Scaling-Free Cathodes: Enabling Electrochemical Extraction of High-Purity Nano-CaCO3 and -Mg(OH)2 in Seawater.

For electrochemical application in seawater or brine, continuous scaling on cathodes will form insulation layers, making it nearly impossible to run an electrochemical reaction continuously. Herein, we report our discovery that a cathode consisting of conical nanobundle arrays with hydrophobic surfaces exhibits a unique scaling-free function. The hydrophobic surfaces will be covered with microbubbles created by electrolytic water splitting, which limits scale crystals from standing only on nanotips of conical nanobundles, and the bursting of large bubbles formed by the accumulation of microbubbles will cause a violent disturbance, removing scale crystals automatically from nanotips. Benefiting from the scaling-free properties of the cathode, high-purity nano-CaCO3 (98.9%) and nano-Mg(OH)2 (99.5%) were extracted from seawater. This novel scaling-free cathode is expected to eliminate the inherent limitations of electrochemical technology and open up a new route to seawater mining.

Sodium chloride promotes macrophage pyroptosis and aggravates rheumatoid arthritis by activating SGK1 through GABA receptors Slc6a12.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovial inflammation and the production of autoantibodies. Previous studies have indicated an association between high-salt diets (HSD) and an increased risk of RA, yet the underlying mechanisms remain unclear. Macrophage pyroptosis, a pro-inflammatory form of cell death, plays a pivotal role in RA. In this study, we demonstrate that HSD exacerbates the severity of arthritis in collagen-induced arthritis (CIA) mice, correlating with macrophage infiltration and inflammatory lesions. Given the significant alterations observed in macrophages from CIA mice subjected to HSD, we specifically investigate the impact of HSD on macrophage responses in the inflammatory milieu of RA. In our in vitro experiments, pretreatment with NaCl enhances LPS-induced pyroptosis in RAW.264.7 and THP-1 cells through the p38 MAPK/NF-κB signaling pathway. Subsequent experiments reveal that Slc6a12 inhibitors and SGK1 silencing inhibit sodium-induced activation of macrophage pyroptosis and the p38 MAPK/NF-κB signaling pathway, whereas overexpression of the SGK1 gene counteracts the effect of sodium on macrophages. In conclusion, our findings verified that high salt intake promotes the progression of RA and provided a detailed elucidation of the activation of macrophage pyroptosis induced by sodium transportation through the Slc6a12 channel.

Preparation, pungency and bioactivity transduction of piperine from black pepper (Piper nigrum L.): A comprehensive review.

Piperine, derived from black pepper (Piper nigrum L.), is responsible for the pungent sensation. The diverse bioactivities of piperine underscores its promising potential as a functional food ingredient. This review presents a comprehensive overview of the research progress in extraction, synthesis, pungency transduction mechanism and bioactivities of piperine. Piperine can be extracted through various methods, such as traditional, modern, and innovative extraction techniques. Its synthesis mainly included both chemical and biosynthetic approaches. It exhibits a diverse range of bioactivities, including anticancer, anticonvulsant, antidepressant, anti-inflammatory, antioxidant, immunomodulatory, anti-obesity, neuroprotective, antidiabetic, hepatoprotective, and cardiovascular protective activities. Piperine can bind to TRPV1 receptor to elicit pungent sensation. Overall, the present review can provide a theoretical reference for advancing the potential application of piperine in the field of food science.

Emerging concern on air pollution and health: Trade-off between air pollution exposure and physical activity.

Air pollution is a major contributor to the global disease burden, especially affecting respiratory and cardiovascular health. However, physical activity is associated with improved lung function, a slower decline in lung function, and lower mortality. The public is more likely to be exposed to air pollution during outdoor physical activity. However, studies on how long-term and short-term exposure to air pollution interacts with physical activity yield inconsistent results, and the thresholds for air pollution and physical activity remain unclear. Thus, more studies are needed to provide sufficient evidence to guide the public to safely engage in outdoor physical activity when exposed to air pollution.

Analyzing entropy features in time-series data for pattern recognition in neurological conditions.

