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Abstract Background Kinesiophobia, an irrational fear-avoidance behaviour, can significantly impact the quality of life and prognosis of peritoneal dialysis patients. This study aimed to assess the prevalence of kinesiophobia in patients undergoing peritoneal dialysis and to analyse its influencing factors. Methods A total of 291 patients who visited the outpatient and ward of peritoneal dialysis in 7 tertiary hospitals in Jiangsu Province from December 2023 to March 2024 were selected as research subjects via the convenience sampling method. A cross-sectional survey was conducted using a general data questionnaire, the Tampa Kinesiophobia-11 Scale, the Chinese Version of the Multidimensional Fatigue Symptom Scale, and the Simplified Coping Style Questionnaire. Results The score obtained using the Tampa Scale for kinesiophobia in patients with peritoneal dialysis was 22.44 ± 7.46, with a prevalence rate of 69.1%. Binary logistic regression analysis revealed that no complications, daily exercise before illness, and positive coping styles were protective factors (p

Abstract Bearing‐fault diagnosis in rotating machinery is essential for ensuring the safety and reliability of mechanical systems. However, under complicated working conditions, the number of normal mechanical equipment samples can far exceed the number of faulty ones. When the data are so imbalanced, data fault diagnosis cannot be easily conducted using conventional deep learning methods. This study proposes a fault diagnosis method based on a dual‐branch interactive fusion network, which improves the accuracy and stability of bearing‐fault diagnosis. First, a dual‐branch feature representation network comprising an iterative attention‐feature fusion residual neural network and a long short‐term memory network is designed for extracting different modal features. Meanwhile, intermodal fusion of the extracted features is performed through multilayer perception. Based on the cost‐sensitive regularization loss, a new joint loss function is then designed for network training. Finally, the effectiveness of the proposed method is verified through comparative experiments, visualization analyses, ablation experiments, and generalization performance experiments.

Abstract Infectious diseases usually originate from a specific location within a city. Due to the heterogenous distribution of population and public facilities, and the structural heterogeneity of human mobility network embedded in space, infectious diseases break out at different locations would cause different transmission risk and control difficulty. This study aims to investigate the impact of initial outbreak locations on the risk of spatiotemporal transmission and reveal the driving force behind high-risk outbreak locations. First, we built a SLIR (susceptible-latent-infectious-removed)-based age-stratified meta-population model, integrating mobile phone location data, to simulate the spreading process of an infectious disease across fine-grained intra-urban regions (i.e., 649 communities of Shenzhen City, China). Based on the simulation model, we evaluated the transmission risk caused by different initial outbreak locations by proposing three indexes including the number of infected cases (CaseNum), the number of affected regions (RegionNum), and the spatial diffusion range (SpatialRange). Finally, we investigated the contribution of different influential factors to the transmission risk via machine learning models. Results indicate that different initial outbreak locations would cause similar CaseNum but different RegionNum and SpatialRange. To avoid the epidemic spread quickly to more regions, it is necessary to prevent epidemic breaking out in locations with high population-mobility flow density. While to avoid epidemic spread to larger spatial range, remote regions with long daily trip distance of residents need attention. Those findings can help understand the transmission risk and driving force of initial outbreak locations within cities and make precise prevention and control strategies in advance.

Low high-density lipoprotein cholesterol (HDL-C) is a risk factor for cardiovascular disease. Very low HDL-C levels (less than 20 mg/dL), however, were uncommonly seen and can be due to genetic defects involving the metabolic pathway of high-density lipoprotein (HDL). We encountered a 50-year-old Chinese man who was only noticed to have extremely low HDL-C levels after surviving recurrent episodes of myocardial infarction. Further workup revealed the undetectable level of apolipoprotein A-I, the absence of HDL on gel electrophoresis, and a novel heterozygous splicing variant in the ABCA1 gene, which was predicted to be pathogenic by in silico analysis. To the best of our knowledge, this is the first reported Hong Kong Chinese with ABCA1 deficiency and probable Tangier disease. The association of ABCA1 deficiency/Tangier disease and accelerated atherosclerosis is discussed.

Characterization of defects in large 3D printed metals is critical but challenging. This study reports on the X-ray micro-computed tomography (micro-CT) examination of porosities in large-volume 3D-printed and heat-treated titanium (Ti–6Al–4V) alloys, together with their tensile properties and failure mechanisms. Titanium alloy powders were analyzed using scanning electron microscopy (SEM). Laser powder bed fusion (L-PBF) was used to print titanium alloy specimens vertically and horizontally, followed by stress-relieved heat treatment. Micro-CT imaging was performed on printed specimens of 10 × 20 mm3 (diameter × length) to determine their porosities, pore locations and size distributions using an industrial micro-CT system and relevant imaging software. Tensile testing of the processed specimens was conducted to determine their mechanical properties. Optical microscopy and SEM were used to examine the tension-induced failure mechanisms. The results show that porosities, pore sizes and locations were influenced by the build direction, resulting in different mechanical properties. Horizontal printing achieved higher tensile modulus, strength, ductility, resilience and toughness than vertical printing. Heat treatment did not change porosities in horizontally built specimens, but slightly reduced porosities for vertically built ones by 10%. This led to most mechanical properties nearly unchanged for the horizontally printed specimens but remarkably increased yield and tensile strength, and resilience, for the vertically printed ones. All tension-induced fractured surfaces contained pores, possible indicators of failure origins, which should be diminished in advanced processes for higher mechanical reliability.

BackgroundEndometriosis is a multifaceted disorder with genetic, immune, inflammatory, and multifactorial origins. Vitamin B6 serves as a pivotal coenzyme in various metabolic pathways involving lipids, hemes, nucleic acids, proteins, and carbohydrates. Dysregulation or deficiency of vitamin B6 can perturb human physiology. However, the relationship between dietary vitamin B6 and endometriosis remains elusive. This study aims to explore how dietary intake of vitamin B6 is associated with the risk of endometriosis.MethodsUsing cross-sectional data from the National Health and Nutrition Examination Survey, we analyzed information from American women aged 20–54 years between 1999 and 2006. After adjusting for relevant covariates, multivariable logistic regression analysis was employed to evaluate correlations.ResultsA total of 4,453 women were included in the study. The multiple linear regression model revealed a positive association between dietary vitamin B6 intake and the risk of endometriosis, even after controlling for confounding variables. Compared to individuals with lower vitamin B6 consumption (Q1: 1.90 mg/day) were 1.22 (95% CI: 0.88–1.69, p = 0.23), 1.22 (95% CI: 0.86–1.73, p = 0. 279), and 1.51 (95% CI, 1.01–2. 24, p = 0.04), respectively.ConclusionOur findings suggest a positive correlation between endometriosis and dietary vitamin B6 intake. Further investigations are imperative to establish a causal relationship between dietary vitamin B6 intake and endometriosis.

