Factors and pathways of non-suicidal self-injury in children: insights from computational causal analysis.

Background: Non-suicidal self-injury (NSSI) has become a significant public health issue, especially prevalent among adolescents. The complexity and multifactorial nature of NSSI necessitate a comprehensive understanding of its underlying causal factors. This research leverages the causal discovery methodology to explore these causal associations in children. Methods: An observational dataset was scrutinized using the causal discovery method, particularly employing the constraint-based approach. By integrating machine learning and causal inference techniques, the study aimed to determine direct causal relationships associated with NSSI. The robustness of the causal relationships was evaluated using three methods to construct and validate it: the PC (Peter and Clark) method, Fast Causal Inference (FCI) method, and the GAE (Graphical Autoencoder) method. Results: Analysis identified nine nodes with direct causal relationships to NSSI, including life satisfaction, depression, family dysfunction, sugary beverage consumption, PYD (positive youth development), internet addiction, COVID-19 related PTSD, academic anxiety, and sleep duration. Four principal causal pathways were identified, highlighting the roles of lockdown-induced lifestyle changes, screen time, positive adolescent development, and family dynamics in influencing NSSI risk. Conclusions: An in-depth analysis of the factors leading to Non-Suicidal Self-Injury (NSSI), highlighting the intricate connections among individual, family, and pandemic-related influences. The results, derived from computational causal analysis, underscore the critical need for targeted interventions that tackle these diverse causative factors.

Adaptive beamforming based on minimum variance (ABF-MV) using deep neural network for ultrafast ultrasound imaging.

Ultrafast ultrasound imaging can achieve high frame rate by emitting planewave (PW). However, the image quality is drastically degraded in comparison with traditional scanline focused imaging. Using adaptive beamforming techniques can improve image quality at cost of real-time performance. In this work, an adaptive beamforming based on minimum variance (ABF-MV) with deep neural network (DNN) is proposed to improve the image performance and to speed up the beamforming process of ultrafast ultrasound imaging. In particular, a DNN, with a combination architecture of fully-connected network (FCN) and convolutional autoencoder (CAE), is trained with channel radio-frequency (RF) data as input while minimum variance (MV) beamformed data as ground truth. Conventional delay-and-sum (DAS) beamformer and MV beamformer are utilized for comparison to evaluate the performance of the proposed method with simulations, phantom experiments, and in-vivo experiments. The results show that the proposed method can achieve superior resolution and contrast performance, compared with DAS. Moreover, it is remarkable that both in theoretical analysis and implementation, our proposed method has comparable image quality, lower computational complexity, and faster frame rate, compared with MV. In conclusion, the proposed method has the potential to be deployed in ultrafast ultrasound imaging systems in terms of imaging performance and processing time.

Collision-aware interactive simulation using graph neural networks.

Deep simulations have gained widespread attention owing to their excellent acceleration performances. However, these methods cannot provide effective collision detection and response strategies. We propose a deep interactive physical simulation framework that can effectively address tool-object collisions. The framework can predict the dynamic information by considering the collision state. In particular, the graph neural network is chosen as the base model, and a collision-aware recursive regression module is introduced to update the network parameters recursively using interpenetration distances calculated from the vertex-face and edge-edge tests. Additionally, a novel self-supervised collision term is introduced to provide a more compact collision response. This study extensively evaluates the proposed method and shows that it effectively reduces interpenetration artifacts while ensuring high simulation efficiency.

Versatile cutting fracture evolution modeling for deformable object cutting simulation.

BACKGROUND AND OBJECTIVES: Soft body cutting simulation is the core module of virtual surgical training systems. By making full use of the powerful computing resources of modern computers, the existing methods have already met the needs of real-time interaction. However, there is still a lack of high realism. The main reason is that most current methods follows the "Intersection-IS-Fracture" mode, namely cutting fracture occurs as long as the cutting blade intersects with the object. To model real-life cutting phenomenon considering deformable objects' fracture resistance, this paper presents a highly realistic virtual cutting simulation algorithm by introducing an energy-based cutting fracture evolution model. METHODS: We design the framework based on the co-rotational linear FEM model to support large deformations of soft objects and also adopt the composite finite element method (CFEM) to balance between simulation accuracy and efficiency. Then, a cutting plane constrained Griffth's energy minimization scheme is proposed to determine when and how to generate a new cut. Moreover, to provide the contact effect before the fracture occurs, we design a material-aware adaptation scheme that can guarantee indentation consistent with the cutting tool blade and visually plausible indentation-induced deformation to avoiding large computational effort. RESULTS AND CONCLUSION: The experimental results demonstrate that the proposed algorithm is feasible for generating highly realistic cutting simulation results of different objects with various materials and geometrical characteristics while introducing a negligible computational cost. Besides, for different blade shapes, the proposed algorithm can produce highly consistent indentation and fracture. Qualitative evaluation and performance analysis indicate the versatility of the proposed algorithm.