In the field of medical diagnosis and patient monitoring, effective pattern recognition in neurological time-series data is essential. Traditional methods predominantly based on statistical or probabilistic learning and inference often struggle with multivariate, multi-source, state-varying, and noisy data while also posing privacy risks due to excessive information collection and modeling. Furthermore, these methods often overlook critical statistical information, such as the distribution of data points and inherent uncertainties. To address these challenges, we introduce an information theory-based pipeline that leverages specialized features to identify patterns in neurological time-series data while minimizing privacy risks. We incorporate various entropy methods based on the characteristics of different scenarios and entropy. For stochastic state transition applications, we incorporate Shannon's entropy, entropy rates, entropy production, and the von Neumann entropy of Markov chains. When state modeling is impractical, we select and employ approximate entropy, increment entropy, dispersion entropy, phase entropy, and slope entropy. The pipeline's effectiveness and scalability are demonstrated through pattern analysis in a dementia care dataset and also an epileptic and a myocardial infarction dataset. The results indicate that our information theory-based pipeline can achieve average performance improvements across various models on the recall rate, F1 score, and accuracy by up to 13.08 percentage points, while enhancing inference efficiency by reducing the number of model parameters by an average of 3.10 times. Thus, our approach opens a promising avenue for improved, efficient, and critical statistical information-considered pattern recognition in medical time-series data.

ADMM-inspired image reconstruction for terahertz off-axis digital holography.

Image reconstruction in off-axis terahertz digital holography is complicated due to the harsh recording conditions and the non-convexity form of the problem. In this paper, we propose an inverse problem-based reconstruction technique that jointly reconstructs the object field and the amplitude of the reference field. Regularization in the wavelet domain promotes a sparse object solution. A single objective function combining the data-fidelity and regularization terms is optimized with a dedicated algorithm based on an alternating direction method of multipliers framework. Each iteration alternates between two consecutive optimizations using projections operating on each solution and one soft thresholding operator applying to the object solution. The method is preceded by a windowing process to alleviate artifacts due to the mismatch between camera frame truncation and periodic boundary conditions assumed to implement convolution operators. Experiments demonstrate the effectiveness of the proposed method, in particular, improvements of reconstruction quality, compared to two other methods.

Giant Tunability of Rashba Splitting at Cation-Exchanged Polar Oxide Interfaces by Selective Orbital Hybridization.

The 2D electron gas (2DEG) at oxide interfaces exhibits extraordinary properties, such as 2D superconductivity and ferromagnetism, coupled to strongly correlated electrons in narrow d-bands. In particular, 2DEGs in KTaO3 (KTO) with 5d t2g orbitals exhibit larger atomic spin-orbit coupling and crystal-facet-dependent superconductivity absent for 3d 2DEGs in SrTiO3 (STO). Herein, by tracing the interfacial chemistry, weak anti-localization magneto-transport behavior, and electronic structures of (001), (110), and (111) KTO 2DEGs, unambiguously cation exchange across KTO interfaces is discovered. Therefore, the origin of the 2DEGs at KTO-based interfaces is dramatically different from the electronic reconstruction observed at STO interfaces. More importantly, as the interface polarization grows with the higher order planes in the KTO case, the Rashba spin splitting becomes maximal for the superconducting (111) interfaces approximately twice that of the (001) interface. The larger Rashba spin splitting couples strongly to the asymmetric chiral texture of the orbital angular moment, and results mainly from the enhanced inter-orbital hopping of the t2g bands and more localized wave functions. This finding has profound implications for the search for topological superconductors, as well as the realization of efficient spin-charge interconversion for low-power spin-orbitronics based on (110) and (111) KTO interfaces.

Targeting fusion proteins of the interleukin family: A promising new strategy for the treatment of autoinflammatory diseases.

As a means of communication between immune cells and non-immune cells, Interleukins (ILs) has the main functions of stimulating the proliferation and activation of inflammatory immune cells such as dendritic cells and lymphocytes, promote the development of blood cells and so on. However, dysregulation of ILs expression is a major feature of autoinflammatory diseases. The drugs targeting ILs or IL-like biologics have played an important role in the clinical treatment of autoinflammatory diseases. Nevertheless, the widespread use of IL products may result in significant off-target adverse reactions. Thus, there is a clear need to develop next-generation ILs products in the biomedical field. Fusion proteins are proteins created through the joining of two or more genes that originally coded for separate proteins. Over the last 30 years, there has been increasing interest in the use of fusion protein technology for developing anti-inflammatory drugs. In comparison to single-target drugs, fusion proteins, as multiple targets drugs, have the ability to enhance the cytokine therapeutic index, resulting in improved efficacy over classical drugs. The strategy of preparing ILs or their receptors as fusion proteins is increasingly used in the treatment of autoimmune and chronic inflammation. This review focuses on the efficacy of several fusion protein drugs developed with ILs or their receptors in the treatment of autoinflammatory diseases, in order to illustrate the prospects of this new technology as an anti-inflammatory drug development protocol in the future.

