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Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen prediction focus on the binding between human leukocyte antigens (HLAs) and peptides, which is insufficient for high-confidence neoantigen prediction. In this study, we apply deep learning techniques to predict neoantigens considering both the possibility of HLA-peptide binding (binding model) and the potential immunogenicity (immunogenicity model) of the peptide-HLA complex (pHLA). The binding model achieves comparable performance with other well-acknowledged tools on the latest Immune Epitope Database (IEDB) benchmark datasets and an independent mass spectrometry (MS) dataset. The immunogenicity model could significantly improve the prediction precision of neoantigens. The further application of our method to the mutations with pre-existing T-cell responses indicating its feasibility in clinical application. DeepHLApan is freely available at https://github.com/jiujiezz/deephlapan and http://biopharm.zju.edu.cn/deephlapan.

As a next-generation immersive service, holographic video enables users to move freely within a virtual world. This imposes stringent requirements on wireless networks. Given the massive bandwidth capacity inherent to visible light, visible light communication (VLC) can effectively meet the transmission requirements of holographic video and is an ideal wireless technology for next-generation indoor immersive services. However, VLC channels are highly dependent on Line-of-Sight (LoS) links. Due to user mobility, traditional VLC systems relying on fixed-orientation Photodetectors (PDs) often suffer from severe channel fading, which significantly degrades the transmission performance. In this paper, we propose an indoor VLC holographic video transmission architecture supporting rotatable PDs, utilizing rotatable PDs mounted on Head-Mounted Displays (HMDs) to assist in holographic video transmission. To minimize the total transmission delay of all users, we address the holographic video transmission problem by jointly optimizing the transmit power allocation of VLC Access Points (APs) and the pitch and roll angles of the users’ PDs. By formulating the problem as a Markov Decision Process (MDP), we address it using a novel Deep Reinforcement Learning (DRL) strategy leveraging the Soft Actor–Critic (SAC) architecture. Simulation results demonstrate that the proposed scheme reduces the overall latency by up to 29.6% compared to the benchmark schemes. Furthermore, the convergence speed of the algorithm is improved by 35% compared to traditional deep reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG).

The destruction of the microvascular structure and function can seriously affect the survival and prognosis of patients with acute myocardial infarction (AMI). Nuciferine has a potentially beneficial effect in the treatment of cardiovascular disease, albeit its role in microvascular structure and function during AMI remains unclear. This study aimed to investigate the protective effect and the related mechanisms of nuciferine in microvascular injury during AMI. Cardiac functions and pathological examination were conducted in vivo to investigate the effect of nuciferine on AMI. The effect of nuciferine on permeability and adherens junctions in endothelial cells was evaluated in vitro, and the phosphorylation level of the PI3K/AKT pathway (in the presence or absence of PI3K inhibitors) was also analyzed. In vivo results indicated that nuciferine inhibited ischemia-induced cardiomyocyte damage and vascular leakage and improved cardiac function. In addition, the in vitro results revealed that nuciferine could effectively inhibit oxygen–glucose deprivation (OGD) stimulated breakdown of the structure and function of human coronary microvascular endothelial cells (HCMECs). Moreover, nuciferine could significantly increase the phosphorylation level of the PI3K/AKT pathway. Finally, the inhibitor wortmannin could reverse the protective effect of nuciferine on HCMECs. Nuciferine inhibited AMI-induced microvascular injury by regulating the PI3K/AKT pathway and protecting the endothelial barrier function in mice.

Background The incidence rates of cervical cancer in developing countries have been steeply increasing while the medical resources for prevention, detection, and treatment are still quite limited. Computer-based deep learning methods can achieve high-accuracy fast cancer screening. Such methods can lead to early diagnosis, effective treatment, and hopefully successful prevention of cervical cancer. In this work, we seek to construct a robust deep convolutional neural network (DCNN) model that can assist pathologists in screening cervical cancer. Methods ThinPrep cytologic test (TCT) images diagnosed by pathologists from many collaborating hospitals in different regions were collected. The images were divided into a training dataset (13,775 images), validation dataset (2301 images), and test dataset (408,030 images from 290 scanned copies) for training and effect evaluation of a faster region convolutional neural network (Faster R-CNN) system. Results The sensitivity and specificity of the proposed cervical cancer screening system was 99.4 and 34.8%, respectively, with an area under the curve (AUC) of 0.67. The model could also distinguish between negative and positive cells. The sensitivity values of the atypical squamous cells of undetermined significance (ASCUS), the low-grade squamous intraepithelial lesion (LSIL), and the high-grade squamous intraepithelial lesions (HSIL) were 89.3, 71.5, and 73.9%, respectively. This system could quickly classify the images and generate a test report in about 3 minutes. Hence, the system can reduce the burden on the pathologists and saves them valuable time to analyze more complex cases. Conclusions In our study, a CNN-based TCT cervical-cancer screening model was established through a retrospective study of multicenter TCT images. This model shows improved speed and accuracy for cervical cancer screening, and helps overcome the shortage of medical resources required for cervical cancer screening.

