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Nelarabine is a purine nucleoside analogue prodrug approved for the treatment of relapsed and refractory T-cell acute lymphoblastic leukemia (R/R T-ALL) and lymphoblastic lymphoma (T-LBL). Although effective in R/R T-ALL, significant neurotoxicity is dose-limiting and such neurotoxicity associated with nucleoside analogues can be related to dosing schedule.The authors conducted a phase 1 study to evaluate the pharmacokinetics and toxicity of nelarabine administered as a continuous infusion (CI) for 5 days (120 hours), rather than the standard, short-infusion approach.Twenty-nine patients with R/R T-ALL/LBL or T-cell prolymphocytic leukemia (T-PLL) were treated, with escalating doses of nelarabine from 100 to 800 mg/mPreliminary evaluation of continuous infusion schedule of nelarabine suggests that the safety profile is acceptable for this patient population, with clinical activity observed even at low doses and could broaden the use of nelarabine both as single agent and in combinations by potentially mitigating the risk of central nervous system toxicities.

To establish the factor structure of the Emotion Regulation Questionnaire for Children and Adolescents (ERQ-CA) in Chinese and American adolescent samples; to assess measurement invariance of the ERQ-CA in Chinese and American adolescent samples and latent means across early adolescents from two diverse cultural settings. The ERQ-CA was administered to 1221 Chinese adolescents (49.3% males) and 1148 American adolescents (50.1% males), and multi-group confirmatory factor analysis was performed to evaluate measurement invariance.(1) Multi-group confirmatory factor analysis of the ERQ-CA demonstrated full configural invariance, full metric invariance, partial scalar invariance, and partial strict invariance. (2) The latent variable mean comparisons revealed significant differences between the two samples; specifically, Chinese adolescents’ mean scores on the latent variables of cognitive reappraisal (CR) and expressive suppression (ES) were significantly higher than American adolescents’ scores. The findings demonstrated that the ERQ-CA displays appropriate measurement invariance across Chinese and America adolescents and that Chinese adolescents reported higher scores on CR and ES.

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal malignancies worldwide. Recently, our group identified purine-rich element binding protein alpha (PURα), a single-stranded DNA/RNA-binding protein, to be significantly associated with the progression of ESCC. Additional immunofluorescence staining demonstrated that PURα forms cytoplasmic stress granules to suppress mRNA translation initiation. The expression level of cytoplasmic PURα in ESCC tumor tissues was significantly higher than that in adjacent epithelia and correlated with a worse patient survival rate by immunohistochemistry. Functionally, PURα strongly preferred to bind to UG-/U-rich motifs and mRNA 3´UTR by CLIP-seq analysis. Moreover, PURα knockout significantly increased the protein level of insulin-like growth factor binding protein 3 (IGFBP3). In addition, it was further demonstrated that PURα-interacting proteins are remarkably associated with translation initiation factors and ribosome-related proteins and that PURα regulates protein expression by interacting with translation initiation factors, such as PABPC1, eIF3B and eIF3F, in an RNA-independent manner, while the interaction with ribosome-related proteins is significantly dependent on RNA. Specifically, PURα was shown to interact with the mRNA 3´UTR of IGFBP3 and inhibit its expression by suppressing mRNA translation initiation. Together, this study identifies cytoplasmic PURα as a modulator of IGFBP3, which could be a promising therapeutic target for ESCC treatment.

The purpose of the present study was to identify the patterns of Internet addiction in early adolescents and their associated protective factors in order to prevent and/or ameliorate internet addiction as early as possible. A 2-year longitudinal study was conducted among 621 Chinese early adolescents. Latent class and latent transition analyses were used to identify classes of the development of internet addiction. Three latent classes were identified, including a “Non-Internet Addiction Group” (43%), “Low Internet Addiction Group” (43%) and “High Internet Addiction Group” (14%). A Latent Transition Analysis of Adolescents in the Non-Internet Addiction Group and Low Internet Addiction Group demonstrated relative stability in class membership, whereas adolescents in the High Internet Addiction Group tended to change to the Low Internet Addiction Group. Results of multinomial logistic regression and latent transition analyses revealed that low impulsivity, high family care, and high student engagement in school all contributed to membership in the latent classes of internet use and transitions. Implications of these results for prevention and intervention and for future research are discussed.

