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Abstract Aged male patients are more vulnerable to severe or critical symptoms of COVID‐19, but the underlying mechanism remains elusive. In this study, we analyzed previously published scRNA‐seq data from a large cohort of COVID‐19 patients, castrated and regenerated mice, and bulk RNA‐seq of a RNAi library of 400 genes, and revealed that both immunity and OXPHOS displayed cell‐type‐, sex‐, and age‐related variation in the severe or critical COVID‐19 patients during disease progression, with a more prominent increase in immunity and decrease in OXPHOS in myeloid cells in the males relative to the females (60–69 years old). Male severe or critical patients above 70 years old were an exception in that the compromised negative correlation between OXPHOS and immunity in these patients was associated with its disordered transcriptional regulation. Finally, the expression levels of OXPHOS and androgens were revealed to be positively correlated, and the responses of macrophages to android fluctuation were more striking than other types of detected immune cells in the castrated mice model. Therefore, the interplay of OXPHOS and immunity displayed a cell‐type‐specific, age‐related, and sex‐biased pattern, and the underlying potential regulatory role of the hormonal milieu should not be neglected.

The management and disposal of waste is a severe social issue and an essential part of ecological sustainability. As an important component of the green, low-carbon, and recycling economic system, the identification and classification of recyclable waste is the premise of its reuse and energy conservation. The main issues at hand are to improve the classification accuracy and reliability of recyclable waste and to achieve automatic classification. The methods based on physical characteristics and image-based methods are inaccurate and unreliable. The current spectroscopy methods need to process the detected samples in advance, unsuitable for automatic detection. Based on material composition properties, the Laser-Induced Breakdown Spectroscopy (LIBS) technology is here proposed to accurately and reliably identify and classify recyclable waste into six categories at the level of consumer, such as paper, plastic, glass, metal, textile, and wood. The method is also used to subclassify the same category of waste for reuse at the level of a recycling factory. We subclassified metals into iron, stainless steel, copper, and aluminum and plastics into polyvinylchloride, polyoxymethylene, acrylonitrile-butadiene-styrene, polyamide, polyethylene, and polytetrafluoroethylene. The drop-dimension methods of LIBS spectra of waste were researched to eliminate noise and redundant information by principal component analysis (PCA) and linear discriminant analysis (LDA), respectively. Their clustering effects were analyzed to choose a suitable dimension. Combining the random forest (RF), back propagation neural network (BPNN), and convolutional neural network (CNN), we established and compared five classification models, PCA + RF, PCA + BPNN, LDA + RF, LDA + BPNN, and 1D-CNN. For the classification of six categories, the accuracies of proposed classification models are all more than 96%, and LDA(5D) + RF has 100% accuracy and optimal classification performance indices. For the subclassification of metals and plastics, PCA(8D) + RF has the highest classification accuracy of 98.77% and 99.52%, respectively.

In order to study effects of macrophage-derived inflammatory mediators associated with systemic inflammation on brain endothelial cells, we have established a co-culture system consisting of bEnd.3 cells and LPS-activated Raw 264.7 cells and performed its cytokine profiling. The cytokine profile of the co-culture model was compared to that of mice treated with intraperitoneal LPS injection. We found that, among cytokines profiled, eight cytokines/chemokines were similarly upregulated in both in vivo mouse and in vitro co-culture model. In contrast to the co-culture model, the cytokine profile of a common mono-culture system consisting of only LPS-activated bEnd.3 cells had little similarity to that of the in vivo mouse model. These results indicate that the co-culture of bEnd.3 cells with LPS-activated Raw 264.7 cells is a better model than the common mono-culture of LPS-activated bEnd.3 cells to investigate the molecular mechanism in endothelial cells, by which systemic inflammation induces neuroinflammation. Moreover, fibrinogen adherence both to bEnd.3 cells in the co-culture and to brain blood vessels in a LPS-treated animal model of Alzheimer's disease increased. To the best of our knowledge, this is the first to utilize bEnd.3 cells co-cultured with LPS-activated Raw 264.7 cells as an in vitro model to investigate the consequence of macrophage-derived inflammatory mediators on brain endothelial cells.

Leydig cells (Lc), located in the interstitial space of the testis between seminiferous tubules, produce 95% of testosterone in male individuals, which is pivotal for male sexual differentiation, spermatogenesis, and maintenance of the male secondary sex characteristics. Lc are prone to senescence in aging testes, resulting in compromised androgen synthesis capability upon aging. However, little is known about whether Lc undergo senescence in a chronic inflammatory environment. To investigate this question, mouse models of experimental autoimmune orchitis (EAO) were used, and Lc were analyzed by high throughput scRNA-Seq. Data were screened and analyzed by correlating signaling pathways with senescence, apoptosis, androgen synthesis, and cytokine/chemokine signaling pathways. EAO did induce Lc senescence, and Lc senescence in turn antagonized androgen synthesis. Based on the correlation screening of pathways inducing Lc senescence, a plethora of pathways were found to play potential roles in triggering Lc senescence during EAO, among which the Arf6 and angiopoietin receptor pathways were highly correlated with senescence signature. Notably, complement and interstitial fibrosis activated by EAO worsened Lc senescence and strongly antagonized androgen synthesis. Furthermore, most proinflammatory cytokines enhanced both senescence and apoptosis in Lc and spermatogonia (Sg) during EAO, and proinflammatory cytokine antagonism of the glutathione metabolism pathway may be key in inducing cellular senescence during EAO.

mRNAs have been found to undergo substantial selective degradation during the late stages of spermiogenesis. However, the mechanisms regulating this biological process are unknown. In this report, we have identified Tex13a, a spermatid-specific gene that interacts with the CCR4–NOT complex and is implicated in the targeted degradation of mRNAs encoding particular structural components of sperm. Deletion of Tex13a led to a delayed decay of these mRNAs, lowered the levels of house-keeping genes, and ultimately lowered several key parameters associated with the control of sperm motility, such as the path velocity (VAP, average path velocity), track speed (VCL, velocity curvilinear), and rapid progression.

Wall-penetrating radar (WPR) is the device to image very small objects buried inside the wall. The small objects usually a few millimetres, whereas the bandwidth of WPR limits its resolution up to several centimetres. As a result, the target imaging result of the traditional method is ‘defocused’ in the range direction. To solve this problem, a near-field three-dimensional imaging algorithm based on matching filtering with multiple reference signals and selection processing is proposed. Instead of obtaining a focused image via coherent superposition processing, a focused image is determined by selecting an image from a plurality imaging results of different reference depths according to the minimum entropy criterion. The proposed algorithm is validated by imaging the computer simulation technology simulation data and the measured data.

Through-the-wall radar has been used in rescue missions, behind-the-wall targets detection, surveillance and reconnaissance etc. However, through-the-wall radar encounters two major problems in complex environment. One is that the refraction of the unknown wall would distort the through-the-wall image. The other is that the multi-reflection between wall and walls as well as wall and targets would lead to a lot of fake targets. To solve these problems, a multi-path suppression algorithm is proposed in this study. The simulation results show that proposed algorithm can automatically estimate the thickness and dielectric parameter of the unknown wall and give an undistort image, and remove the fake targets due to the multi-path effect.