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To elucidate the rules of particle crushing and loss of gravel soil subgrade filler during compaction and penetration, we performed compaction and permeability tests of gravel soil samples with different stone and moisture contents; moreover, crushing condition and fractal analysis were also performed on the test results. The results reveal that the best compaction effect is achieved when the stone content is 60% for gravel soil samples with hard rocks and fine particles as sandy soil and optimal moisture content is 8%. With the exception of the 70% stone content, the permeability coefficients of each ratio are similar, and the permeability coefficients all range from 10−2 to 10−3, indicating good permeability. The particle size distributions before and after compaction and crushing exhibit good fractal characteristics. The fractal dimension D is positively correlated with the dry density. Furthermore, the optimal fractal dimension D for crushing is 2.23–2.25 and 2.43–2.45 for coarse and fine particles, respectively. Relationships between the fractal dimension D and stone and moisture contents are established. Based on the relationship and optimal fractal dimension interval, the fractal dimension D can be predicted, and the compaction effect can be further estimated. There is also a good linear relationship between the crushing ratio Bg and fractal dimension D. When the stone content is no more than 60%, D of the coarse and fine particles increases with increasing Bg. The relationship between the fractal dimension D and penetration erosion shows that the smaller the difference between the fractal dimension before and after penetration, the smaller the effect of penetration on the erosion of gravel soil. The permeation erosion effect on D is highly affected by the stone content. When the stone content is 60%, the difference in fractal dimension decreases first and then increases as the moisture content increases, which is consistent with the changing trend of the permeability coefficient. Moreover, stone and moisture contents are two important factors that affect particle crushing and loss. However, stone content has a more significant impact on particle crushing and loss than moisture content. The fractal dimension D has a good correlation with the compaction and permeability test results of each proportion sample, which can better reflect the compaction and permeability characteristics of gravel soil samples. Thus, the results of this study can further reveal the compaction mechanism of gravel soil subgrade and provide a reference for subgrade construction.

Objective To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography （CBCT） images, and to compare and analyze the estimation results. Methods A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected. The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated. Three machine learning algorithms （K-nearest neighbor, ridge regression, and decision tree） and stepwise regression were used to establish four age estimation models. The coefficient of determination, mean error, root mean square error, mean square error and mean absolute error were computed and compared. A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed. Results The K-nearest neighbor model （R2=0.779） and the ridge regression model （R2=0.729） outperformed stepwise regression （R2=0.617）, while the decision tree model （R2=0.494） showed poor fitting. The correlation heatmap demonstrated a monotonically negative correlation between age and the parameters including pulp volume, the ratio of pulp volume to hard tissue volume, and the ratio of pulp volume to tooth volume. Conclusion Pulp volume and pulp volume proportion are closely related to age. The application of CBCT-based machine learning methods can provide more accurate age estimation results, which lays a foundation for further CBCT-based deep learning dental age estimation research.

Abstract Interpolation of probability distributions can be formulated as an optimal transport problem. Positive matrix, which can be viewed as the generalization of probability distribution to higher dimension, is used in quantum theory to describe the state of a quantum system. Here, a quantum‐inspired method for the interpolation of positive matrices is proposed. Particularly, this method employs the quantum state purification of the positive matrices in an extended space. Since pure state controllability can be easily achieved using open‐loop coherent control, the continuous interpolation of positive matrices is given as a completely positive map induced by simulating the optimal control for pure state transfer. The quantum‐inspired interpolation is shape‐preserving with applications to tensor field processing.

Objective(s): Human umbilical cord mesenchymal stem cells (HUC-MSCs) are pluripotent stem cells with anti-inflammatory and immunomodulatory properties used in the treatment of acute lung injury (ALI). However, the treatment of ALI using exosomes derived from HUC-MSCs (HUC-MSC-exos) primed with interferon-gamma (IFN-γ-exos) has not been described. This study investigated the effects of IFN-γ-exos on ALI.Materials and Methods: IFN-γ primed and unprimed HUC-MSC-exos (IFN-γ-exos and CON-exos, respectively) were extracted, identified, and traced. A549 cells and mice subjected to lipopolysaccharide (LPS)-induced inflammation were treated with IFN-γ-exos or CON-exos. Viability; interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and reactive oxygen species (ROS) levels; NF-κB p65, and NLRP3 expression and histology and lung injury scores were measured in cell, supernatant or lung tissue. Results: Indoleamine 2,3-dioxygenase (IDO) mRNA expression was elevated in HUC-MSCs primed with 5 ng/mL IFN-γ (P