Stroke is the most common cause of human death and functional disability, resulting in more than 5 million deaths worldwide each year. Bone marrow mesenchymal stem cells (BMSCs) are a kind of stem cell that are able to self-renew and differentiate into many types of tissues. Therefore, BMSCs have the potential to replace damaged neurons and promote the reconstruction of nerve conduction pathways and connective tissue. However, it remains unknown whether transplanted BMSCs promote angiogenesis or improve the tissue microenvironment directly or indirectly through paracrine interactions. This study aimed to determine the therapeutic effect of BMSCs on ischemic stroke with hypertension in a rodent model and to explore the possible mechanisms underlying any benefits.Middle cerebral artery occlusion was used to establish the experimental stroke model. The area of cerebral infarction, expression of vascular endothelial growth factor (VEGF) and glial cell line-derived neurotrophic factor (GDNF), and increment of astrocyte were measured by TTC staining, western blot, real-time quantitative polymerase chain reaction (RT-qPCR) and immunocytochemistry. The results showed a smaller area of cerebral infarction and improved neurological function scores in animals treated with BMSCs compared to controls. The results of RT-qPCR and western blot assays showed higher expression of VEGF and GDNF in BMSC-treated animals compared with controls. Our study also showed that one round of BMSCs transplantation significantly promoted the proliferation of subventricular zone and cortical cells, especially astrocytes, on the ischemic side following cerebral ischemia.Above findings support that BMSCs have therapeutic effects for ischemic stroke complicated with hypertension, which may occur via up-regulated expression of VEGF and GDNF and reduction of neuronal apoptosis, thereby promoting the recovery of nerve function.

Intrusion detection is a critical component of network security. However, intrusion detection cannot play a very good role in the face of APT and 0 day. It needs to combine intrusion prevention, deception defense, and other technologies to ensure network security. Intrusion prediction is an important part of intrusion prevention and deception defense. Only by predicting the next possible attack can we prevent the corresponding intrusion or cheat adversary more efficiently. However, the current research on intrusion prediction has not received much attention. Most of the existing intrusion prediction research focuses on the prediction of security situation, specific security events, system calls, etc., having limitation in applicability and sequence dependency. In order to supplement this part of research, this paper reports the prediction of network penetration intrusion sequence for the first time. By introducing the ATT&CK framework, this paper builds a dictionary for the penetration intrusion types and builds three different seq2seq models. The experiment runs on the public and generated sequence data based on real APT events and adversary groups resulting that the model can predict future penetration intrusion sequence with an accuracy of up to 0.90.

The HIV-1 fusion peptide has been identified as a site for elicitation of broadly neutralizing antibodies, with prior studies demonstrating that priming with fusion peptide-based immunogens and boosting with soluble envelope (Env) trimers can elicit cross-clade HIV-1-neutralizing responses. To improve the neutralizing breadth and potency of fusion peptide-directed responses, we evaluated vaccine regimens that incorporated diverse fusion peptide-conjugates and Env trimers with variation in fusion peptide length and sequence.

With the increase of the housing population, it is very important for renters to find credible housing information through rental platforms. However, due to the imperfection of relevant laws and insufficient supervision of the housing rental market, problems have emerged one after another. In this article, we propose a housing rental scheme based on redactable blockchain, introducing a trusted third party to verify the homeowner rental listings, and fundamentally preventing false listings from flowing into the housing rental market. Specifically, a trusted third party similar to the housing authority will issue a verifiable claim for the homeowners listing, and then the accounting node of the consortium blockchain will publish the verified listing information on the blockchain so as tenants to make inquiries according to their needs. At the same time, we use the new chameleon hash to build a redactable blockchain. After the homeowner proposes to change the housing price or housing information, the content of the historical block is modified as required. Thus, to a certain extent, the changes in housing prices can be monitored to curb chaos in the housing rental market.

