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Transfer learning can enhance classification performance of a target domain with insufficient training data by utilizing knowledge relating to the target domain from source domain. Nowadays, it is common to see two or more source domains available for knowledge transfer, which can improve performance of learning tasks in the target domain. However, the classification performance of the target domain decreases due to mismatching of probability distribution. Recent studies have shown that deep learning can build deep structures by extracting more effective features to resist the mismatching. In this paper, we propose a new multi-source deep transfer neural network algorithm, MultiDTNN, based on convolutional neural network and multi-source transfer learning. In MultiDTNN, joint probability distribution adaptation (JPDA) is used for reducing the mismatching between source and target domains to enhance features transferability of the source domain in deep neural networks. Then, the convolutional neural network is trained by utilizing the datasets of each source and target domain to obtain a set of classifiers. Finally, the designed selection strategy selects classifier with the smallest classification error on the target domain from the set to assemble the MultiDTNN framework. The effectiveness of the proposed MultiDTNN is verified by comparing it with other state-of-the-art deep transfer learning on three datasets.

Acute myeloid leukemia (AML) with t(8;21)(q22;q22.1);RUNX1-ETO is one of the most common subtypes of AML. Although t(8;21) AML has been classified as favorable-risk, only about half of patients are cured with current therapies. Several genetic abnormalities, including TP53 mutations and deletions, negatively impact survival in t(8;21) AML. In this study, we established Cas9 + mouse models of t(8;21) AML with intact or deficient Tpr53 (a mouse homolog of TP53 ) using a retrovirus-mediated gene transfer and transplantation system. Trp53 deficiency accelerates the in vivo development of AML driven by RUNX1-ETO9a, a short isoform of RUNX1-ETO with strong leukemogenic potential. Trp53 deficiency also confers resistance to genetic depletion of RUNX1 and a TP53-activating drug in t(8;21) AML. However, Trp53 -deficient t(8;21) AML cells were still sensitive to several drugs such as dexamethasone. Cas9 + RUNX1-ETO9a cells with/without Trp53 deficiency can produce AML in vivo, can be cultured in vitro for several weeks, and allow efficient gene depletion using the CRISPR/Cas9 system, providing useful tools to advance our understanding of t(8;21) AML.

The recently emerged Omicron (B.1.1.529) variant has rapidly surpassed Delta to become the predominant circulating SARS-CoV-2 variant, given the higher transmissibility rate and immune escape ability, resulting in breakthrough infections in vaccinated individuals. A new generation of SARS-CoV-2 vaccines targeting the Omicron variant are urgently needed. Here, we developed a subunit vaccine named RBD-HR/trimer by directly linking the sequence of RBD derived from the Delta variant (containing L452R and T478K) and HR1 and HR2 in SARS-CoV-2 S2 subunit in a tandem manner, which can self-assemble into a trimer. In multiple animal models, vaccination of RBD-HR/trimer formulated with MF59-like oil-in-water adjuvant elicited sustained humoral immune response with high levels of broad-spectrum neutralizing antibodies against Omicron variants, also inducing a strong T cell immune response in vivo. In addition, our RBD-HR/trimer vaccine showed a strong boosting effect against Omicron variants after two doses of mRNA vaccines, featuring its capacity to be used in a prime-boost regimen. In mice and non-human primates, RBD-HR/trimer vaccination could confer a complete protection against live virus challenge of Omicron and Delta variants. The results qualified RBD-HR/trimer vaccine as a promising next-generation vaccine candidate for prevention of SARS-CoV-2, which deserved further evaluation in clinical trials. The SARS-CoV-2 Omicron variant has quickly become the predominant circulating variant, due to the high transmissibility and immune escape. Here, the authors develop a trimeric protein vaccine candidate and show a sustained humoral immune response, and protection from challenge (Omicron and Delta) in various animal models.

