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Conclusions Patients with AD and age ≥80 years have a higher mortality rate and cumulative major complications as compared younger patients. Invasive treatments were associated to a poor prognosis in this group.Importance of sperm-derived transcripts and chromatin imprints in organismal development is poorly investigated. Here using an integrative approach, we show that human sperm transcripts are equally important as oocyte. Sperm-specific and sperm-oocyte common transcripts carry distinct chromatin structures at their promoters correlating with corresponding transcript levels in sperm. Interestingly, sperm-specific H3K4me3 patterns at the lincRNA promoters are not maintained in the germ layers and somatic tissues. However, bivalent chromatin at the sperm-specific protein-coding gene promoters is maintained throughout the development. Sperm-specific transcripts reach their peak expression during zygotic genome activation, whereas sperm-oocyte common transcripts are present during early preimplantation development but decline at the onset of zygotic genome activation. Additionally, there is an inverse correlation between sperm-specific and sperm-oocyte lincRNAs throughout the development. Sperm-lincRNAs also show aberrant activation in tumors. Overall, our observations indicate that sperm transcripts carrying chromatin imprints may play an important role in human development and cancer.Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic in the past four months and causes respiratory disease in humans of almost all ages. [https://www.selleckchem.com/products/PD-0325901.html Mirdametinib] Although several drugs have been announced to be partially effective treatments for this disease, no approved vaccine is available. Here, we described the construction of a recombinant Lactobacillus plantarum strain expressing the SARS-CoV-2 spike protein. The results showed that the spike gene with optimized codons could be efficiently expressed on the surface of recombinant L. plantarum and exhibited high antigenicity. The highest protein yield was obtained under the following conditions cells were induced with 50 ng/mL SppIP at 37 °C for 6-10 h. The recombinant spike (S) protein was stable under normal conditions and at 50 °C, pH = 1.5, or a high salt concentration. Recombinant L. plantarum may provide a promising food-grade oral vaccine candidate against SARS-CoV-2 infection.Deep learning has received increasing attention in recent years and it has been successfully applied for feature extraction (FE) of hyperspectral images. However, most deep learning methods fail to explore the manifold structure in hyperspectral image (HSI). To tackle this issue, a novel graph-based deep learning model, termed deep locality preserving neural network (DLPNet), was proposed in this paper. Traditional deep learning methods use random initialization to initialize network parameters. Different from that, DLPNet initializes each layer of the network by exploring the manifold structure in hyperspectral data. In the stage of network optimization, it designed a deep-manifold learning joint loss function to exploit graph embedding process while measuring the difference between the predictive value and the actual value, then the proposed model can take into account the extraction of deep features and explore the manifold structure of data simultaneously. Experimental results on real-world HSI datasets indicate that the proposed DLPNet performs significantly better than some state-of-the-art methods.Deep learning has received increasing attention in recent years and it has been successfully applied for feature extraction (FE) of hyperspectral images. However, most deep learning methods fail to explore the manifold structure in hyperspectral image (HSI). To tackle this issue, a novel graph-based deep learning model, termed deep locality preserving neural network (DLPNet), was proposed in this paper. Traditional deep learning methods use random initialization to initialize network parameters. Different from that, DLPNet initializes each layer of the network by exploring the manifold structure in hyperspectral data. In the stage of network optimization, it designed a deep-manifold learning joint loss function to exploit graph embedding process while measuring the difference between the predictive value and the actual value, then the proposed model can take into account the extraction of deep features and explore the manifold structure of data simultaneously. Experimental results on real-world HSI datasets indicate that the proposed DLPNet performs significantly better than some state-of-the-art methods.Identifying individual differences in stress reactivity is of particular interest in the context of stress-related disorders and resilience. Previous studies already identified several factors mediating the individual stress response of the hypothalamus-pituitary-adrenal axis (HPA). However, the impact of long-term HPA axis activity on acute stress reactivity remains inconclusive. To investigate associations between long-term HPA axis variation and individual acute stress reactivity, we tested 40 healthy volunteers for affective, endocrine, physiological, and neural reactions to a modified, compact version of the established in-MR stress paradigm ScanSTRESS (ScanSTRESS-C). Hair cortisol concentrations (HCC) served as an integrative marker of long-term HPA axis activity. First, the ScanSTRESS-C version proved to be valid in evoking a subjective, endocrine, physiological, and neural stress response with enhanced self-reported negative affect and cortisol levels, increased heart rate as well as increased activation in the anterior insula and the dorso-anterior cingulate cortex (dACC). Second and interestingly, results indicated a lower neuroendocrine stress response in individuals with higher HCC HCC was negatively correlated with the area under the curve (respect to increase; AUCi) of saliva cortisol and with a stress-related increase in dACC activity. The present study explicitly targeted the relationship between HCC and acute stress reactivity on multiple response levels, i.e. subjective, endocrine and neural stress responses. The lower stress reactivity in individuals with higher HCC levels indicates the need for further research evaluating the role of long-term HPA axis alterations in the context of vulnerability or immunization against acute stress and following stress-related impairments.