The multi-UAV relay system can rapidly deploy a temporary communication network in disaster emergency communication scenarios to enhance communication coverage and stability in the affected area and ensure the efficient transmission of rescue information. Aiming at the problems of insufficient real-time performance, low user fairness, and low utilization of communication resources in multi-UAV relay systems, this paper proposes a joint optimization method of communication rate based on Lexicographic Optimization (LO). The multi-UAV relay scenario using multi-carrier non-orthogonal multiple access (MC-NOMA) technology is modeled as a multi-objective optimization problem and solved in stages using the LO method. Specifically, the first stage maximizes the minimum user communication rate by jointly optimizing the user association, relay UAV transmit power and flight trajectory; the second stage optimizes the modulation order of the relay UAVs to maximize the communication rate between UAV base stations. Finally, the proposed algorithm is compared under different optimization schemes and different optimization algorithms. The simulation results show that the user communication rate of the proposed algorithm is 6.8 × 10 5 b p s / s higher than that of the static user association scheme, 6.7 × 10 6 b p s / s higher than that of the static UAV trajectory scheme, and 2.0 × 10 5 b p s / s higher than that of the traditional Jara algorithm, and 6.7 × 10 6 b p s / s higher than that of the K-mean based optimization algorithm. Moreover, this algorithm performs well in convergence and stability, effectively improves the user communication rate, the communication rate between UAV base stations, and the energy utilization of relay UAV, and enhances the adaptability of the system to the dynamic environment.

Background This study aimed to (1) determine the association between varus knee deformity and ipsilateral foot and ankle morphology, and (2) evaluate the relationship between varus knee deformity and foot and ankle pain in patients with end-stage varus knee osteoarthritis (KOA). Methods A total of 213 patients who underwent primary total knee arthroplasty for end-stage varus KOA were enrolled in this study and divided into a ‘severe varus group’ ( n  = 119) and a ‘mild varus group’ ( n  = 94) based on preoperative knee varus degree. Morphological parameters and pain incidence in the foot and ankle were compared between the two groups. The correlation between knee varus and foot and ankle morphology was analyzed. Results Significant differences in ankle morphology were observed between the two groups. The deformity magnitudes of the hindfoot valgus ( P  < 0.001) and hallux valgus (HVA, P  = 0.028; IMA, P  = 0.046) were significantly higher in the severe varus group. Additionally, the incidences of ankle osteoarthritis (OA) ( P  = 0.005) and hallux valgus ( P  = 0.028) were higher in the severe varus group. Patients with severe KOA were more likely to experience medial ankle pain ( P  = 0.023), hindfoot pain ( P  = 0.034), and multiple pain locations ( P  = 0.015). Conclusion Varus knee deformity was associated with morphological changes in the foot and ankle, and the incidence of ankle OA and hallux valgus deformity was significantly higher in patients with severe varus KOA. Patients with severe varus KOA were more prone to medial ankle pain, hindfoot pain, and multiple pain locations, which were associated with corresponding morphological changes.

In recent years, the frequent occurrence of dynamic disasters in tunnels with high stress in fault areas has greatly threatened engineering safety. The typical case – a tunnel influenced by fault slip on is taken as a research object. A series of physical simulation experiments and numerical simulations are conducted to analyze the stress evolution laws in the tunnel roof, shoulder, and coal pillar, along with the stress distribution characteristics across the working face at different excavation stages. The disaster mechanisms, the influence law of fault parameters and control measures for such tunnels are clarified. The main experiment results are as follows. The tunnel located in the hanging wall of the fault experiences a more pronounced increase in stress. Additionally, the closer the tunnel is to the fault plane in the hanging wall, the higher the stresses in the roof, shoulders, and coal pillar sides. For example, the stress at measurement point J β−3 in the β measurement section is 63.4% higher than that at point J α−3 in the α measurement section. Moreover, the surrounding rock at different locations of the tunnel is more severely affected by the fault deeper inside, while the shallow parts experience less influence. Meanwhile, the pressure relief effect by the artificial pre-splitting for high-stress tunnels is proven by the established quantitative evaluation indicators for stress increase and decrease. Among them, the application of the new technology results in a maximum reduction of 145.4% in stress change rate. Through this study, a preliminary measure for controlling the surrounding rock of high-stress tunnels in fault areas is proposed, which can provide a reference for the control of similar tunnels.