Background Risk-based breast cancer screening offers a more targeted and potentially cost-effective approach in cancer detection compared to age-based screening. This study aims to understand women’s preferences and willingness for undergoing risk assessment tests. Methods A discrete choice experiment (DCE) was conducted. Six attributes were selected to construct the DCE questionnaire: one-time cost of the test, methods for reducing late-stage breast cancer, annual breast cancer screening expenses, insurance coverage for early-stage breast cancer, family risk correlation, and risk communication methods. Women aged between 21 and 59 were recruited from Singapore. Latent class analysis was performed. Results Three hundred twenty-eight women were included in the analysis and classified into two classes: test supporters and non-supporters. Both classes prioritised test costs and screening costs. Among non-cost attributes, the potential to reduce late-stage breast cancer diagnosis was the most influential factor. Insurance coverage increased willingness to undergo testing. Risk communication methods were not significant in influencing the decision of undergoing tests. Non-supporters were less inclined to take the test if family risk correlation was high. Younger women, married women, full-time employees, and those with a history of breast disease were more likely to be supporters. Women with a family history of breast cancer were more likely to be non-supporters. Conclusions Financial incentives play a notable role in increasing the uptake of risk-prediction tests. However, the programme’s success depends on understanding and addressing the diverse preferences of women. While cost considerations ranked highly, additional strategies are needed to engage groups that are hesitant, particularly those with a high family risk correlation.

All-aqueous emulsions exploit spontaneous liquid–liquid separation and due to their water-based nature are particular advantageous for the biocompatible storage and processing of biomacromolecules. However, the ultralow interfacial tensions characteristic of all-aqueous interfaces represent an inherent limitation to the use of thermally adsorbed particles to achieve emulsion stability. Here, we use protein nanofibrils to generate colloidosome-like two-dimensional crosslinked networks of nanostructures templated by all-aqueous emulsions, which we term fibrillosomes. We show that this approach not only allows us to operate below the thermal limit at ultra-low surface tensions but also yields structures that are stable even in the complete absence of an interface. Moreover, we show that the growth and multilayer deposition of fibrils allows us to control the thickness of the capsule shells. These results open up the possibility of stabilizing aqueous two-phase systems using natural proteins, and creating self-standing protein capsules without the requirement for three-phase emulsions or water/oil interfaces. All-aqueous emulsions are useful for delivering and processing biomolecules, but their stability is constrained by low interfacial adsorption energy. Song et al . solve this problem using protein nanofibrils that form a crosslinked network, whose stability is superior to conventional colloidal capsules.

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic event in the world, it has not only caused huge economic losses, but also a serious threat to global public health. Many scientific questions about SARS-CoV-2 and Coronavirus disease (COVID-19) were raised and urgently need to be answered, including the susceptibility of animals to SARS-CoV-2 infection. Here we tested whether tree shrew, an emerging experimental animal domesticated from wild animal, is susceptible to SARS-CoV-2 infection. No clinical signs were observed in SARS-CoV-2 inoculated tree shrews during this experiment except the increasing body temperature particularly in female animals. Low levels of virus shedding and replication in tissues occurred in all three age groups. Notably, young tree shrews (6 months to 12 months) showed virus shedding at the earlier stage of infection than adult (2 years to 4 years) and old (5 years to 7 years) animals that had longer duration of virus shedding comparatively. Histopathological examine revealed that pulmonary abnormalities were the main changes but mild although slight lesions were also observed in other tissues. In summary, tree shrew is less susceptible to SARS-CoV-2 infection compared with the reported animal models and may not be a suitable animal for COVID-19 related researches. However, tree shrew may be a potential intermediate host of SARS-CoV-2 as an asymptomatic carrier.

To improve the integrity of vegetation point clouds, the missing vegetation point can be compensated through vegetation point clouds completion technology. Further, it can enhance the accuracy of these point clouds’ applications, particularly in terms of quantitative calculations, such as for the urban living vegetation volume (LVV). However, owing to factors like the mutual occlusion between ground objects, sensor perspective, and penetration ability limitations resulting in missing single tree point clouds’ structures, the existing completion techniques cannot be directly applied to the single tree point clouds’ completion. This study combines the cutting-edge deep learning techniques, for example, the self-supervised and multiscale Encoder (Decoder), to propose a tree completion net (TC-Net) model that is suitable for the single tree structure completion. Being motivated by the attenuation of electromagnetic waves through a uniform medium, this study proposes an uneven density loss pattern. This study uses the local similarity visualization method, which is different from ordinary Chamfer distance (CD) values and can better assist in visually assessing the effects of point cloud completion. Experimental results indicate that the TC-Net model, based on the uneven density loss pattern, effectively identifies and compensates for the missing structures of single tree point clouds in real scenarios, thus reducing the average CD value by above 2.0, with the best result dropping from 23.89 to 13.08. Meanwhile, experiments on a large-scale tree dataset show that TC-Net has the lowest average CD value of 13.28. In the urban LVV estimates, the completed point clouds have reduced the average MAE, RMSE, and MAPE from 9.57, 7.78, and 14.11% to 1.86, 2.84, and 5.23%, respectively, thus demonstrating the effectiveness of TC-Net.