Background/Purpose: Cutaneous squamous cell carcinoma (cSCC) is one of the most common malignancies worldwide. While several environmental risk factors for cSCC are well established, there is conflicting evidence on cigarette smoking (and its potential causal effect) and cSCC risk. Furthermore, it is unclear if these potential associations represent causal, modifiable risk factors for cSCC development. This study aims to assess the nature of the associations between cigarette smoking traits (smoking initiation, amount smoked, and lifetime smoking exposure) and cSCC risk using two-sample Mendelian randomization analyses. Methods: Genetic instruments, based on common genetic variants associated with cigarette smoking traits (P

The significant accumulation of snow and ice in the bogie region severely compromises operational quality and poses a safety hazard to high-speed trains. To enhance testing capabilities for assessing ice and snow accumulation within bogie regions, this study conducts numerical investigations into the influence of contraction section configuration and deflector layout density on wind-snow flow quality within an ice and snow wind tunnel. The predictive accuracy of the numerical method is comprehensively validated against wind-snow wind tunnel tests, involving a comparison of airflow velocity in the test section and snow accumulation thickness on the channel's floor. The results demonstrate that the coupled numerical method of Improved Delayed Detached Eddy Simulation (IDDES) and Discrete Phase Model (DPM) is a reliable tool for analyzing wind-snow flow characteristics within an ice and snow wind tunnel. Furthermore, compared to the vickers curve and bicubic curve, quintic curves applied to the contraction section consistently compress and accelerate airflow. This contributes to a more uniform flow characterized by lower stream-wise fluctuation levels, pitch angles, and yaw angles in the test section, thereby significantly enhancing the overall flow quality of wind and snow. Thus, the quintic curves or smoother curves are recommended for the design of the contraction section in ice and snow wind tunnels. Moreover, increasing the deflector number leads to a noticeable improvement in flow quality inside the test section, while resulting in increased snow accretion on the windward surfaces of deflectors. Hence, a medium-level deflector density is suggested for designing ice and snow wind tunnels to achieve a better balance between flow quality and the additional snow accretion inside the channel.

A silicon‐based room temperature (RT) continuous wave (CW) operation quantum well (QW) laser emitting at 850 nm is reported in this article. By applying the dislocation filter superlattice, the threading dislocation density of the GaAs pseudosubstrate on Si is reduced to 1.8 × 107 cm−2. The metal‐organic chemical vapor deposition‐grown laser structure with GaAs/GaAsP QW and InAlAs active region dislocation blocking layer are fabricated into broad‐stripe Fabry–Perot laser diodes. A typical threshold current and threshold current density of 286 mA and 715 Acm−2 are obtained with 2 mm cavity length and 20 um stripe width samples. A 94.2 mW single‐facet output power lasing around 854 nm and a 0.314 WA−1 slope efficiency is measured under RT CW operation. After a 10‐min aging process, the tested laser can operate stably under continuous operation conditions at RT and the lifetime can be approximated using an exponential fitting curve, indicating a good life reliability of this QW laser.

Chitosan is a biocompatible, non-toxic and renewable natural basic polysaccharide that can be cross-linked and reacted with Ce(IV) to form a physiologically active chitosan-Ce(IV) complex. To investigate this novel complex and its potential to hydrolyze phosphate ester bonds, chitosan-cerium complex microspheres resin (CS-CCMR) was prepared from chitosan and ceric ammonium nitrate by reversed-phase suspension cross-linking polymerization. CS-CCMR was characterized, its ability to hydrolyze disodium p-nitrobenzene phosphate (PNPP2Na) and organophosphorus pesticides was investigated, and the hydrolytic mechanism was explored. CS-CCMR was composed of dark yellow microspheres with smooth surfaces and dense pores. It was found that CS-CCMR contained 4.507 mg/g Ce(IV), indicating that coordination polymerization between Ce(IV) and chitosan was successful. The presence of Ce(IV) in CS-CCMR was confirmed by multiple analytical methods and it was found that coordination of Ce(IV) by chitosan was mediated by the nitrogen atom of the amino group and the oxygen atom of the hydroxyl group of chitosan. It was shown that CS-CCMR efficiently hydrolyzed the phosphate ester bonds of PNPP2Na and five organophosphorus pesticides. Hydrolysis of PNPP2Na is potentially accomplished by charge neutralization and nucleophilic substitution. The mechanism of parathion degradation by CS-CCMR involves modification of the nitro group to give aminoparathion, followed by cleavage of the P–O bond to generate diazinphos. Consequently, the novel chitosan-Ce(IV) complex exhibits great efficiency for hydrolysis of phosphate ester bonds and CS-CCMR is expected to be developed as an agent to reduce the possibility of contamination of fruit and vegetable drinks by organophosphorus pesticides.