Abstract Messenger RNA (mRNA) therapeutics delivered via lipid nanoparticles hold the potential to treat metabolic diseases caused by protein deficiency, including propionic acidemia (PA), methylmalonic acidemia (MMA), and phenylketonuria (PKU). Herein we report results from multiple independent preclinical studies of mRNA-3927 (an investigational treatment for PA), mRNA-3705 (an investigational treatment for MMA), and mRNA-3210 (an investigational treatment for PKU) in murine models of each disease. All 3 mRNA therapeutics exhibited pharmacokinetic/pharmacodynamic (PK/PD) responses in their respective murine model by driving mRNA, protein, and/or protein activity responses, as well as by decreasing levels of the relevant biomarker(s) when compared to control-treated animals. These preclinical data were then used to develop translational PK/PD models, which were scaled allometrically to humans to predict starting doses for first-in-human clinical studies for each disease. The predicted first-in-human doses for mRNA-3927, mRNA-3705, and mRNA-3210 were determined to be 0.3, 0.1, and 0.4 mg/kg, respectively.

AbstractContext Sanguinarine (SAG) is the most abundant constituent of Macleaya cordata (Willd.) R. Br. (Popaceae). SAG has shown antimammary and colorectal metastatic effects in mice in vivo, suggesting its potential for cancer chemotherapy.Objective To determine the antimetastatic effect and underlying molecular mechanisms of SAG on melanoma.Materials and methods CCK8 assay was used to determine the inhibition of SAG on the proliferation of A375 and A2058 cells. Network pharmacology analysis was applied to construct a compound-target network and select potential therapeutic targets of SAG against melanoma. Molecular docking simulation was conducted for further analysis of the selected targets. In vitro migration/invasion/western blot assay with 1, 1.5, 2 μM SAG and in vivo effect of 2, 4, 8 mg/kg SAG in xenotransplantation model in nude mice.Results The key targets of SAG treatment for melanoma were mainly enriched in PI3K-AKT pathway, and the binding energy of SAG to PI3K, AKT, and mTOR were −6.33, −6.31, and −6.07 kcal/mol, respectively. SAG treatment inhibited the proliferation, migration, and invasion ability of A375 and A2058 cells (p

For drone-based detection tasks, accurately identifying small-scale targets like people, bicycles, and pedestrians remains a key challenge. In this paper, we propose DV-DETR, an improved detection model based on the Real-Time Detection Transformer (RT-DETR), specifically optimized for small target detection in high-density scenes. To achieve this, we introduce three main enhancements: (1) ResNet18 as the backbone network to improve feature extraction and reduce model complexity; (2) the integration of recalibration attention units and deformable attention mechanisms in the neck network to enhance multi-scale feature fusion and improve localization accuracy; and (3) the use of the Focaler-IoU loss function to better handle the imbalanced distribution of target scales and focus on challenging samples. Experimental results on the VisDrone2019 dataset show that DV-DETR achieves an mAP@0.5 of 50.1%, a 1.7% improvement over the baseline model, while increasing detection speed from 75 FPS to 90 FPS, meeting real-time processing requirements. These improvements not only enhance the model’s accuracy and efficiency but also provide practical significance in complex, high-density urban environments, supporting real-world applications in UAV-based surveillance and monitoring tasks.

Systematically predicting carbon emissions in the building sector is crucial for formulating effective policies and plans. However, the timing and potential peak emissions from urban buildings remain unclear. This research integrates socio-economic, urban planning, building technology, and energy consumption factors to develop a LEAP-SD model using Shenzhen as a case study. The model considers the interrelationship between socio-economic development and energy consumption, providing more realistic scenario simulations to predict changes in carbon emissions within the urban building sector. The study investigates potential emission peaks and peak times of buildings under different population and building area development scenarios. The results indicate that achieving carbon peaking by 2030 is challenging under a business as usual (BAU) scenario. However, a 10% greater reduction in energy intensity compared to BAU could result in peaking around 2030. The simulation analysis highlights the significant impact of factors such as population growth rate, per capita residential building area, and energy consumption per unit building area and the need for a comprehensive analysis. It provides more realistic scenario simulations that not only enhance theories and models for predicting carbon emissions but also offer valuable insights for policymakers in establishing effective reduction targets and strategies.

Background: Chemotherapy resistance is an obstacle to promoting the survival of patients with hepatocellular carcinoma (HCC). Thus, finding promising therapeutic targets to enhance HCC chemotherapy is necessary. Methods: Signal sequence receptor subunit (SSR2) expression analysis was performed using quantitative real time polymerase chain reaction (qPCR) and Western blotting assays. Colony formation, apoptosis, anchorage-independent growth assay, and in vivo animal models were used to investigate the effect of SSR2 expression on the resistance of HCC cells to Cisplatin (DDP). Western blotting and luciferase reporter gene techniques were used to explore the molecular mechanism of SSR2 on the resistance of HCC cells to DDP. Results: We found that the SSR2 is upregulated in HCC and associated with poor survival. Further analysis showed that the downregulation of SSR2 increased the sensitivity of HCC to DDP. Mechanically, SSR2 inhibited the Yes-associated protein (YAP) phosphorylation and promoted the transcription of Hippo signaling downstream genes. Finally, the Hippo pathway inhibitor can suppress colony formation and tumorigenesis arising from SSR2 upregulation. Conclusions: Our study shows that SSR2 is important in HCC progression via the Hippo pathway. Thus, targeting the SSR2/Hippo axis might be a potential strategy for overcoming HCC resistance to DDP.