Rural micro-credit model design and credit risk assessment via improved LSTM algorithm.

Rural microcredit plays an important role in promoting rural economic development and increasing farmers' income. However, traditional credit risk assessment models may have insufficient adaptability in rural areas. This study is based on the improved Long Short Term Memory (LSTM) algorithm using self organizing method, aiming to design an optimized evaluation model for rural microcredit risk. The improved LSTM algorithm can better capture the long-term dependence between the borrower's historical behavior and risk factors with its advantages in sequential data modeling. The experimental results show that the rural microcredit risk assessment model based on the self organizing LSTM algorithm has higher accuracy and stability compared to traditional models, and can effectively control credit default risk, providing more comprehensive risk management support for financial institutions. In addition, the model also has real-time monitoring and warning functions, which helps financial institutions adjust their decisions in a timely manner and reduce credit losses. The practical application of this study is expected to promote the stable development of rural economy and the advancement of financial technology. However, future work needs to further validate the practical application effectiveness and interpretability of the model, taking into account the special circumstances of different rural areas, in order to achieve sustainable application of the model in the rural microcredit market.

Low-dose ethanol consumption inhibits neutrophil extracellular traps formation to alleviate rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease. Ethanol consumption has been reported to reduce morbidity in RA patients, but the mechanism behind it remains unclear. Our results showed that Muribaculaceae was predominant in the gut microbiota of mice after ethanol treatment, and the levels of microbiota metabolite acetate were increased. Acetate reduced arthritis severity in collagen-induced arthritis (CIA) mice, which was associated with a decrease in the articular neutrophils and the myeloperoxidase-deoxyribonucleic acid complex in serum. Meanwhile, in vitro experiments confirmed that acetate affected neutrophil activity by acting on G-protein-coupled receptor 43, which reduced endoplasmic reticulum stress in neutrophils and inhibited neutrophil extracellular traps formation. Furthermore, exogenous acetate reversed CIA mice with exacerbated gut microbial disruption, further confirming that the effect of gut microbial metabolite acetate on neutrophils in vivo is crucial for the immune regulation. Our findings illuminate the metabolic and cellular mechanisms of the gut-joint axis in the regulation of autoimmune arthritis, and may offer alternative avenues to replicate or induce the joint-protective benefits of ethanol without associated detrimental effects.

Heterogeneous changes in mobility in response to the SARS-CoV-2 Omicron BA.2 outbreak in Shanghai.

The coronavirus disease 2019 (COVID-19) pandemic and the measures taken by authorities to control its spread have altered human behavior and mobility patterns in an unprecedented way. However, it remains unclear whether the population response to a COVID-19 outbreak varies within a city or among demographic groups. Here, we utilized passively recorded cellular signaling data at a spatial resolution of 1 km × 1 km for over 5 million users and epidemiological surveillance data collected during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 outbreak from February to June 2022 in Shanghai, China, to investigate the heterogeneous response of different segments of the population at the within-city level and examine its relationship with the actual risk of infection. Changes in behavior were spatially heterogenous within the city and population groups and associated with both the infection incidence and adopted interventions. We also found that males and individuals aged 30 to 59 y old traveled more frequently, traveled longer distances, and their communities were more connected; the same groups were also associated with the highest SARS-CoV-2 incidence. Our results highlight the heterogeneous behavioral change of the Shanghai population to the SARS-CoV-2 Omicron BA.2 outbreak and the effect of heterogenous behavior on the spread of COVID-19, both spatially and demographically. These findings could be instrumental for the design of targeted interventions for the control and mitigation of future outbreaks of COVID-19, and, more broadly, of respiratory pathogens.

Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis.