Glioblastoma (GBM) is a lethal brain cancer known for its potent immunosuppressive effects. Loss of Methylthioadenosine Phosphorylase ( MTAP ) expression, via gene deletion or epigenetic silencing, is one of the most common alterations in GBM. Here we show that MTAP loss in GBM cells is correlated with differential expression of immune regulatory genes. In silico analysis of gene expression profiles in GBM samples revealed that low MTAP expression is correlated with an increased proportion of M2 macrophages. Using in vitro macrophage models, we found that methylthioadenosine (MTA), the metabolite that accumulates as a result of MTAP loss in GBM cells, promotes the immunosuppressive alternative activation (M2) of macrophages. We show that this effect of MTA on macrophages is independent of IL4/IL3 signaling, is mediated by the adenosine A 2B receptor, and can be pharmacologically reversed. This study suggests that MTAP loss in GBM cells may contribute to the immunosuppressive tumor microenvironment, and that MTAP status should be considered for characterizing GBM immune states and devising immunotherapy-based approaches for treating MTAP -null GBM.

Background Research on factors influencing prolonged length of stay (LOS) and its impact on prognosis in intracerebral hemorrhage (ICH) patients is limited. This study aimed to identify clinical predictors associated with prolonged LOS and to explore the potential impact of prolonged LOS on the prognosis of patients with mild to moderate ICH. Methods The study included mild to moderate ICH patients from the China Quality Evaluation of Stroke Care and Treatment (QUEST) database. Prolonged LOS was defined as a hospitalization exceeding 14 days. Sociodemographic characteristics, medical histories, stroke severity, in-hospital treatments, complications, discharge destination, and hospital characteristics were compared between the prolonged and normal LOS groups to screen for the potential predictors of extending LOS after ICH. The outcomes were the proportions of poor outcome at 3 months and 12 months after stroke onset. Poor outcome was defined as an mRS score of 3–5 or death. Results A total of 1055 mild to moderate ICH patients were enrolled in the study, with 281 (26.6%) exhibiting a LOS of 14 days or less, and 774 (73.4%) exceeding 14 days. The multivariable logistic regression analysis identified several independent predictors of prolonged LOS including younger age, higher annual household income, possession of medical insurance, a history of antithrombotic medication use, infection complication during hospitalization, and hospital regions. Unadjusted analyses showed there were no significant differences in the risk of poor outcome between the prolonged and normal LOS groups at 3 and 12 months after ICH (OR 0.89, 95% CI 0.67–1.17, P  = 0.404; OR 0.82, 95% CI 0.61–1.09, P  = 0.165). The adjusted models and the sensitivity analysis using propensity score matching and subgroup analysis produced the similar results. Conclusions Various factors contributed to prolonged LOS in mild to moderate ICH patients, including younger age, higher annual household income, possession of medical insurance, a history of antithrombotic medication use, the occurrence of infections during hospitalization, and the hospital regions. A prolonged LOS exceeding 14 days was not associated with a better functional outcome for mild to moderate ICH patients at 3 and 12 months.

Background The pathogenesis of malignant neoplasms of bone and articular cartilage is not fully understood, as the inflammatory immune microenvironment may play a crucial role in tumor development and progression. This study aimed to investigate the causal associations between specific inflammatory immune markers and the risk of bone and articular cartilage malignancies. Methods On the basis of genome-wide association study (GWAS) data from inflammatory factors and blood metabolites, single nucleotide polymorphisms (SNPs) with F statistics greater than 10 were selected as valid instrumental variables. Mendelian randomization (MR) methodology was employed to assess causal relationships between inflammatory markers and bone tumor risk, with sensitivity analyses conducted via MR‒Egger, heterogeneity tests, leave-one-out analysis, and MR-PRESSO. Additionally, qRT-PCR was used to validate the expression of key markers in cell lines. Results Mendelian randomization analysis revealed that elevated CXCL6 levels were positively correlated with tumor occurrence risk (OR = 1.5, 95% CI: 1.1–2.0), while MIP (OR = 0.5, 95% CI: 0.3–0.7), CCL4 (OR = 0.6, 95% CI: 0.4–0.8), and LIF-R (OR = 0.5, 95% CI: 0.3–0.8) were significantly associated with reduced tumor risk. Sensitivity analyses confirmed robust results with no significant horizontal pleiotropy. Meta-analysis showed CCL4 expression was reduced in most studies, while CXCL6 was significantly upregulated in tumor tissues. qRT-PCR validation demonstrated that all four inflammatory markers were significantly higher in tumor cell lines compared to normal cells ( P  < 0.01). Conclusion This study, which uses Mendelian randomization, suggests potential causal associations between inflammatory immune markers and the risk of malignant neoplasms of bone and articular cartilage.