Objective: To study the predictive value of a positive anti-nuclear antibody (ANA) for a rheumatological diagnosis in an outpatient setting. Methods: Individuals who were referred to the rheumatology outpatient clinics because of a positive ANA between July 2014 and June 2015 were retrospectively reviewed. Presenting symptoms in addition to a positive ANA and whether a final rheumatological diagnosis was made were recorded. The positive predictive value of a positive ANA and its titer for a rheumatological diagnosis, with and without accompanying symptoms was evaluated. Results: A total of 230 patients were included (82% women, age 47.7 ± 14.1 years [range 18-84]). Family medicine and the general outpatient clinic were the main sources of referral (32.2%), followed by ophthalmology (13.0%) and otorhinolaryngology (11.7%). A final rheumatological diagnosis was made in 54 (23.5%) patients, with rheumatoid arthritis being the commonest diagnosis (40.7%). In the absence of any associated symptoms, the predictive value of a positive ANA was 0%. The presence of Raynaud’s phenomenon (100%), joint swelling (59.5%), and joint stiffness (48.9%) predicted a better final rheumatological diagnosis along with a positive ANA. ANA titers of 1:80 or less had a low sensitivity for rheumatic diseases. A receiver operating characteristic (ROC) curve analysis showed that an ANA titer of [Formula: see text]1:128 best predicted a rheumatological diagnosis (AUC 0.78 [0.71–0.85]; sensitivity 0.78; specificity 0.64). Conclusions: To improve the prediction for a rheumatological diagnosis, referral for a positive ANA test should be more appropriately done with compatible symptoms.

Agent-based models have gained traction in exploring the intricate processes governing the spread of infectious diseases, particularly due to their proficiency in capturing nonlinear interaction dynamics. The fidelity of agent-based models in replicating real-world epidemic scenarios hinges on the accurate portrayal of both population-wide and individual-level interactions. In situations where comprehensive population data are lacking, synthetic populations serve as a vital input to agent-based models, approximating real-world demographic structures. While some current population synthesizers consider the structural relationships among agents from the same household, there remains room for refinement in this domain, which could potentially introduce biases in subsequent disease transmission simulations. In response, this study unveils a novel methodology for generating synthetic populations tailored for infectious disease transmission simulations. By integrating insights from microsample-derived household structures, we employ a heuristic combinatorial optimizer to recalibrate these structures, subsequently yielding synthetic populations that faithfully represent agent structural relationships. Implementing this technique, we successfully generated a spatially-explicit synthetic population encompassing over 17 million agents for Shenzhen, China. The findings affirm the method's efficacy in delineating the inherent statistical structural relationship patterns, aligning well with demographic benchmarks at both city and subzone tiers. Moreover, when assessed against a stochastic agent-based Susceptible-Exposed-Infectious-Recovered model, our results pinpointed that variations in population synthesizers can notably alter epidemic projections, influencing both the peak incidence rate and its onset.

Background: Hepatocellular carcinoma (HCC) is a common clinical malignant tumor of the digestive system. Hu-Qi-Zheng-Xiao (HQZX) decoction has been clinically found to prolong the survival of patients with hepatocellular carcinoma and improve the quality of patients’ survival, but its antitumor biological mechanism is still unclear. Methods: A nude mouse hollow fiber hepatocellular carcinoma model was constructed to analyze the in vivo efficacy of HQZX decoction against 7 different hepatocellular carcinoma cells. The subcutaneous graft tumor model was again validated. In vitro, the effect of HQZX decoction on the growth and metastasis of the cell line with the highest growth inhibition was evaluated. The cell line with the best efficacy response screened was again used to construct a hollow fiber hepatocellular carcinoma model and hollow fiber conduit cells were extracted to detect the expression of HIF-1α, VEGF, EMT-related molecules, LCSCs-related molecules, and to observe the density of the subcutaneous vascular network of hollow fiber conduits. The liver metastasis model of splenic injection was constructed to observe the effect of HQZX decoction on tumor metastasis. Results: The hollow fiber hepatocellular carcinoma model was evaluated for the efficacy of HQZX decoction, and it was found to have the highest growth inhibition of LM3-luc cells. In vitro, the CCK8 assay revealed that HQZX decoction could inhibit tumor migration and invasion and promote apoptosis. In addition, the mechanism study of extracting cells from hollow fiber tubes found that HQZX decoction could inhibit metastasis-associated HIF-1α, VEGF, EMT-related molecules, and LCSCs-related molecules expression. capillary network around subcutaneous fiber tubes was reduced in the HQZX decoction gavage group of mice. It inhibited tumor metastasis in nude mice. Conclusions: HQZX decoction inhibited the growth of a variety of hepatocellular carcinoma cells. HQZX decoction suppressed the expression of metastasis-associated VEGF, EMT-related molecules, and LCSCs-related molecules and inhibited tumor angiogenesis and growth and metastasis, which may be related to the inhibition of the HIF-1α signaling pathway. It reveals that HQZX decoction may be a promising herbal compound for anti-HCC therapy, and also reveals the accurate feasibility of the hollow fiber hepatocellular carcinoma model for in vivo pharmacodynamic evaluation and mechanism study.

Monitoring spores is crucial for predicting and preventing fungal- or oomycete-induced diseases like grapevine downy mildew. However, manual spore or sporangium detection using microscopes is time-consuming and labor-intensive, often resulting in low accuracy and slow processing speed. Emerging deep learning models like YOLOv8 aim to rapidly detect objects accurately but struggle with efficiency and accuracy when identifying various sporangia formations amidst complex backgrounds. To address these challenges, we developed an enhanced YOLOv8s, namely, AFM-YOLOv8s, by introducing an Adaptive Cross Fusion module, a lightweight feature extraction module FasterCSP (Faster Cross-Stage Partial Module), and a novel loss function MPDIoU (Minimum Point Distance Intersection over Union). AFM-YOLOv8s replaces the C2f module with FasterCSP, a more efficient feature extraction module, to reduce model parameter size and overall depth. In addition, we developed and integrated an Adaptive Cross Fusion Feature Pyramid Network to enhance the fusion of multiscale features within the YOLOv8 architecture. Last, we utilized the MPDIoU loss function to improve AFM-YOLOv8s’ ability to locate bounding boxes and learn object spatial localization. Experimental results demonstrated AFM-YOLOv8s’ effectiveness, achieving 91.3% accuracy (mean average precision at 50% IoU) on our custom grapevine downy mildew sporangium dataset—a notable improvement of 2.7% over the original YOLOv8 algorithm. FasterCSP reduced model complexity and size, enhanced deployment versatility, and improved real-time detection, chosen over C2f for easier integration despite minor accuracy trade-off. Currently, the AFM-YOLOv8s model is running as a backend algorithm in an open web application, providing valuable technical support for downy mildew prevention and control efforts and fungicide resistance studies.