BACKGROUND: After the first COVID-19 wave caused by the ancestral lineage, the pandemic has been fueled from the continuous emergence of new SARS-CoV-2 variants. Understanding key time-to-event periods for each emerging variant of concern is critical as it can provide insights into the future trajectory of the virus and help inform outbreak preparedness and response planning. Here, we aim to examine how the incubation period, serial interval, and generation time have changed from the ancestral SARS-CoV-2 lineage to different variants of concern. METHODS: We conducted a systematic review and meta-analysis that synthesized the estimates of incubation period, serial interval, and generation time (both realized and intrinsic) for the ancestral lineage, Alpha, Beta, and Omicron variants of SARS-CoV-2. RESULTS: Our study included 280 records obtained from 147 household studies, contact tracing studies, or studies where epidemiological links were known. With each emerging variant, we found a progressive shortening of each of the analyzed key time-to-event periods, although we did not find statistically significant differences between the Omicron subvariants. We found that Omicron BA.1 had the shortest pooled estimates for the incubation period (3.49 days, 95% CI: 3.13-4.86 days), Omicron BA.5 for the serial interval (2.37 days, 95% CI: 1.71-3.04 days), and Omicron BA.1 for the realized generation time (2.99 days, 95% CI: 2.48-3.49 days). Only one estimate for the intrinsic generation time was available for Omicron subvariants: 6.84 days (95% CrI: 5.72-8.60 days) for Omicron BA.1. The ancestral lineage had the highest pooled estimates for each investigated key time-to-event period. We also observed shorter pooled estimates for the serial interval compared to the incubation period across the virus lineages. When pooling the estimates across different virus lineages, we found considerable heterogeneities (I2 > 80%; I2 refers to the percentage of total variation across studies that is due to heterogeneity rather than chance), possibly resulting from heterogeneities between the different study populations (e.g., deployed interventions, social behavior, demographic characteristics). CONCLUSIONS: Our study supports the importance of conducting contact tracing and epidemiological investigations to monitor changes in SARS-CoV-2 transmission patterns. Our findings highlight a progressive shortening of the incubation period, serial interval, and generation time, which can lead to epidemics that spread faster, with larger peak incidence, and harder to control. We also consistently found a shorter serial interval than incubation period, suggesting that a key feature of SARS-CoV-2 is the potential for pre-symptomatic transmission. These observations are instrumental to plan for future COVID-19 waves.

Denoising Method Based on Salient Region Recognition for the Spatiotemporal Event Stream.

Event cameras are the emerging bio-mimetic sensors with microsecond-level responsiveness in recent years, also known as dynamic vision sensors. Due to the inherent sensitivity of event camera hardware to light sources and interference from various external factors, various types of noises are inevitably present in the camera's output results. This noise can degrade the camera's perception of events and the performance of algorithms for processing event streams. Moreover, since the output of event cameras is in the form of address-event representation, efficient denoising methods for traditional frame images are no longer applicable in this case. Most existing denoising methods for event cameras target background activity noise and sometimes remove real events as noise. Furthermore, these methods are ineffective in handling noise generated by high-frequency flickering light sources and changes in diffused light reflection. To address these issues, we propose an event stream denoising method based on salient region recognition in this paper. This method can effectively remove conventional background activity noise as well as irregular noise caused by diffuse reflection and flickering light source changes without significantly losing real events. Additionally, we introduce an evaluation metric that can be used to assess the noise removal efficacy and the preservation of real events for various denoising methods.

Using energy expenditure to estimate the minute ventilation and inhaled load of air pollutants: a pilot survey in young Chinese adults.

Existing equations to estimate ventilation (VE) may not represent the Chinese population. The objective is to develop regression equations to predict the basal metabolic rate (BMR) for ventilation estimation. 80 participants underwent the incremental tests on a bicycle ergometer, wearing a fitted facial mask with an airflow sensor connected to the cardiopulmonary gas analyzer, where the energy expenditure, metabolic factors and VE were monitored simultaneously. Linear regression models were established between BMR and body weight, which were used to estimate energy expenditure and VE. Extrapolation of the regression model was evaluated by the five-fold cross-validation. And we also assessed the inhaled load of air pollutants in subgroups at the same exposure levels. Regression models for males and females were BMR (kJ/d) = 107.58 × weight (kg)-172.61 and BMR (kJ/d) = 105.61 × weight (kg)-26.94, respectively. The model showed good fitness between the measured and predicted VE. Differences between the measured and predicted VE of this model are smaller than that of other models. There were significant differences in inhaled load participants in the same exposure concentrations. The regression model showed that weight and BMR are highly correlated and can be used to estimate individual VE.

