogenase 10-knockout male mice and overexpressing retinol dehydrogenase 10 in male type 2 diabetic mice via adeno-associated virus, we verify that the reduction in cardiac retinol dehydrogenase 10 is the initiating factor for cardiac retinol metabolism disorder and results in diabetic cardiomyopathy through lipotoxicity and ferroptosis. Therefore, we suggest that the reduction of cardiac retinol dehydrogenase 10 and its mediated disorder of cardiac retinol metabolism is a new mechanism underlying diabetic cardiomyopathy. The current challenges for diabetic cardiomyopathy (DCM) are unclear mechanisms and no effective therapy in clinics. Here, the authors found that the decrease of cardiac retinol dehydrogenase 10 in type 2 diabetes leads to retinol metabolism disorder, cardiac lipid toxicity and cardiomyopathy development, suggesting that correcting the imbalance of cardiac retinol metabolism may be an effective strategy for the treatment of DCM.

AimThe impact of pelvis on the development of anastomotic leak (AL) in rectal cancer (RC) patients who underwent anterior resection (AR) remains unclear. The aim of this study was to evaluate the impact of pelvic dimensions on the risk of AL.MethodsA total of 1058 RC patients undergoing AR from January 2013 to January 2016 were enrolled. Pelvimetric parameters were obtained using abdominopelvic computed tomography scans.ResultsUnivariate analyses showed that pelvic inlet, pelvic outlet, interspinous distance, and intertuberous distance were significantly associated with the risk for AL (P < 0.05). Multivariate analysis confirmed that pelvic inlet and intertuberous distance were independent risk factors for AL (P < 0.05). Significant factors from multivariate analysis were assembled into the nomogram A (without pelvic dimensions) and nomogram B (with pelvic dimensions). The area under curve (AUC) of nomogram B was 0.72 (95% CI 0.67–0.77), which was better than the AUC of nomogram A (0.69, [95% CI 0.65–0.74]), but didn’t reach a statistical significance (P = 0.199). Decision curve supported that nomogram B was better than nomogram A.ConclusionPelvic dimensions, specifically pelvic inlet and intertuberous distance, seemed to be independent predictors for postoperative AL in RC patients. Pelvic inlet and intertuberous distance incorporated with preoperative radiotherapy, preoperative albumin, conversion, and tumor diameter in the nomogram might provide a clinical tool for predicting AL.

Boundary-layer wind associated with extratropical cyclones (ETCs) is an essential element for posing serious threats to the urban centers of eastern North America. Using a similar methodology for tropical cyclone (TC) wind risk (i.e., hurricane tracking approach), the ETC wind risk can be accordingly simulated. However, accurate and efficient assessment of the wind field inside the ETC is currently not available. To this end, a knowledge-enhanced deep learning (KEDL) is developed in this study to estimate the ETC boundary-layer winds over eastern North America. Both physics-based equations and semi-empirical formulas are integrated as part of the system loss function to regularize the neural network. More specifically, the scale-analysis-based reduced-order Navier–Stokes equations that govern the ETC wind field and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) ERA-interim data-based two-dimensional (2D) parametric formula (with respect to radial and azimuthal coordinates) that prescribes an asymmetric ETC pressure field are respectively employed as rationalism-based and empiricism-based knowledge to enhance the deep neural network. The developed KEDL, using the standard storm parameters (i.e., spatial coordinates, central pressure difference, translational speed, approach angle, latitude of ETC center, and surface roughness) as the network inputs, can provide the three-dimensional (3D) boundary-layer wind field of an arbitrary ETC with high computational efficiency and accuracy. Finally, the KEDL-based wind model is coupled with a large ETC synthetic track database (SynthETC), where 6-hourly ETC center location and pressure deficit are included to effectively assess the wind risk along the US northeast coast in terms of annual exceedance probability.

Background Studies have shown that the absolute lymphocyte count (ALC) and the neutrophil-to-lymphocyte ratio (NLR) are related to the outcomes in patients with breast cancer receiving specific chemotherapies. However, the reports have focussed on the initial blood test and there is a lack of evidence or data to support that dynamic changes of ALC or NLR are associated with the patients’ survival outcomes. Methods We retrospectively reviewed electronic medical records from patients with breast cancer treated with eribulin from 2015 to 2019 at our institution. Blood test data were available prior to starting eribulin (baseline), and at 1, 3 and 6 months after initiating eribulin. We classified the patients into ALC and NLR high and low groups using the following cut-offs: 1000/µl for ALC and 3 for NLR. We defined ALC and NLR trends as increasing or decreasing compared with the initial data. We assessed the associations between the ALC and NLR with progression-free survival and overall survival. Results There were 136 patients with breast cancer treated with eribulin. Of these patients, 60 had complete blood tests and follow-up data. Neither a high ALC nor a low baseline NLR was associated with the survival outcome. One month after initiating eribulin treatment, a high ALC and a low NLR were significantly associated with longer progression-free survival ( p = 0.044 for each). Three months after initiating eribulin, a high ALC was significantly associated with better overall survival ( p = 0.006). A high NLR at 3 or 6 months after initiating eribulin was associated with worse overall survival ( p = 0.017 and p = 0.001, respectively). The ALC and NLR trends across times were not associated with survivals. Conclusion We showed that 1, 3 and 6 months after initiating eribulin, a high ALC and a low NLR may be related to the patients’ survival outcomes. The ALC and NLR trends were not associated with survival. Accordingly, we believe patients who maintain a high ALC and a low NLR may have better clinical outcomes after initiating eribulin.