BackgroundOsteosarcoma primarily affects children and adolescents, with current clinical treatments often resulting in poor prognosis. There has been growing evidence linking programmed cell death (PCD) to the occurrence and progression of tumors. This study aims to enhance the accuracy of OS prognosis assessment by identifying PCD-related prognostic risk genes, constructing a PCD-based OS prognostic risk model, and characterizing the function of genes within this model.MethodWe retrieved osteosarcoma patient samples from TARGET and GEO databases, and manually curated literature to summarize 15 forms of programmed cell death. We collated 1621 PCD genes from literature sources as well as databases such as KEGG and GSEA. To construct our model, we integrated ten machine learning methods including Enet, Ridge, RSF, CoxBoost, plsRcox, survivalSVM, Lasso, SuperPC, StepCox, and GBM. The optimal model was chosen based on the average C-index, and named Osteosarcoma Programmed Cell Death Score (OS-PCDS). To validate the predictive performance of our model across different datasets, we employed three independent GEO validation sets. Moreover, we assessed mRNA and protein expression levels of the genes included in our model, and investigated their impact on proliferation, migration, and apoptosis of osteosarcoma cells by gene knockdown experiments.ResultIn our extensive analysis, we identified 30 prognostic risk genes associated with programmed cell death (PCD) in osteosarcoma (OS). To assess the predictive power of these genes, we computed the C-index for various combinations. The model that employed the random survival forest (RSF) algorithm demonstrated superior predictive performance, significantly outperforming traditional approaches. This optimal model included five key genes: MTM1, MLH1, CLTCL1, EDIL3, and SQLE. To validate the relevance of these genes, we analyzed their mRNA and protein expression levels, revealing significant disparities between osteosarcoma cells and normal tissue cells. Specifically, the expression levels of these genes were markedly altered in OS cells, suggesting their critical role in tumor progression. Further functional validation was performed through gene knockdown experiments in U2OS cells. Knockdown of three of these genes—CLTCL1, EDIL3, and SQLE—resulted in substantial changes in proliferation rate, migration capacity, and apoptosis rate of osteosarcoma cells. These findings underscore the pivotal roles of these genes in the pathophysiology of osteosarcoma and highlight their potential as therapeutic targets.ConclusionThe five genes constituting the OS-PCDS model—CLTCL1, MTM1, MLH1, EDIL3, and SQLE—were found to significantly impact the proliferation, migration, and apoptosis of osteosarcoma cells, highlighting their potential as key prognostic markers and therapeutic targets. OS-PCDS enables accurate evaluation of the prognosis in patients with osteosarcoma.

The prevalence of calcific aortic valve disease (CAVD) remains substantial while there is currently no medical therapy available. Forkhead box O1 (FOXO1) is known to be involved in the pathogenesis of cardiovascular diseases, including vascular calcification and atherosclerosis; however, its specific role in calcific aortic valve disease remains to be elucidated. In this study, we identified FOXO1 significantly down-regulated in the aortic valve interstitial cells (VICs) of calcified aortic valves by investigating clinical specimens and GEO database analysis. FOXO1 silencing or inhibition promoted VICs osteogenic differentiation in vitro and aortic valve calcification in Apoe−/− mice, respectively. We identified that FOXO1 facilitated the ubiquitination and degradation of RUNX2, which process was mainly mediated by SMAD-specific E3 ubiquitin ligase 2 (SMURF2). Our discoveries unveil a heretofore unacknowledged mechanism involving the FOXO1/SMURF2/RUNX2 axis in CAVD, thereby proposing the potential therapeutic utility of FOXO1 or SMURF2 as viable strategies to impede the progression of CAVD.