Pig point cloud data can be used to digitally reconstruct surface features, calculate pig body volume and estimate pig body weight. Volume, as a pig novel phenotype feature, has the following functions: (a) It can be used to estimate livestock weight based on its high correlation with body weight. (b) The volume proportion of various body parts (such as head, legs, etc.) can be obtained through point cloud segmentation, and the new phenotype information can be utilized for breeding pigs with smaller head volumes and stouter legs. However, as the pig point cloud has an irregular shape and may be partially missing, it is difficult to form a closed loop surface for volume calculation. Considering the better water tightness of Poisson reconstruction, this article adopts an improved Poisson reconstruction algorithm to reconstruct pig body point clouds, making the reconstruction results smoother, more continuous, and more complete. In the present study, standard shape point clouds, a known-volume Stanford rabbit standard model, a measured volume piglet model, and 479 sets of pig point cloud data with known body weight were adopted to confirm the accuracy and reliability of the improved Poisson reconstruction and volume calculation algorithm. Among them, the relative error was 4% in the piglet model volume result. The average absolute error was 2.664 kg in the weight estimation obtained from pig volume by collecting pig point clouds, and the average relative error was 2.478%. Concurrently, it was determined that the correlation coefficient between pig body volume and pig body weight was 0.95.

AIM: To observe the clinical effect of foldable capsular vitreous body(FCVB)implantation on ocular trauma and silicone oil-dependent eyes.METHODS: A prospective case study was performed on 17 cases(17 eyes)with ocular trauma and silicone oil-dependent in the First Hospital of Changsha from October 2017 to April 2022. All patients underwent FCVB or silicone oil removal combined with FCVB implantation. The follow-up time was 6mo, and the visual acuity, intraocular pressure, ocular axes, normal external appearances and FVCB were observed at 1wk and 6mo after operation.RESULTS: Only 6 cases had visual acuity before operation, and there were no statistical differences in the visual acuity before and at 1wk and 6mo after operation(P>0.05). The intraocular pressure was low before operation, but it was elevated at 1wk and 6mo after operation. The axial length was unchanged at 1wk and 6mo after operation, and the appearance and structure of eyeball were well maintained, and FCVB was stable with no atrophy during the follow-up period.CONCLUSIONS: FCVB implantation can preserve the appearance of eyeball, and avoid atrophy of eyeball and repeated operation, which has favorable clinical application value in the treatment of ocular trauma and silicone oil-dependent eyes.

Tandem gene duplication is an important process in plant adaptive evolution, but the generation mechanism and expression characteristics of tandem duplicated (TD) genes and their roles in plant stress response have not been rigorously investigated. Here, we take grapevine (V. vinifera) as an example to show that recent large-scale tandem gene duplication, mediated by long terminal repeat retrotransposons, promotes the expansion of specific gene families involved in response to biotic stress, biosynthesis of various secondary metabolites and adaptive evolution. More importantly, compared with interspersed duplicated genes, TD genes exhibit a position and synergistic effect, and multifaceted overactivity and play key roles in response to biotic stress caused by pathogens such as P. viticola (downy mildew) and Erysiphe necator (powdery mildew). The higher co-expression level of TD genes is not only reflected in the co-response to biotic stress, but also universal in various tissues and developmental stages. This may be related to a higher level of co-regulation and a higher transcription factor regulatory efficiency, as well as sequence similarity within gene clusters. Moreover, most TD genes are expressed asymmetrically, while maintaining a relative balance, which may be beneficial for the retention and functional differentiation of the TD genes. These findings not only advance our understanding of the evolution of the V. vinifera genome and the evolution dynamics of the TD genes which has often been overlooked, but also provide guidance for the directional selection in breeding work.

The grapevine is an important and economically valuable fruit crop, with flower sex being a key genetic trait that directly affects grapevine yield and quality. Despite its significance, there is a lack of studies on sex-linked molecular markers that can assist in grapevine breeding. In this study, we developed a grapevine single nucleotide polymorphism (SNP) marker array using a combination of genotyping by target sequencing (GBTS) and capture-in-solution technology and applied it to marker-assisted selection (MAS) of grapevine gender. The SNP array could detect a total of 20,597 core SNPs and 97,453 multiple SNPs (mSNPs), covering over 99% of the grapevine genome on each chromosome. A total of 131 progenies from a cross between Vitis vinifera 'Cabernet Sauvignon' and Vitis pseudoreticulata 'Huadong1058' that exhibited segregated sex phenotypes were sequenced using this array. Through locus mapping and a genome-wide association study (GWAS), a locus on chromosome 2 (54.74−58.80 cM) that explained 98.6% of the phenotypic variation was identified. To further utilize this locus, a sex prediction marker combination consisting of two SNPs was developed, which accurately predicted the sex of 34 natural grapevine varieties/accessions. This study demonstrates the application of GBTS in grapevine breeding and provides a reliable MAS marker set for early-stage sex selection.

Cyber-physical-social systems (CPSS) have recently gained attention from researchers due to their combination of cyber, physical, and social spaces. Modeling and Analysis of Real-Time and Embedded systems (MARTE) is a Unified Modeling Language (UML) extension profile that supports the specification, design, and verification of Real-Time Embedded Systems (RTES). While MARTE Statecharts can assist in describing CPS, it does not model the uncertainty within a CPSS environment. To enhance the accuracy of CPSS analysis, we propose the stohMCharts (stochastic hybrid MARTE statecharts) modelling framework as an extension of MARTE statecharts for modelling and analyzing stochastic hybrid systems. stohMCharts can model CPSS in a unified manner. Additionally, based on the mapping rules and algorithms, we have developed a tool to convert models built in stohMChart language into Networks Stochastic Hybrid Automata (NSHA) which can be verified by statistical model checker UPPAAL-SMC. We demonstrate the efficiency and accuracy of the framework by applying it to one autonomous driving scenarios.

Abstract Background To compare the effect of alternate part-time patching and pencil push-up training on control ability in patients with intermittent exotropia. Methods Patients (3–7 years old) with previously untreated intermittent exotropia were randomly assigned to receive alternate part-time patching, pencil push-up training, or observation. Control ability was assessed using the Office Control Score. Stereoacuity at 40 cm was evaluated with Titmus. Results were compared after a 12-week follow-up. Results Ninety-two patients (28 in patching, 30 in pencil push-ups, and 34 in observation group) completed 12-week follow-up assessments. Based on 6-point scale, the mean deviation control was significantly better in patching and pencil push-up group after 12 weeks at distance (P = 0.002 and 0.026, respectively). Furthermore, there were greater control changes in patching and pencil push-up groups in comparison with observation group from baseline to 12 weeks (P

A distributed high-speed data acquisition and monitoring system for the RF negative ion source at Huazhong University of Science and Technology (HUST) is developed, which consists of data acquisition, data forwarding and data processing. Firstly, the data acquisition modules sample physical signals at high speed and upload the sampling data with corresponding absolute-time labels over UDP, which builds the time correlation among different signals. And a special data packet format is proposed for the data upload, which is convenient for packing or parsing a fixed-length packet, especially when the span of the time labels in a packet crosses an absolute second. The data forwarding modules then receive the UDP messages and distribute their data packets to the real-time display module and the data storage modules by PUB/SUB-pattern message queue of ZeroMQ. As for the data storage, a scheme combining the file server and MySQL database is adopted to increase the storage rate and facilitate the data query. The test results show that the loss rate of the data packets is within the range of 0–5% and the storage rate is higher than 20 Mbps, both acceptable for the HUST RF negative ion source.

