Flavan-3-ol monomers intake is associated with osteoarthritis risk in Americans over 40 years of age: results from the National Health and Nutritional Examination Survey database.

Objectives: Osteoarthritis (OA) stands as the prevailing progressive musculoskeletal disease, serving as the primary cause of chronic pain and activity limitations among adults over 40. Flavan-3-ols, common polyphenolic compounds, are believed to harbor anti-inflammatory and anti-aging properties. This study explores the relationship between flavan-3-ol intake and osteoarthritis risk in individuals over the age of 40 in the US. Methods: This study included 7452 participants over the age of 40 from three cycles (2007-2008, 2009-2010, and 2017-2018) of the National Health and Nutrition Examination Survey. Information on OA history was obtained via home surveys. Information on flavan-3-ol monomers intake was obtained using a survey from the Food and Nutrient Database for Dietary Studies. We used a logistic regression model and restricted cubic spline to analyze the relationships between flavan-3-ol monomers and OA. Stratified analyses were also conducted in this study. Results: There were 1056 participants with OA and 6396 without OA. Compared to the first tertile (T1) group, the adjusted odds ratio with a 95% confidence interval (CI) of logistic regression model 2 for the flavan-3-ol T2 group was 1.296 (0.979-1.715) (p = 0.068), the OR for (-)-epigallocatechin was 1.292 (1.025-1.629) (p = 0.032), and the OR for (-)-epicatechin 3-gallate was 1.348 (1.013, 1.793) (p = 0.042). A dose-response curve indicated a non-linear association (p for non-linearity <0.05) between OA and total flavan-3-ol monomers (nadir point: 483.29 mg, 95% CI: 0.61-0.90). No interaction effects were found in the subgroup analysis. Conclusions: In individuals over 40 in the US, the average daily dietary intake of flavan-3-ol monomers manifests a J-shaped relationship with OA risk.

Magnesium Ions Promote the Induction of Immunosuppressive Bone Microenvironment and Bone Repair through HIF-1α-TGF-ß Axis in Dendritic Cells.

The effect of immunoinflammation on bone repair during the recovery process of bone defects needs to be further explored. It is reported that Mg2+ can promote bone repair with immunoregulatory effect, but the underlying mechanism on adaptive immunity is still unclear. Here, by using chitosan and hyaluronic acid-coated Mg2+ (CSHA-Mg) in bone-deficient mice, it is shown that Mg2+ can inhibit the activation of CD4+ T cells and increase regulatory T cell formation by inducing immunosuppressive dendritic cells (imDCs). Mechanistically, Mg2+ initiates the activation of the MAPK signaling pathway through TRPM7 channels on DCs. This process subsequently induces the downstream HIF-1α expression, a transcription factor that amplifies TGF-ß production and inhibits the effective T cell function. In vivo, knock-out of HIF-1α in DCs or using a HIF-1α inhibitor PX-478 reverses inhibition of bone inflammation and repair promotion upon Mg2+-treatment. Moreover, roxadustat, which stabilizes HIF-1α protein expression, can significantly promote immunosuppression and bone repair in synergism with CSHA-Mg. Thus, the findings identify a key mechanism for DCs and its HIF-1α-TGF-ß axis in the induction of immunosuppressive bone microenvironment, providing potential targets for bone regeneration.

Understanding China's shifting priorities and priority-setting processes in development assistance for health.

Over the past two decades, China has become a distinctive and increasingly important donor of development assistance for health (DAH). However, little is known about what factors influence China's priority-setting for DAH. In this study, we provide an updated analysis of trends in the priorities of Chinese DAH and compare them to comparable trends among OECD Development Assistance Committee (DAC) donors using data from the AidData's Global Chinese Development Finance Dataset (2000-2017, version 2.0) and the Creditor Reporting System (CRS) database (2000-2017). We also analyse Chinese medical aid exports before and after the start of the COVID-19 pandemic using a Chinese Aid Exports Database. We further explore the potential factors influencing China's shifting priority-setting processes by reviewing Chinese official documents following Walt and Gilson's policy analysis framework (context-actors-process-content) and by testing our conjectures empirically. We find that China has become an important DAH donor to most regions if measured using project value, including but not limited to Africa. China has prioritized aid to African and Asian countries as well as to CRS subsectors that are not prioritized by DAC donors, such as medical services and basic health infrastructure. Chinese quarterly medical aid exports almost quintupled after the start of the COVID-19 pandemic. Noticeably, China has allocated more attention to Asia, eye diseases and infectious disease outbreaks over time. In contrast, the priority given to malaria has declined over the same period. Regarding factors affecting priority shifts, the outbreaks of SARS and Ebola, the launch of the Belt and Road Initiative and the COVID-19 pandemic appear to be important milestones in the timeline of Chinese DAH. Unlike stereotypes of China as a 'lone wolf' donor, our analysis suggests multilateral processes are influential in informing and setting Chinese DAH priorities.