The overall oocyte quality declines with aging, and this effect is strongly associated with a higher reactive oxygen species (ROS) level and the resultant oxidative damage. C-type natriuretic peptide (CNP) is a well-characterized physiological meiotic inhibitor that has been successfully used to improve immature oocyte quality during in vitro maturation. However, the underlying roles of CNP in maternally aged oocytes have not been reported. Here, we found that the age-related reduction in the serum CNP concentration was highly correlated with decreased oocyte quality. Treatment with exogenous CNP promoted follicle growth and ovulation in aged mice and enhanced meiotic competency and fertilization ability. Interestingly, the cytoplasmic maturation of aged oocytes was thoroughly improved by CNP treatment, as assessed by spindle/chromosome morphology and redistribution of organelles (mitochondria, the endoplasmic reticulum, cortical granules, and the Golgi apparatus). CNP treatment also ameliorated DNA damage and apoptosis caused by ROS accumulation in aged oocytes. Importantly, oocyte RNA-seq revealed that the beneficial effect of CNP on aged oocytes was mediated by restoration of mitochondrial oxidative phosphorylation, eliminating excessive mitophagy. CNP reversed the defective phenotypes in aged oocytes by alleviating oxidative damage and suppressing excessive PINK1/Parkin-mediated mitophagy. Mechanistically, CNP functioned as a cAMP/PKA pathway modulator to decrease PINK1 stability and inhibit Parkin recruitment. In summary, our results demonstrated that CNP supplementation constitutes an alternative therapeutic approach for advanced maternal age-related oocyte deterioration and may improve the overall success rates of clinically assisted reproduction in older women.

Background: Gene therapy has emerged as a new strategy for cancer therapy. As an alternative nucleic acid material, messenger ribonucleic acid (mRNA) is being increasingly utilized in cancer gene therapy. However, unfulfilled requirements and a lack of ideal mRNA delivery vectors persist. Methods: We developed an advanced mRNA delivery system, DMP-039, by fusing a cell-penetrating peptide, cRGD-R9, and a cationic nano-sized DMP backbone together. The DMP gene vector backbone was synthesized by the self-assembly of DOTAP lipid and mPEG-PCL polymer. Introduction of the cRGD-R9 peptide onto the DMP backbone was performed to elevate the mRNA delivery capacity, which resulted in a peptide-functionalized hybrid delivery system. Results: The average size of the synthesized DMP-039 was 268.9 [+ or -] 12.4 nm (PDI = 0.382), with a potential of 17.4 [+ or -] 0.5 mV. The synthesized DMP-039 hybrid nanoparticles exhibited high mRNA delivery efficiency through multiple mechanisms during transmembrane transportation. By loading the encoding mRNA from the suicide gene Bim, a locally administered mBim/DMP-039 complex strongly inhibited growth in two colon cancer models. Moreover, intravenous administration of the mBim/DMP-039 complex efficiently suppressed C26 pulmonary metastatic tumor progression with high safety. The in vivo distribution, degradation, and excretion were also investigated in detail. Conclusion: Our results suggest that the DMP-039 peptide-functionalized hybrid nanoparticle is an advanced candidate for mRNA-based suicide gene therapy. Keywords: mRNA, Bim, cell-penetrating peptide, gene therapy

Identification of a suitable nonhuman primate (NHP) model of COVID-19 remains challenging. Here, we characterized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in three NHP species: Old World monkeys Macaca mulatta (M. mulatta) and Macaca fascicularis (M. fascicularis) and New World monkey Callithrix jacchus (C. jacchus). Infected M. mulatta and M. fascicularis showed abnormal chest radiographs, an increased body temperature and a decreased body weight. Viral genomes were detected in swab and blood samples from all animals. Viral load was detected in the pulmonary tissues of M. mulatta and M. fascicularis but not C. jacchus. Furthermore, among the three animal species, M. mulatta showed the strongest response to SARS-CoV-2, including increased inflammatory cytokine expression and pathological changes in the pulmonary tissues. Collectively, these data revealed the different susceptibilities of Old World and New World monkeys to SARS-CoV-2 and identified M. mulatta as the most suitable for modeling COVID-19.