Abstract Background Multi-Agent Simulation is an essential technique for exploring complex systems. In research of contagious diseases, it is widely exploited to analyze their spread mechanisms, especially for preventing COVID-19. Nowadays, transmission dynamics and interventions of COVID-19 have been elaborately established by this method, but its computation performance is seldomly concerned. As it usually suffers from inadequate CPU utilization and poor data locality, optimizing the performance is challenging and important for real-time analyzing its spreading. Results This paper explores approaches to optimize multi-agent simulation for COVID-19 disease. The focus of this work is on the algorithm and data structure designs for improving performance, as well as its parallelization strategies. We propose two successive methods to optimize the computation. We construct a case-focused iteration algorithm to improve data locality, and propose a fast data-mapping scheme called hierarchical hash table to accelerate hash operations. As a result, The case-focused method degrades $$\sim 90 \%$$ ∼ 90 % cache references and achieves $$\times 4.3$$ × 4.3 speedup. Hierarchical hash table can further boost computation speed by 47%. And parallel implementation with 20 threads on CPU achieves $$\times 80$$ × 80 speedup consequently. Conclusions In this work, we propose optimizations for multi-agent simulation of COVID-19 transmission from aspects of algorithm and data structure. Benefit from improvement of locality and multi-thread implementation, our methods can significantly accelerate the simulation computation. It is promising in supporting real-time prevention of COVID-19 and other infectious diseases in the future.

Background The study aimed to detect the serum levels of fibroblast growth factor-21 (FGF-21) in fatty pancreas (FP) patients and to investigate their potential clinical value. Methods We screened patients with FP using transabdominal ultrasound. The anthropometric, biochemical and serum levels of FGF-21 were compared between the FP group and the normal control (NC) group. A receiver operating characteristic (ROC) curve was used to evaluate the predictive value of serum FGF-21 for FP patients. Results Compared with the NC group, body mass index, fasting blood glucose levels, uric acid levels and cholesterol levels of the FP group were significantly higher, while the high-density lipoprotein level was lower. In addition, levels of serum FGF-21, resistin, leptin and tumor necrosis factor-α were significantly higher than those in the NC group, while the serum adiponectin level was lower. Pearson analysis showed serum FGF-21 levels in FP patients were negatively correlated with leptin. The ROC curve showed the best critical value of the serum FGF-21 level in FP patients was 171 pg/mL (AUC 0.744, P = 0.002, 95% confidence intervals 0.636–0.852). Conclusion Serum FGF-21 was closely related to fatty pancreas. Detecting serum FGF-21 levels may help identify the population susceptible to FP.

p62/Sequestosome-1 (SQSTM1) is a stress-inducible scaffold protein involved in multiple cellular processes, including apoptosis, inflammation, cell survival, and selective autophagy. SQSTM1 mutations are associated with a spectrum of multisystem proteinopathy, including Paget disease of the bone, amyotrophic lateral sclerosis, frontotemporal dementia, and distal myopathy with rimmed vacuoles (MRV). Herein, we report a new phenotype of SQSTM1-associated proteinopathy, a novel frameshift mutation in SQSTM1 causing proximal MRV. A 44-year-old Chinese patient presented with progressive limb–girdle weakness. She had asymmetric proximal limb weakness and myopathic features on electromyography. The magnetic resonance images showed fatty infiltration into muscles, predominantly in the thighs and medial gastrocnemius, sparing the tibialis anterior. Muscle histopathology revealed abnormal protein deposition, p62/SQSTM1-positive inclusions, and rimmed vacuoles. Next-generation sequencing showed a novel pathogenic SQSTM1 frameshift mutation, c.542_549delACAGCCGC (p. H181Lfs*66). We expanded the pathogenic genotype of SQSTM1 to include a new, related phenotype: proximal MRV. We suggest that SQSTM1 variations should be screened in cases of proximal MRV.

The death of Sertoli cells (SCs) under condition of heat stress (HS) affects spermatogenesis and is associated with impaired function of the blood-testis barrier (BTB). The fatty acid arachidonic acid (AA) is essential for the maintenance of cellular function. However, excessive release of AA during HS may adversely affect the reproductive function. The molecular mechanisms through which AA modulates the BTB in SCs are unclear. In this study, we found that 100 µM AA damaged testicular morphology and accelerated SC apoptosis during HS, reducing the stability of tight junction proteins (TJPs), shown by measurement of the levels of Claudin 11, 5, Occludin, and trans-epithelial electrical resistance (TEER). It was also found that AA adversely affected TJPs by increasing the accumulation of reactive oxygen species (ROS) and malondialdehyde (MDA), activating p38 mitogen-activated protein kinases (P38 MAPK) and reducing mitochondria DNA (mtDNA) and the expression of mitochondrial complexes I and III. In contrast, pretreatment with SB203508 (a P38 MAPK inhibitor), Rotenone (an inhibitor of complex I) and Antimycin A1 (an inhibitor of complex III) reversed TJPs degradation induced by AA. Interestingly, pretreatment of cells with 10 µM Baicalein, a 12/15 lipoxygenase (12/15-LOX) -dependent inhibitor of AA production, protected against AA-induced TJPs degradation, restored mitochondrial function, and reduced apoptosis. These results suggested an intriguing link between the induction of TJPs degradation induced by AA overload and mitochondrial antioxidant function during HS, which was found to be regulated by the mitochondrial complex-ROS-P38 MAPK axis.