Extreme Low-Resolution Activity Recognition Using a Super-Resolution-Oriented Generative Adversarial Network.

Activity recognition is a fundamental and crucial task in computer vision. Impressive results have been achieved for activity recognition in high-resolution videos, but for extreme low-resolution videos, which capture the action information at a distance and are vital for preserving privacy, the performance of activity recognition algorithms is far from satisfactory. The reason is that extreme low-resolution (e.g., 12 × 16 pixels) images lack adequate scene and appearance information, which is needed for efficient recognition. To address this problem, we propose a super-resolution-driven generative adversarial network for activity recognition. To fully take advantage of the latent information in low-resolution images, a powerful network module is employed to super-resolve the extremely low-resolution images with a large scale factor. Then, a general activity recognition network is applied to analyze the super-resolved video clips. Extensive experiments on two public benchmarks were conducted to evaluate the effectiveness of our proposed method. The results demonstrate that our method outperforms several state-of-the-art low-resolution activity recognition approaches.

Monocyte chemoattractant protein 1 released from macrophages induced by hepatitis C virus promotes monocytes migration.

Hepatitis C Virus (HCV) infection usually progress to chronic liver disease and shows a significant increase in total monocyte/macrophages numbers in the liver. Monocyte chemoattractant protein-1 (MCP-1) plays a role in the recruitment of monocytes to the liver. In this study we found that MCP-1 were up-regulated in macrophages cultured with cell-culture derived infectious HCV particles (HCVcc) and promoted the migration of monocytes. IL1ß, IL6 and TNFα were factors that induced MCP-1 expression, which were up-regulated in macrophages induced by HCV. Long-term of HCV incubation induced apoptosis of macrophages. Finally, we observed the effect of HCV infected macrophages on nearby liver cells. Huh7 cells continuously co-cultured with monocyte/macrophages displayed increased expression of pro-inflammatory cytokines and the morphology of Huh7 cells were greatly changed. Taken together, our study provides more information for the role of monocyte/macrophages in HCV related chronic liver disease.

Development of hair cells in inner ear is associated with expression and promoter methylation of Notch-1 in postnatal mice.

The present study was designed to investigate the correlation among the number of hair cells in inner ear, Notch-1 gene expression levels and its methylation status of the promoter region in the postnatal mice. The hair cells in inner ear were collected from postnatal mice at day 0, 4, 8 and 16 and counted by immunofluorescence. Notch-1 mRNA expression were measured by real-time quantitative polymerize chain reaction (PCR). Methylation levels of CpG islands in Notch-1 promoters were analyzed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry. The results showed that the number of hair cells in the inner ear increased gradually after birth, which were positively correlated to Notch-1 mRNA expression. However, analysis on methylation of CpG sites in Notch-1 promoter showed that the methylation rates increased gradually after births, which were correlated with the decreased expression of Notch-1. Drug lesion induced the loss of hair cells, and stimulated the expression of Notch-1 mRNA expression, but didn't influence the methylation rates of Notch-1 promoter. We concluded that the Notch-1 mRNA expression level in inner ear tissues is correlated with the development of hair cells. CpG islands in Notch-1 promoter region manifest hypermethylation status when hair cells in inner ear are mature.

Characterization of a novel orthoreovirus isolated from fruit bat, China.

BACKGROUND: In recent years novel human respiratory disease agents have been described for Southeast Asia and Australia. The causative pathogens were classified as pteropine orthoreoviruses with a strong phylogenetic relationship to orthoreoviruses of bat origin. RESULTS: In this report, we isolated a novel Melaka-like reovirus (named "Cangyuan virus") from intestinal content samples of one fruit bat residing in China's Yunnan province. Phylogenetic analysis of the whole Cangyuan virus genome sequences of segments L, M and S demonstrated the genetic diversity of the Cangyuan virus. In contrast to the L and M segments, the phylogenetic trees for the S segments of Cangyuan virus demonstrated a greater degree of heterogeneity. CONCLUSIONS: Phylogenetic analysis indicated that the Cangyuan virus was a novel orthoreovirus and substantially different from currently known members of Pteropine orthoreovirus (PRV) species group.