Radiation therapy (RT) nowadays is a main treatment modality of cancer. To ensure the therapeutic efficacy of patients, accurate dose distribution is often required, which is a time-consuming and labor-intensive process. In addition, due to the differences in knowledge and experience among participants and diverse institutions, the predicted dose are often inconsistent. In last several decades, artificial intelligence (AI) has been applied in various aspects of RT, several products have been implemented in clinical practice and confirmed superiority. In this paper, we will review the research of AI in dose prediction, focusing on the progress in deep learning (DL).

Fugu (Takifugu rubripes) is a commercially important fish in aquaculture in China, Japan, and Korea. Male fugu are highly prized compared to females because the mature testes are regarded as a delicacy, thus all-male populations are preferred in aquaculture. However, the molecular mechanisms underlying sex differentiation in fugu remain largely unclear. Progestins, which are mediated by the progesterone receptor, can initiate spermatogenesis or ovarian differentiation in teleosts. To explore the effect of progestin blockage on fugu sex differentiation, the antiprogestin mifepristone (RU486) (500 μg/g of feed) was administrated to fugu larvae from 30 to 90 days after hatching (dah). Histological analysis revealed that RU486 treatment resulted in complete masculinization (100 %) of the XX fugu population at both 120 (RU486 withdrawal 30 days) and 150 (RU486 withdrawal 60 days) dah, and RU486-treated XX gonads developed testes-like structure. Gonadal transcriptomic analysis at 90 dah identified 3595 genes that were differentially expressed (DEGs) between the control and treated groups. Among them, the expression of steroid hormone biosynthesis-related genes (e.g., cyp11c1, cyp19a1a, and hsd17b1) and other key genes (e.g., gsdf, dmrt1, and foxl2) were altered in the gonads of RU486-treated groups. Most of the DEGs were enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to sex differentiation, such as neuroactive ligand-receptor interaction, ovarian steroidogenesis, and steroid hormone biosynthesis pathways. The expression of cyp19a1a, foxl2, cyp11c1, gsdf, dmrt3, and dmrt1 at 50, 70, and 90 dah was further assessed. The expression levels of gsdf, dmrt1, and cyp11c1 were increased, and the expression levels of cyp19a1a and foxl2 were decreased in the gonads of XX larvae in RU486 treated groups. These results demonstrated for the first time that RU486 induced masculinization in XX fugu and provided a theoretical basis for further studies of the regulatory role of progestins in sex differentiation in teleosts.

Objective:. To determine whether socio-demographic and preoperative clinical factors contribute to the percent total body weight loss (%TBWL) after bariatric surgery (BS). Background:. BS is the most effective long-term treatment for medically complicated obesity. More information is needed about the factors that contribute to postoperative %TBWL in large and ethnically diverse cohorts. Methods:. This retrospective study conducted in the Kaiser Permanente Northern California region included 7698 patients who underwent Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) between January 2009 and March 2015. Trajectory analyses were conducted from 5-year follow-up data to assign patients to “low,” “average,” or “high” postoperative %TBWL groups. We then evaluated whether age, sex, race/ethnicity, neighborhood deprivation index and preoperative body mass index (BMI)/weight loss, diabetes, hypertension, and sleep apnea contributed to postoperative %TBWL using logistic regression models. Results:. Of 7698 patients (83.2% women), 48.6% underwent a RYGB and 51.4% underwent a SG. Postoperative %TBWL trajectories over 5 years were obtained in 6229 (81%) of 7698 eligible patients. About 27.8% and 29.3% of patients followed the “low” postoperative %TBWL trajectory, for RYGB and SG, respectively. Men, older patients, and Asian, Black, and Hispanic/Latino patients were more likely to be classified in the low postoperative %TBWL group. Patients showing lower postoperative %TBWL had a lower preoperative BMI (but lost less weight before surgery) and were more likely to have preoperative comorbidities. Conclusions:. This study confirms and extends prior findings of the effects of several demographic and preoperative clinical factors on postoperative weight loss. Findings could improve the support of patients to achieve desired surgical outcomes.