High-performance composite elastomers with abundant heterostructures for enhanced electromagnetic wave absorption with ultrabroad bandwidth.

Two-dimensional (2D) MXene has attracted vast attention in electromagnetic wave absorption (EWA), but there remains a contradiction between maintaining impedance matching and enhancing dielectric loss. Herein, the multi-scale architectures of ecoflex/2D MXene (Ti3C2Tx)@zero-dimensional CoNi sphere@one-dimensional carbon nanotube composite elastomers were successfully constructed by simple liquid-phase reduction and thermo-curing method. The binding between the hybrids as fillers and ecoflex as a matrix greatly enhanced the EWA capability of the obtained composite elastomer and improved its mechanical properties. Owing to its good impedance matching, abundant heterostructures, and synergistic electrical and magnetic losses, this elastomer exhibited an excellent minimum reflection loss of -67 dB at 9.46 GHz under a thickness of 2.98 mm. In addition, its ultrabroad effective absorption bandwidth reached 6.07 GHz. This achievement will pave the way for the exploitation of multi-dimensional heterostructures as high-performance electromagnetic absorbers with superior EWA ability.

Vibration Detection and Degraded Image Restoration of Space Camera Based on Correlation Imaging of Rolling-Shutter CMOS.

To mitigate the influence of satellite platform vibrations on space camera imaging quality, a novel approach is proposed to detect vibration parameters based on correlation imaging of rolling-shutter CMOS. In the meantime, a restoration method to address the image degradation of rolling-shutter CMOS caused by such vibrations is proposed. The vibration parameter detection method utilizes the time-sharing and row-by-row imaging principle of rolling-shutter CMOS to obtain relative offset by comparing two frames of correlation images from continuous imaging. Then, the space camera's vibration parameters are derived from the fitting curve parameters of the relative offset. According to the detected vibration parameters, the discrete point spread function is obtained, and the rolling-shutter CMOS image degradation caused by vibration is restored row by row. The verification experiments demonstrate that the proposed detection method for two-dimensional vibration achieves a relative accuracy of less than 1% in period detection and less than 2% in amplitude detection. Additionally, the proposed restoration method can enhance the MTF index by over 20%. The experimental results demonstrate that the detection method is capable of detecting high-frequency vibrations through low-frame-frequency image sequences, and it exhibits excellent applicability in both push-scan cameras and staring cameras. The restoration method effectively enhances the evaluation parameters of image quality and yields a remarkable restorative effect on degraded images.

Frequency of health care provider recommendations for HPV vaccination: a survey in three large cities in China.

Introduction: Human papillomavirus (HPV) infection, an important pathogenic factor for cervical cancer, can be prevented by the HPV vaccine. Health care provider (HCP) recommendations contribute to improve HPV vaccination coverage. The aim of this study was to assess the frequency of HCP recommendations for HPV vaccination and associated factors. Methods: From Nov 8 to Dec 6 in 2018, a cross-sectional study was conducted through online questionnaires among HCPs (n = 1,371) from hospitals in three large cities in China (Shanghai, Guangzhou, and Shenzhen). Data on demographic characteristics, the frequency of HPV vaccination recommendations, HPV knowledge and related attitudes were collected through the questionnaires. Results: Among 1,371 participants, only 30.2% reported that they frequently recommended HPV vaccination. Multivariate analyses indicated that female sex, being employed in obstetrics or gynecology departments and community health service centers, and having higher self-reported and actual knowledge of HPV were factors associated with a higher recommendation frequency. Factors including a self-perceived non-obligation to provide recommendations and difficulties in discussing sexual topics were significantly correlated with less frequent recommendations. Employment in a community health service center (OR = 2.068, 95% CI: 1.070-3.999) was the strongest factor associated with the frequency of HCPs' recommendations for HPV vaccination. Discussion: The frequency of HCPs' recommendations for HPV vaccination in China was much lower than that in many developed countries. To enhance the recommendation frequency, medical institutions should help HCPs gain more knowledge of HPV and master communication skills. At the same time, the government should take measures to enhance the accessibility of HPV vaccines. The media should help to alleviate people's concerns and encourage them to face up sexual health.