Abstract Background Although immune checkpoint inhibitor (ICI) is regarded as a breakthrough in cancer therapy, only a limited fraction of patients benefit from it. Cancer stemness can be the potential culprit in ICI resistance, but direct clinical evidence is lacking. Methods Publicly available scRNA-Seq datasets derived from ICI-treated patients were collected and analyzed to elucidate the association between cancer stemness and ICI response. A novel stemness signature (Stem.Sig) was developed and validated using large-scale pan-cancer data, including 34 scRNA-Seq datasets, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 10 ICI transcriptomic cohorts. The therapeutic value of Stem.Sig genes was further explored using 17 CRISPR datasets that screened potential immunotherapy targets. Results Cancer stemness, as evaluated by CytoTRACE, was found to be significantly associated with ICI resistance in melanoma and basal cell carcinoma (both P < 0.001). Significantly negative association was found between Stem.Sig and anti-tumor immunity, while positive correlations were detected between Stem.Sig and intra-tumoral heterogenicity (ITH) / total mutational burden (TMB). Based on this signature, machine learning model predicted ICI response with an AUC of 0.71 in both validation and testing set. Remarkably, compared with previous well-established signatures, Stem.Sig achieved better predictive performance across multiple cancers. Moreover, we generated a gene list ranked by the average effect of each gene to enhance tumor immune response after genetic knockout across different CRISPR datasets. Then we matched Stem.Sig to this gene list and found Stem.Sig significantly enriched 3% top-ranked genes from the list (P = 0.03), including EMC3, BECN1, VPS35, PCBP2, VPS29, PSMF1, GCLC, KXD1, SPRR1B, PTMA, YBX1, CYP27B1, NACA, PPP1CA, TCEB2, PIGC, NR0B2, PEX13, SERF2, and ZBTB43, which were potential therapeutic targets. Conclusions We revealed a robust link between cancer stemness and immunotherapy resistance and developed a promising signature, Stem.Sig, which showed increased performance in comparison to other signatures regarding ICI response prediction. This signature could serve as a competitive tool for patient selection of immunotherapy. Meanwhile, our study potentially paves the way for overcoming immune resistance by targeting stemness-associated genes.

Highlights Increased use of primary tumor resection plus metastasectomy benefited patients with left-sided tumors but not those with right-sided tumors. Increased use of primary tumor resection alone did not improve survival in either left or right-sided tumor group. Overuse of palliative primary tumor resection should be avoided.

Relationship between urban diversity and urban vitality is imperative for guiding better design in urban development, although existing frameworks are not able to efficiently examine the relationship at multiple scales. In this article, we propose a new framework to integrate nighttime light (NTL) imagery and multisource urban data into multiscale geographically weighted regression (MGWR) models to examine the varying relationship between diversity and vitality across space and time. NTL is used as a proxy for urban nighttime vitality. Public transport, taxi transit, and points of interest data are used to derive three aspects of urban diversity indices: ridership diversity, spatial interaction diversity, and built environment diversity. By comparing the models in holiday and nonholiday weeks in Shenzhen, China, the NTL-based vitality proxy was found to be strongly correlated with the urban diversity indices, given by the satisfactory goodness of fit (r-squared = 0.9) of the MGWR models. The spatially varying relationships between diversity indices and nighttime vitality were observed and patterns discussed. The analysis of the coefficients revealed the importance of stable public transport and fluctuating taxi trips for nighttime vitality. The new index proposed for the diversity of spatial interaction (DSI) is a strong indicator for nighttime vitality, adding to existing vitality indicators. Furthermore, this study found that DSI and density of catering have less temporal variation, indicating their robustness in measuring nighttime vitality. This study provided empirical insights into how nighttime vitality is related to urban diversity, demonstrating new applications of NTL for intracity studies.

IntroductionDiabetic kidney disease (DKD) is one of the complications of diabetes; however, the pathogenesis is not yet clear. A recent study has shown that senescence is associated with the course of DKD. In the present study, we explored whether senescent renal tubular cells promote renal tubulointerstitial fibrosis by secreting Sonic hedgehog (Shh) which mediates fibroblast activation and proliferation in DKD.MethodsA 36-week-old db/db mice model and the renal tubular epithelial cells were cultured in high glucose (HG, 60 mmol/L) medium for in vivo and in vitro experiments.ResultsCompared to db/m mice, blood glucose, microalbuminuria, serum creatinine, urea nitrogen, and UACR (microalbuminuria/urine creatinine) were markedly increased in db/db mice. Collagen III, monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor-alpha (TNF-α) were also increased in db/db mice kidneys, suggesting fibrosis and inflammation in the organ. Moreover, the detection of SA-β-galactosidase (SA-β-Gal) showed that the activity of SA-β-Gal in the cytoplasm of renal tubular epithelial cells increased, and the cell cycle inhibition of the expression of senescence-related gene cell cycle inhibitor p16INK4A protein and p21 protein increased, indicating that renal fibrosis in db/db mice was accompanied by cell senescence. Furthermore, Shh is highly expressed in the injured renal tubules and in the kidney tissue of db/db mice, as detected by enzyme-linked immunosorbent assay (ELISA). The results of immunofluorescence staining showed increased positive staining for Shh in renal tubular epithelial cells of db/db mice and decreased positive staining for Lamin B1, but increased positive staining for γH2A.X in cells with high Shh expression; similar results were obtained in vitro. In addition, HG stimulated renal tubular epithelial cells to secrete Shh in the supernatant of the medium. D-gal treatment of renal tubular epithelial cells increased the protein levels of Shh and p21. We also found enhanced activation and proliferation of fibroblasts cultured with the supernatant of renal tubular epithelial cells stimulated by HG medium but the proliferative effect was significantly diminished when co-cultured with cyclopamine (CPN), an inhibitor of the Shh pathway.DiscussionIn conclusion, HG induces renal tubular epithelial cell senescence, and the secretion of senescence-associated proteins and Shh mediates inflammatory responses and fibroblast activation and proliferation, ultimately leading to renal fibrosis.

Abstract Background Paphiopedilum hirsutissimum is a member of Orchidaceae family that is famous for its ornamental value around the globe, it is vulnerable due to over-exploitation and was listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora, which prevents its trade across borders. Variation in flower color that gives rise to different flower patterns is a major trait contributing to its high ornamental value. However, the molecular mechanism underlying color formation in P. hirsutissimum still remains unexplored. In the present study, we exploited natural variation in petal and labellum color of Paphiopedilum plants and used comparative transcriptome analysis as well as pigment measurements to explore the important genes, metabolites and regulatory pathways linked to flower color variation in P. hirsutissimum. Result We observed that reduced anthocyanin and flavonoid contents along with slightly higher carotenoids are responsible for albino flower phenotype. Comparative transcriptome analysis identified 3287 differentially expressed genes (DEGs) among normal and albino labellum, and 3634 DEGs between normal and albino petals. Two genes encoding for flavanone 3-hydroxylase (F3H) and one gene encoding for chalcone synthase (CHS) were strongly downregulated in albino labellum and petals compared to normal flowers. As both F3H and CHS catalyze essentially important steps in anthocyanin biosynthesis pathway, downregulation of these genes is probably leading to albino flower phenotype via down-accumulation of anthocyanins. However, we observed the downregulation of major carotenoid biosynthesis genes including VDE, NCED and ABA2 which was inconsistent with the increased carotenoid accumulation in albino flowers, suggesting that carotenoid accumulation was probably controlled at post-transcriptional or translational level. In addition, we identified several key transcription factors (MYB73, MYB61, bHLH14, bHLH106, MADS-SOC1, AP2/ERF1, ERF26 and ERF87) that may regulate structural genes involved in flower color formation in P. hirsutissimum. Importantly, over-expression of some of these candidate TFs increased anthocyanin accumulation in tobacco leaves which provided important evidence for the role of these TFs in flower color formation probably via regulating key structural genes of the anthocyanin pathway. Conclusion The genes identified here could be potential targets for breeding P. hirsutissimum with different flower color patterns by manipulating the anthocyanin and carotenoid biosynthesis pathways.