[Genetic evolution analysis of matrix protein 2 gene of avian influenza H5N1 viruses from boundary of Yunnan province].

OBJECTIVE: To elucidate the variation in characterizations and genetic evolution of the matrix protein 2 or ion channel protein(M2) genes of avian influenza subtype H5N1 viruses in the boundary region of Yunnan province from 2008 to 2012. METHODS: A total of swab samples were collected from foreign poultry such as the junction between Yunnan and Vietnam, Laos,myanmar and wild birds in boundary region of Yunnan province from 2008 to 2012 and screened by H5N1 subtype-specific multiplex RT-PCR. The M genes of H5N1 virus from the positive samples were amplified by RT-PCR and cloned into pMD18-T vectors for sequencing. The alignment and phylogenetic analysis of M2 genes were performed with sequences of the known reference strains. RESULTS: A total of 71 positive samples were found out of 1240 samples and the positive rate was 5.72%. A total of 14 different M2 sequences were obtained from 30 positive samples and were divided into 3 distinct clades or sub-clades(1.2.1, 1.2.2 and 2) by phylogenetic analysis, 5, 7 and 2, respectively. The M2 genes and Hemagglutinin(HA) genes of H5N1 viruses from the boundary region of Yunnan province had showed different relationship of genetic evolution. The substitution or mutation of key amino acids sites had been found among the domains of epitope, adamantane-resistance, and poultry or human original viral strains. CONCLUSION: The M2 genes of H5N1 subtype viruses in boundary region of Yunnan province from 2008 to 2012 showed genetic divergence and the virus of clade 1.2.2 had become dominant epidemic strain in this region.

[Genetic evolution of non-structural gene among avian influenza H5N1 viruses isolated from the boundary of Yunnan province].

OBJECTIVE: To elucidate the characteristics of variation and the genetic evolution of non-structural protein (NS1, NS2) genes related to avian influenza subtype H5N1 viruses isolated from the boundary region of Yunnan province. METHODS: Swab samples were collected from foreign poultry and wild birds in the boundary regions of Yunnan province and screened by H5/N1 subtype-specific multiplex RT-PCR. The NS segment of H5N1 virus from the positive samples were amplified by RT-PCR and cloned into pMD18-T vectors for sequencing. The alignment and phylogenetic analysis on those available NS1, NS2 genes were performed with sequences of the known reference strains. RESULTS: 71 positive samples were identified from 1240 samples, with the positive rate as 5.72%. Fourteen different NS segment sequences were obtained from 30 representative positive samples and could be divided into 3 distinct clades or sub-clades (I-1, I-2 and II), by phylogenetic analysis. The NS1/NS2 genes and Hemagglutinin (HA) genes of H5N1 viruses from the boundary regions of Yunnan province showed different relationships regarding the characteristics on genetic evolution. The substitution or mutation of key amino acids sites had been noticed in the nuclear location signal domains, effect domain, and other pathogenicity markers. CONCLUSION: NS genes of H5N1 subtype viruses in boundary region of Yunnan province showed genetic divergence and the virus of clade I-2 and II had become dominant epidemic strains in this region since 2010.

Larvicidal activity of essential extract of Rosmarinus officinalis against Culex quinquefasciatus.

Constituents in rosemary (Rosmarinus officinalis) have been shown to have larvicidal activity against invertebrates. In order to explore the properties of crude extract of rosemary further, we studied the chemical composition and its activity against dichlorodiphenyltrichloroethane (DDT)-susceptible, DDT-resistant, and field strains of Culex quinquefasciatus larvae. The major components of R. officinalis were found to be eucalyptol and camphor, with relative percentages of 10.93% and 5.51%, respectively. Minor constituents included limonene, (+)-4-carene, isoborneol, 1-methyl-4-(1-methylethylidene)-cyclohexene, and pinene. The median lethal concentration (LC50) values of the essential oil of R. officinalis against DDT-susceptible, DDT-resistant, and field strains of larvae of Cx. quinquefasciatus were 30.6, 26.4, and 38.3 mg/liter, respectively. The single median lethal dose (LD50) in Kunming mice was 4752 mg/kg. Essential oils from R. officinalis may, therefore, provide an effective natural plant product for use in mosquito prevention and control.