Background: The optimal body mass index (BMI) for cardiovascular disease (CVD) prevention in older adults remains uncertain. We aimed to evaluate the relationship between BMI and CVD mortality and identify the nadirs for CVD mortality in older (≥65 years) and younger ( Methods: We used data from the 1997 to 2018 National Health Interview Survey, linked to the National Death Index (NDI). We included adults aged 18 years and older with BMI and NDI follow-up data available. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for the association between BMI and CVD mortality. Fully adjusted models were stratified by age and controlled for baseline age, sex, race, income, education, marital status, diabetes, cancer, general health, physical activity, smoking, and alcohol status. Results: Among 490,037 adults, the mean(±SD) age was 47(18) years; 55% were female. During a median follow-up period of 11 years, 19,194 CVD deaths occurred. The associations between BMI and CVD mortality were J-shaped in adults aged ≥ 65 years and < 65 years. The CVD mortality was minimized at a BMI of 26 kg/m 2 in adults aged ≥ 65 years and 22 kg/m 2 in those aged < 65 years. In adults aged ≥ 65 years, being overweight was associated with a lower risk of CVD mortality (HR 0.93, [95% CI, 0.89-0.96]); having level I obesity (0.90 [0.94-1.05]) and level II obesity (1.06 [0.97-1.16]) did not increase the risk of CVD mortality; and level III obesity was associated with increased risk of CVD mortality in comparison with individuals who had a normal BMI ( Figure ). In individuals aged < 65 years, being overweight, level I, II, and III obesity were associated with a progressively higher risk of CVD mortality. Conclusion: Overweight and level I obesity seem to be protective against CVD mortality in older adults. This obesity paradox suggests that the optimal BMI might be sensitive to age. Thus, weight management should be individualized.

Background As a common tumor with high incidence, osteosarcoma possesses extremely poor prognosis and high mortality. Improving the survival of osteosarcoma patients is still a great challenge due to the precipice of advancement in treatment. This study aims to develop a multifunctional nanoplatform based on the synergistic effect of NIR-II photothermal therapy (PTT) and gene therapy for efficient treatment of osteosarcoma. Methods In this study, a combination strategy of gene therapy and photothermal therapy (PTT) is developed for efficient treatment of osteosarcoma. Two-dimensional (2D) FePS3 nanosheets are synthesized and functionalized by poly-L-lysine-PEG-folic acid (PPF) to fabricate a multifunctional nanoplatform (FePS@PPF) for further loading microRNAs inhibitor, miR-19a inhibitor (anti-miR-19a). Results The photothermal conversion efficiency of FePS@PPF is up to 47.1% under irradiation by 1064 nm laser. In vitro study shows that anti-miR-19a can be efficiently internalized into osteosarcoma cells through the protection and delivery of FePS@PPF nanao carrier, which induces up-regulation of PTEN gene and down-regulation p-AKT gene. After intravenous injection, the FePS@PPF nanoplatform specifically accumulates to tumor site of osteosarcoma-bearing mice. The in vitro and in vivo investigations reveal that the combined PTT-gene therapy displays most significant tumor ablation compared with monotherapy. More importantly, the good biodegradability promotes FePS@PPF to be cleared from body avoiding potential toxicity of long-term retention. Conclusion Our work not only develops a combined strategy of NIR-II PTT and gene therapy mediated by anti-miR-19a/FePS@PPF but also provides insights into the design and applications of other nanotherapeutic platforms.

At present, deep neural networks have been widely used in various fields, but their vulnerability requires attention. The adversarial attack aims to mislead the model by generating imperceptible perturbations on the source model, and although white-box attacks have achieved good success rates, existing adversarial samples exhibit weak migration in the black-box case, especially on some adversarially trained defense models. Previous work for gradient-based optimization either optimizes the image before iteration or optimizes the gradient during iteration, so it results in the generated adversarial samples overfitting the source model and exhibiting poor mobility to the adversarially trained model. To solve these problems, we propose the dual-sample variance aggregation with feature heterogeneity attack; our method is optimized before and during iterations to produce adversarial samples with better transferability. In addition, our method can be integrated with various input transformations. A large amount of experimental data demonstrate the effectiveness of the proposed method, which improves the attack success rate by 5.9% for the normally trained model and 11.5% for the adversarially trained model compared with the current state-of-the-art migration-enhancing attack methods.

Big data as a derivative of information technology facilitates the birth of data trading. The technology surrounding the business value of big data has come into focus. However, most of the current research focuses on improving the performance of big data analytics algorithms. Data pricing is still one of the main issues in data trading. Therefore, we aim to tackle the problem of evaluating the utility of data in the big data trading market and the problem of maximizing the profits of the various roles involved in data trading. To this end, we propose a Multidimensional Data Utility Evaluation (MDDUE) method through three data quality dimensions, namely, data size, availability, and completeness. Next, we propose a big data trading market model including data providers, service providers, and service users. An optimal data-pricing scheme based on a three-party Stackelberg game is proposed to maximize the participants’ profits. Finally, a machine learning model is used to verify the rationality and validity of the MDDUE. The results show that MDDUE can evaluate the utility of data more accurately than previous work. The existence and uniqueness of the Nash equilibrium are demonstrated through numerical experiments.