Objectives This study aimed to explore the distribution differences of common risk factors between coronary heart disease (CHD) and stroke in China.Setting The China National Stroke Screening Survey is a cluster sampling survey based on a nationwide general community population, adopting multistage stratified sampling method and covering all 31 provinces in China mainland.Participants A total number of 725 707 people aged 40 years and above were included in the study.Primary and secondary outcome measures The basic demographic information, lifestyle behaviour, physical examination, traditional risk factors, family history of cardiovascular disease (CVD) and CVD events were collected. Risk factors of CHD and stroke were explored and analysed in the whole investigated population to identify the common risk factors. Multivariate logistic regression analysis was used to analyse the distribution difference of risk factors between CHD and stroke.Results There were 13 variables associated with CHD and stroke, in which 11 variables revealed differences in the distribution between CHD and stroke. Family history of stroke (OR: 2.30; 95% CI 2.15 to 2.45), men (OR: 1.92; 95% CI 1.80 to 2.05), rural areas (OR: 1.70; 95% CI 1.60 to 1.80), transient ischaemic attack (OR: 1.41; 95% CI 1.30 to 1.54) and hypertension (OR: 1.28; 95% CI 1.19 to 1.38) indicated significantly stronger association with stroke, while family history of CHD (OR: 0.25; 95% CI 0.23 to 0.27), atrial fibrillation (OR: 0.60; 95% CI 0.51 to 0.71), diabetes (OR: 0.76; 95% CI 0.71 to 0.81), dyslipidaemia (OR: 0.76; 95% CI 0.72 to 0.81), smoking (OR: 0.79; 95% CI 0.73 to 0.85) and overweight/obesity (OR: 0.90; 95% CI 0.86 to 0.93) had closer relationship with CHD.Conclusions The distribution of risk factors for CHD and stroke were substantial differences. More specific prevention and control measures should be formulated according to the distribution differences of risk factors related to CVD.

Machining-induced edge chipping damage represents a common challenge in ceramic applications. This paper reports on responses of zirconia materials with porous and dense microstructures to edge chipping damage induced in conventional and ultrasonic vibration-assisted diamond machining. The machining-induced damage was evaluated using optical and scanning electron microscopies. The results show that edge chipping damage produced in these processes was associated with brittle fracture and depends on the material microstructure and the vibration amplitude. Pre-sintered porous zirconia with a high brittleness index yielded significantly larger edge chipping damage than sintered dense zirconia with a low index in these processes. Ultrasonic machining at an optimal vibration amplitude minimized the scale of brittle fracture at the micro level, and thus significantly diminished edge chipping damage in zirconia materials with distinct microstructures. The investigation underpins the transition from conventional to ultrasonic vibration-assisted machining for manufacturing of ceramics to achieve better product quality.

Glycogen Storage Disease 1a (Gsd1a) is an inherited disorder caused by glucose 6-phosphatase (G6Pase-α) deficiency and characterized by hypoglycaemia and high risk of liver cancer. Here the authors develop a mRNA-based G6Pase-α delivery therapy that is efficacious and safe in a mouse model of GSD1a.

Abstract Background Dengue fever (DF) is a mosquito-borne infectious disease that has threatened tropical and subtropical regions in recent decades. An early and targeted warning of a dengue epidemic is important for vector control. Current studies have primarily determined weather conditions to be the main factor for dengue forecasting, thereby neglecting that environmental suitability for mosquito breeding is also an important factor, especially in fine-grained intra-urban settings. Considering that street-view images are promising for depicting physical environments, this study proposes a framework for facilitating fine-grained intra-urban dengue forecasting by integrating the urban environments measured from street-view images. Methods The dengue epidemic that occurred in 167 townships of Guangzhou City, China, between 2015 and 2019 was taken as a study case. First, feature vectors of street-view images acquired inside each township were extracted by a pre-trained convolutional neural network, and then aggregated as an environmental feature vector of the township. Thus, townships with similar physical settings would exhibit similar environmental features. Second, the environmental feature vector is combined with commonly used features (e.g., temperature, rainfall, and past case count) as inputs to machine-learning models for weekly dengue forecasting. Results The performance of machine-learning forecasting models (i.e., MLP and SVM) integrated with and without environmental features were compared. This indicates that models integrating environmental features can identify high-risk urban units across the city more precisely than those using common features alone. In addition, the top 30% of high-risk townships predicted by our proposed methods can capture approximately 50–60% of dengue cases across the city. Conclusions Incorporating local environments measured from street view images is effective in facilitating fine-grained intra-urban dengue forecasting, which is beneficial for conducting spatially precise dengue prevention and control.

Background: The aim of this study was to validate the 2019 European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria for systemic lupus erythematosus (SLE) in antinuclear antibody (ANA)-positive Chinese patients. Methods: Medical records of all adult patients who attended the rheumatology out-patient clinics between May and September 2019 were reviewed. Patients with ever ANA positive (titre ⩾1:80) were included and evaluated for the fulfilment of the 2019 EULAR/ACR, 2012 Systemic Lupus International Collaborating Clinics (SLICC) and 1997 ACR criteria for SLE classification. The performance of these criteria in predicting a clinical diagnosis of SLE as judged by an independent panel of rheumatologists was studied and compared in different subgroups. Results: A total of 1533 patients (88.2% women; age at first clinic attendance 45.5 ± 15.6 years) were studied and 562 patients were judged to be clinical SLE. The sensitivity and specificity of the EULAR/ACR (⩾10 points), SLICC and ACR criteria for a clinical diagnosis of SLE was 96.1%, 97.9% and 86.1%; and 85.8%, 86.3% and 94.3%, respectively. Applying the attribution rule to the non-SLE controls, the specificity of the three criteria increased to 95.0%, 92.5% and 98.8%, respectively. The specificity of the EULAR/ACR criteria was higher in male patients (97.9%), those aged >50 years (97.0%) and disease duration of ⩽3 years (97.6%). Using a cut-off of 12 points, the specificity of the EULAR/ACR criteria was further increased (96.6%) while a high sensitivity (95.0%) was maintained. Conclusion: In Chinese patients with a positive ANA, the EULAR/ACR criteria for clinical SLE perform equally well to the SLICC criteria. Both the EULAR/ACR and SLICC are more sensitive but less specific than the ACR criteria. The specificity of all the three criteria is enhanced by applying the attribution rule to controls. The specificity of the EULAR/ACR criteria is higher in certain patient subgroups or when the cut-off score is raised.