The Basic Design course can help students understand design principles and visual art elements. It is a compulsory basic course for the department of art and design in many universities. In recent years, Augmented Reality (AR) technology has found its way into the field of design education and has become a popular textbook tool in teaching courses. There are not many pieces of research on the application of AR in design courses. Therefore, this study attempts to explore the factors that affect students' acceptance of AR textbooks in Basic Design course and their continuance intention for AR textbooks. This study first focused on students with experience in using AR textbooks. Open-ended questions were used to collect factors that allow AR textbooks to be used in the design curriculum; then questionnaire surveys and factor analysis were conducted and the research hypotheses are presented. Then, the research hypotheses were verified through reliability and validity as well as structural equation modeling. Three factors and 15 items for students to accept AR textbooks in the Basic Design course were summarized in the research results, including the three factors named "Visual Attraction", "Knowledge-ability", and "Situational Experience". The analysis of differences showed significant differences in gender among these three factors and no significant differences between grades and departments. Also, it was found from the analysis results of the structural equation model that the factors of "Visual Attraction" and "Knowledge-ability" both had a positive effect on the continuance intention, of which "Knowledge-ability" was the most important influencing factor. The results of this study can help the application and development of AR textbooks in the Basic Design course.

[Objective] Stressed by harsh environmental factors such as scarce precipitation and large evaporation, the desert Gobi is characterized as spare vegetation and severe soil and water losses. Therefore, exploring suitable soil improvement methods to improve soil water retention and water holding capacity is very important for the development of Gobi ecological agriculture. [Methods] The hydraulic-infiltration characteristics of the 3 groups of coconut coir-type ecological conservation substrates with better physicochemical properties (aeolian soil∶ coconut coir∶ organic fertilizer∶ artificial peat = 3.5∶3∶3∶1 or 3∶4∶3∶1 or 2∶5∶3∶1, i.e., T1, T2, T3) were tested compared to the control substrate with no coconut coir (aeolian soil∶ organic fertilizer∶ artificial peat = 7∶3∶1, T0). The relationship between matrix water and suction was determined by the centrifuge method, and then the hydraulic characteristics were explored. Then, the infiltration characteristics of the substrates were analyzed by the indoor infiltration test of the soil column with constant water head; and, based on the measured indicators, the proportion optimization was carried out by the coordinate comprehensive evaluation method. [Results] Compared with the T0 group, the field water retention capacity of the T1, T2 and T3 groups increased by 10.22%, 12.13% and 14.99%, and the total effective water content increased by 8.10%, 8.81% and 12.83%, respectively. In the stage of Pf=1.8~3.8 (logarithmic matrix suction), the average specific water capacity of each group showed a law of T3 > T2 > T1 > T0, and according to the gray correlation analysis (RGA) method, the infiltration capacity was ranked as T3 > T2 > T0 > T1. [Conclusion] The results showed that a suitable proportion of coconut coir mixing changes the effective water content and pore distribution ratio, which can significantly improve the water retention capacity of the substrate. From the perspective of physicochemical properties, hydraulic and infiltration characteristics, the T3 ratio is optimal.

AIM: To define the predictive factors of severe retinopathy of prematurity (ROP) and develop a nomogram for predicting severe ROP in southeast China. METHODS: Totally 554 infants diagnosed with ROP hospitalized in the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University and hospitalized in Taizhou Women and Children's Hospital were included. Clinical data and 43 candidate predictive factors of ROP infants were collected retrospectively. Logistic regression model was used to identify predictive factors of severe ROP and to propose a nomogram for individual risk prediction, which was compared with WINROP model and Digirop-Birth model. RESULTS: Infants from the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University (n=478) were randomly allocated into training (n=402) and internal validation group (n=76). Infants from Taizhou Women and Children's Hospital were set as external validation group (n=76). Severe ROP were found in 52 of 402 infants, 12 of 76 infants, and 7 of 76 infants in training group, internal validation group, and external validation group, respectively. Birth weight [odds ratio (OR), 0.997; 95% confidence interval (CI), 0.996-0.999; P

A precise dynamic model and exact statistical information are required in a standard Kalman filter to ensure optimal performance. Without these, degraded performance may be obtained. In this paper, an improved adaptive estimation approach for uncertain models is proposed, and the fading matrix is adaptively estimated according to the observability of the system state. Meanwhile, a sequential way to calculate the covariance matrix of the measurement noises is performed, thereby strengthening its ability to resist disturbances further. The proposed algorithm was implemented in practical data processing of GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System) integrated systems. The measurement sensors were equipped on aircraft and land vehicles to test their stability and robustness. Comparisons with existing fading filters and conventional nonlinear Kalman filters show that the proposed algorithm controls model errors, weakens influences of constantly changing and abrupt outliers, achieves relatively high precision, and restrains filter divergence effectively.