Vitexin inhibits pain and itch behavior via modulating TRPV4 activity in mice.

Itching and pain are distinct unpleasant sensations. The transient receptor potential cation channel subfamily V member 4 (TRPV4) pathway is regarded as a shared pathway that mediates pain and itching. Vitexin (Mujingsu, MJS), a C-glycosylflavonoid, is an effective analgesic. This study aimed to explore the antinociceptive and anti-pruritic effects of MJS and whether its effects are mediated via the TRPV4 pathway. Mice were treated with MJS (7.5 mg/kg) 0.5 h prior to the initiation of the pain or itch modeling process. The results showed that MJS suppressed pain-like behavior in hot plate, thermal infiltration, glacial acetic acid twisting, and formalin tests. Administration of MJS decreased the pruritus response induced by histamine, C48/80, chloroquine and BAM8-22 within 30 min. MJS reduced scratching bouts and lessened the wiping reaction of mice under TRPV4 activation by GSK101 (10 µg/5 µl). MJS inhibited scratching behavior in acetone-ether-water (AEW)-treated mice within 60 min. An H1 receptor antagonist-chlorpheniramine (CLP, 400 mg/kg)-and a TRPV4 antagonist-HC067047 (250 ng/kg), exhibited similar effects to those of MJS. Moreover, MJS ameliorated dry skin itch-associated cutaneous barrier disruption in mice. MJS did not inhibit the expression of TRPV4 in the dorsal root ganglion neurons at L2-L3 in AEW mice. These results indicate that the analgesic and anti-pruritic effects of MJS in acute and chronic pain and itching, as well as itching caused by TRPV4 activation, could be attributed to the TRPV4 pathway modulation.

4-Octyl itaconate attenuates glycemic deterioration by regulating macrophage polarization in mouse models of type 1 diabetes.

BACKGROUND: Pancreatic beta cell dysfunction and activated macrophage infiltration are early features in type 1 diabetes pathogenesis. A tricarboxylic acid cycle metabolite that can strongly activate NF-E2-related factor 2 (Nrf2) in macrophages, itaconate is important in a series of inflammatory-associated diseases via anti-inflammatory and antioxidant properties. However, its role in type 1 diabetes is unclear. We used 4-octyl itaconate (OI), the cell-permeable itaconate derivate, to explore its preventative and therapeutic effects in mouse models of type 1 diabetes and the potential mechanism of macrophage phenotype reprogramming. METHODS: The mouse models of streptozotocin (STZ)-induced type 1 diabetes and spontaneous autoimmune diabetes were used to evaluate the preventative and therapeutic effects of OI, which were performed by measuring blood glucose, insulin level, pro- and anti-inflammatory cytokine secretion, histopathology examination, flow cytometry, and islet proteomics. The protective effect and mechanism of OI were examined via peritoneal macrophages isolated from STZ-induced diabetic mice and co-cultured MIN6 cells with OI-pre-treated inflammatory macrophages in vitro. Moreover, the inflammatory status of peripheral blood mononuclear cells (PBMCs) from type 1 diabetes patients was evaluated after OI treatment. RESULTS: OI ameliorated glycemic deterioration, increased systemic insulin level, and improved glucose metabolism in STZ-induced diabetic mice and non-obese diabetic (NOD) mice. OI intervention significantly restored the islet insulitis and beta cell function. OI did not alter the macrophage count but significantly downregulated the proportion of M1 macrophages. Additionally, OI significantly inhibited MAPK activation in macrophages to attenuate the macrophage inflammatory response, eventually improving beta cell dysfunction in vitro. Furthermore, we detected higher IL-1ß production upon lipopolysaccharide stimulation in the PBMCs from type 1 diabetes patients, which was attenuated by OI treatment. CONCLUSIONS: These results provided the first evidence to date that OI can prevent the progression of glycemic deterioration, excessive inflammation, and beta cell dysfunction predominantly mediated by restricting macrophage M1 polarization in mouse models of type 1 diabetes.