The outbreak of COVID-19 stimulated a new round of discussion on how to deal with respiratory infectious diseases. Influenza viruses have led to several pandemics worldwide. The spatiotemporal characteristics of influenza transmission in modern cities, especially megacities, are not well-known, which increases the difficulty of influenza prevention and control for populous urban areas. For a long time, influenza prevention and control measures have focused on vaccination of the elderly and children, and school closure. Since the outbreak of COVID-19, the public's awareness of measures such as vaccinations, mask-wearing, and home-quarantine has generally increased in some regions of the world. To control the influenza epidemic and reduce the proportion of infected people with high mortality, the combination of these three measures needs quantitative evaluation based on the spatiotemporal transmission characteristics of influenza in megacities. Given that the agent-based model with both demographic attributes and fine-grained mobility is a key planning tool in deploying intervention strategies, this study proposes a spatially explicit agent-based influenza model for assessing and recommending the combinations of influenza control measures. This study considers Shenzhen city, China as the research area. First, a spatially explicit agent-based influenza transmission model was developed by integrating large-scale individual trajectory data and human response behavior. Then, the model was evaluated across multiple intra-urban spatial scales based on confirmed influenza cases. Finally, the model was used to evaluate the combined effects of the three interventions (V: vaccinations, M: mask-wearing, and Q: home-quarantining) under different compliance rates, and their optimal combinations for given control objectives were recommended. This study reveals that adults were a high-risk population with a low reporting rate, and children formed the lowest infected proportion and had the highest reporting rate in Shenzhen. In addition, this study systematically recommended different combinations of vaccinations, mask-wearing, and home-quarantine with different compliance rates for different control objectives to deal with the influenza epidemic. For example, the “V45%-M60%-Q20%” strategy can maintain the infection percentage below 5%, while the “V20%-M60%-Q20%” strategy can maintain the infection percentage below 15%. The model and policy recommendations from this study provide a tool and intervention reference for influenza epidemic management in the post-COVID-19 era.

Abstract Background Coronavirus disease (COVID-19) has become a pandemic. The knowledge, attitudes, and practices (KAP) of the public play a major role in the prevention and control of infectious diseases. The objective of the present study was to evaluate the KAP of the Chinese public and to assess potential influencing factors related to practices. Methods A cross-sectional online survey was conducted in China in February 2020 via a self-designed questionnaire comprising 33 questions assessing KAP. Results For the 2136 respondents from 30 provinces or municipalities in China, the accurate response rate for the knowledge section ranged from 72.7 to 99.5%, and the average was 91.2%. Regarding attitude section, the percentage of positive attitudes (“strongly agree” and “agree”) ranged from 94.7 to 99.7%, and the average value was 98.0%. The good practices (“always” and “often”) results ranged from 76.1 to 99.5%, and the average value was 96.8%. The independent samples t-test revealed that gender and ethnic differences had no effect on knowledge, attitude or behaviour (P > 0.05). However, knowledge was associated with age (t = 4.842, p

Abstract Background To investigate the value of serum hydroxybutyrate dehydrogenase (HBDH) level, an isozyme of lactate dehydrogenase, in evaluating the severity of acute pancreatitis (AP). Methods Patients diagnosed with AP from January 2013 to December 2018 were included in this retrospective study. Patients were divided into the normal serum HBDH levels group (n-HBDH group) and the high serum HBDH levels group (h-HBDH group) according to the criteria HBDH ≥ 182 U/L after admission. The demographic parameters, laboratory data and the severity of AP in the two groups were compared. The receiver operating curve (ROC) was used to evaluate the efficacy of serum HBDH in predicting persistent organ failure and systemic inflammatory response syndrome (SIRS). Results A total of 260 AP patients were enrolled, including 176 cases in the n-HBDH group and 84 cases in the h-HBDH group. The incidence of SIRS and organ failure in the h-HBDH group were significantly higher than those in n-HBDH group (both P

Propionic acidemia is a serious pediatric inherited disorder with no effective treatments. Here the authors demonstrate that delivering dual mRNAs as an enzyme replacement approach can be used as an effective therapy in a mouse model of propionic acidemia, with potential applicability to chronically administer multiple mRNAs in other genetic disorders.

Abstract Background The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. Methods An epidemiological model with five compartments (susceptible–exposed–symptomatic–asymptomatic–recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. Results The age-specific SEIAR model fitted the data well in each age group (P

We have reported that of the 10 most commonly used adeno-associated virus (AAV) serotype vectors, AAV6 is the most efficient in transducing primary human hematopoietic stem cells (HSCs) in vitro, as well as in vivo. More recently, polyvinyl alcohol (PVA), was reported to be a superior replacement for human serum albumin (HSA) for ex vivo expansion of HSCs. Since HSA has been shown to increase the transduction efficiency of AAV serotype vectors, we evaluated whether PVA could also enhance the transduction efficiency of AAV6 vectors in primary human HSCs. We report here that up to 12-fold enhancement in the transduction efficiency of AAV6 vectors can be achieved in primary human HSCs with PVA. We also demonstrate that the improvement in the transduction efficiency is due to PVA-mediated improved entry and intracellular trafficking of AAV6 vectors in human hematopoietic cells in vitro, as well as in murine hepatocytes in vivo. Taken together, our studies suggest that the use of PVA is an attractive strategy to further improve the efficacy of AAV6 vectors. This has important implications in the optimal use of these vectors in the potential gene therapy and genome editing for human hemoglobinopathies such as β-thalassemia and sickle cell disease.

Abstract Background As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. Methods In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R 0) from the RP model to assess the transmissibility of the SARS-CoV-2. Results The value of R 0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. Conclusions Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.