Abstract Basal cell carcinoma (BCC) is one of the most common malignancies worldwide, yet its genetic determinants are incompletely defined. We perform a European ancestry genome-wide association (GWA) meta-analysis and a Hispanic/Latino ancestry GWA meta-analysis and meta-analyze both in a multi-ancestry GWAS meta-analysis of BCC, totaling 50,531 BCC cases and 762,234 controls from four cohorts (GERA, Mass-General Brigham Biobank, UK Biobank, and 23andMe research cohort). Here we identify 122 BCC-associated loci, of which 36 were novel, and subsequently fine-mapped these associations. We also identify an association of the well-known pigment gene SLC45A2 as well as associations at RCC2 and CLPTM1L with BCC in Hispanic/Latinos. We examine these BCC loci for association with cutaneous squamous cell carcinoma (cSCC) in 16,407 SCC cases and 762,486 controls of European ancestry, and 33 SNPs show evidence of association. Our study findings provide important insights into the genetic basis of BCC and cSCC susceptibility.

Abstract Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling. Here, we focused on the role of Semaphorin 3A (Sema3A), expressed by sensory nerves, in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement (OTM) model. Firstly, bone formation was activated after the 3rd day of OTM, coinciding with a decrease in sensory nerves and an increase in pain threshold. Sema3A, rather than nerve growth factor (NGF), highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM. Moreover, in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells (hPDLCs) within 24 hours. Furthermore, exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload. Mechanistically, Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway, maintaining mitochondrial dynamics as mitochondrial fusion. Therefore, Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation, both as a pain-sensitive analgesic and a positive regulator for bone formation.

Abstract Objective The sleep of healthcare students is worth discovering. Mental health and self-rated health are thought to be associated with sleep quality. As such, valid instruments to assess sleep quality in healthcare students are crucial and irreplaceable. This study aimed to investigate the measurement properties of the Sleep Quality Questionnaire (SQQ) for Chinese healthcare students. Methods Two longitudinal assessments were undertaken among healthcare students, with a total of 595, between December 2020 and January 2021. Measures include the Chinese version of the SQQ, Patient Health Questionnaire-4 (PHQ-4), Self-Rated Health Questionnaire (SRHQ), and sociodemographic questionnaire. Structural validity through confirmatory factor analysis (CFA) was conducted to examine factor structure of the SQQ. T-tests and ANOVAs were used to examine sociodemographic differences in sleep quality scores. Multi Group CFA and longitudinal CFA were respectively used to assess cross-sectional invariance and longitudinal invariance across two-time interval, i.e., cross-cultural validity. Construct validity, internal consistency, and test–retest reliability were correspondingly examined via Spearman correlation, Cronbach’s alpha and McDonald’s omega, and intraclass correlation coefficient. Multiple linear regression analysis was performed to examine incremental validity of the SQQ based on the PHQ-4 and SRHQ as indicators of the criterion variables. Results CFA results suggested that the two-factor model of the SQQ-9 (item 2 excluded) had the best fit. The SQQ-9 scores differed significantly by age, grade, academic stage, hobby, stress coping strategy, anxiety, depression, and self-rated health subgroups. Measurement invariance was supported in terms of aforesaid subgroups and across two time intervals. In correlation and regression analyses, anxiety, depression, and self-rated health were moderately strong predictors of sleep quality. The SQQ-9 had good internal consistency and test–retest reliability. Conclusion Good measurement properties suggest that the SQQ is a promising and practical measurement instrument for assessing sleep quality of Chinese healthcare students.

Tumor vaccine is a promising strategy for cancer immunotherapy by introducing tumor antigens into the body to activate specific anti-tumor immune responses. Along with the technological breakthroughs in genetic engineering and delivery systems, messenger ribonucleic acid (mRNA) technology has achieved unprecedented development and application over the last few years, especially the emergency use authorizations of two mRNA vaccines during the COVID-19 pandemic, which has saved countless lives and makes the world witness the powerful efficacy of mRNA technology in vaccines. However, unlike infectious disease vaccines, which mainly induce humoral immunity, tumor vaccines also need to activate potent cellular immunity to control tumor growth, which creates a higher demand for mRNA delivery to the lymphatic organs and antigen-presenting cells (APCs). Here we review the existing bottlenecks of mRNA tumor vaccines and advanced nano-based strategies to overcome those challenges, as well as future considerations of mRNA tumor vaccines and their delivery systems.