Identification of a novel Getah virus by Virus-Discovery-cDNA random amplified polymorphic DNA (RAPD).

BACKGROUND: The identification of new virus strains is important for the study of infectious disease, but current (or existing) molecular biology methods are limited since the target sequence must be known to design genome-specific PCR primers. Thus, we developed a new method for the discovery of unknown viruses based on the cDNA--random amplified polymorphic DNA (cDNA-RAPD) technique. Getah virus, belonging to the family Togaviridae in the genus Alphavirus, is a mosquito-borne enveloped RNA virus that was identified using the Virus-Discovery-cDNA RAPD (VIDISCR) method. RESULTS: A novel Getah virus was identified by VIDISCR from suckling mice exposed to mosquitoes (Aedes albopictus) collected in Yunnan Province, China. The non-structural protein gene, nsP3, the structural protein gene, the capsid protein gene, and the 3'-untranslated region (UTR) of the novel Getah virus isolate were cloned and sequenced. Nucleotide sequence identities of each gene were determined to be 97.1-99.3%, 94.9-99.4%, and 93.6-99.9%, respectively, when compared with the genomes of 10 other representative strains of Getah virus. CONCLUSIONS: The VIDISCR method was able to identify known virus isolates and a novel isolate of Getah virus from infected mice. Phylogenetic analysis indicated that the YN08 isolate was more closely related to the Hebei HB0234 strain than the YN0540 strain, and more genetically distinct from the MM2021 Malaysia primitive strain.

[Genetic diversification of avian influenza H5N1 virus in boundary areas of Yunnan province].

OBJECTIVE: To elucidate the genetic diversifications of avian influenza subtype H5N1 viruses in the boundary regions of Yunnan province during 2009 to July, 2011. METHODS: Swab samples were collected from foreign poultry and wild birds in boundary regions of Yunnan province during 2009 to July, 2011 and tested by H5/N1 subtype-specific multiplex RT-PCR. The HA genes of H5N1 virus from the positive samples were amplified by RT-PCR and cloned into pMD18-T vectors for sequencing. Both alignment and phylogenetic analysis were performed with sequences of the known reference strains. RESULTS: Fifteen different HA sequences were obtained from 36 representative positive samples and could be divided into 2 distinct Clades (2.3.2 and 2.3.4). Through phylogenetic analysis, Clade 2.3.2 and 2.3.4 could then be further divided into 3 (II-1 to II-3) and 2 smaller clades (I-1 and I-2), respectively. The viruses of Clade 2.3.2 II-1 and II-2 were new variant strains of H5N1 virus. The cleavage sites of HA from positive samples all possessed molecular characterization of highly pathogenic avian influenza virus. Mutation of key amino acids had been found among receptor binding sites, potential glycosylation sites, neutralizing epitopes and others. CONCLUSION: It seemed evident that the H5N1 subtype viruses showed genetic diversifications and had undergone the evolution progress of multi-clade (2.3.2, 2.3.4) to single calde (2.3.2) in the boundary regions of Yunnan province, during 2009 to July, 2011.

Application of navigation template to fixation of sacral fracture using three-dimensional reconstruction and reverse engineering technique.

OBJECTIVE: To provide a new method in the fixation of sacral fracture by means of three-dimensional reconstruction and reverse engineering technique. METHODS: Pelvis image data were obtained from three-dimensional CT scan in patients with sacral fracture. The data were transferred into a computer workstation. The three-dimensional models of pelvis were reconstructed using Amira 3.1 software and saved in STL format. Then the three-dimensional fracture models were imported into Imageware 9.0 software. Different situations of reduction (total reduction, half reduction and non-reduction) were simulated using Imageware 9.0 software. The best direction and location of extract iliosacral lag screws were defined using reverse engineering according to these three situations and navigation templates were designed according to the anatomic features of the postero-iliac part and the channel. The exact navigational template was made by rapid prototyping. Drill guides were sterilized and used intraoperatively to assist in surgical navigation and the placement of iliosacral lag screws. RESULTS: Accurate screw placement was confirmed with postoperative X-ray and CT scanning. The navigation template was found to be highly accurate. CONCLUSION: The navigation template may be a useful method in minimal-invasive fixation of sacroiliac joint fracture.