Characteristic Features of Deep Brain Lymphatic Vessels and Their Regulation by Chronic Stress.

Studies have demonstrated that a functional network of meningeal lymphatic vessels exists in the brain. However, it is unknown whether lymphatic vessels could also extend deep into the brain parenchyma and whether the vessels could be regulated by stressful life events. We used tissue clearing techniques, immunostaining, light-sheet whole-brain imaging, confocal imaging in thick brain sections and flow cytometry to demonstrate the existence of lymphatic vessels deep in the brain parenchyma. Chronic unpredictable mild stress or chronic corticosterone treatment was used to examine the regulation of brain lymphatic vessels by stressful events. Western blotting and coimmunoprecipitation were used to provide mechanistic insights. We demonstrated the existence of lymphatic vessels deep in the brain parenchyma and characterized their features in the cortex, cerebellum, hippocampus, midbrain, and brainstem. Furthermore, we showed that deep brain lymphatic vessels can be regulated by stressful life events. Chronic stress reduced the length and areas of lymphatic vessels in the hippocampus and thalamus but increased the diameter of lymphatic vessels in the amygdala. No changes were observed in prefrontal cortex, lateral habenula, or dorsal raphe nucleus. Chronic corticosterone treatment reduced lymphatic endothelial cell markers in the hippocampus. Mechanistically, chronic stress might reduce hippocampal lymphatic vessels by down-regulating vascular endothelial growth factor C receptors and up-regulating vascular endothelial growth factor C neutralization mechanisms. Our results provide new insights into the characteristic features of deep brain lymphatic vessels, as well as their regulation by stressful life events.

Hyperspectral imaging for accurate determination of rice variety using a deep learning network with multi-feature fusion.

The phenomena of rice adulteration and shoddy rice arise continuously in high-quality rice and reduce the interests of producers, consumers and traders. Hyperspectral imaging (HSI) was conducted to determine rice variety using a deep learning network with multiple features, namely, spectroscopy, texture and morphology. HSI images of 10 representative high-quality rice varieties in China were measured. Spectroscopy and morphology were extracted from HSI images and binary images in region of interest, respectively. And texture was obtained from the monochromatic images of characteristic wavelengths which were highly correlated with rice varieties. A deep learning network, namely principal component analysis network (PCANet), was adopted with these features to develop classification models for determining rice variety, and machine learning methods as K-nearest neighbour and random forest were used to compare with PCANet. Meanwhile, multivariate scatter correction, standard normal variate, Savitzky-Golay smoothing and Savitzky-Golay's first-order were applied to eliminate spectral interference, and principal component analysis (PCA) was performed to obtain the main information of high-dimensional features. Multi-feature fusion improved recognition accuracy, and PCANet demonstrated considerable advantage in classification performance. The best result was achieved by PCANet with PCA-processed spectroscopic and texture features with correct classification rates of 98.66% and 98.57% for the training and prediction sets, respectively. In summary, the proposed method provides an accurate identification of rice variety and can be easily extended to the classification, attribution and grading of other agricultural products.

Rapid detection of adulteration of minced beef using Vis/NIR reflectance spectroscopy with multivariate methods.

High economic returns induce the continuous occurrence of meat adulteration. In this study, visible/near-infrared (Vis/NIR) reflectance spectroscopy with multivariate methods was used for the rapid detection of adulteration in minced beef. First, the reflectance spectra of different adulterated minced beef samples were measured at 350-2500 nm. Standardization and Savitzky-Golay (SG) smoothing were applied to reduce spectral interference and noise. Then, support vector machine (SVM), random forest (RF), partial least squares regression (PLSR), and deep convolutional neural network (DCNN) were adopted for adulteration type identification and level prediction. Moreover, principal component analysis (PCA), locally linear embedding (LLE), subwindow permutation analysis (SPA), and competitive adaptive reweighted sampling (CARS) were performed to eliminate redundant information. SG smoothing performed better on interference reduction. DCNN and PCA identified adulteration type with the accuracy above 99%. In adulteration level prediction, the RF with spectra of important wavelengths selected by CARS provided optimal performance for beef adulterated with pork, and coefficient of determination of prediction (R2P) and the root mean square error of prediction (RMSEP) were 0.973 and 2.145. The best prediction for beef adulterated with beef heart was obtained using PLSR and CARS with R2P of 0.960 and RMSEP of 2.758. Accordingly, Vis/NIR reflectance spectroscopy coupled with multivariate methods can provide the rapid and accurate detection of adulterated minced beef.