Resting-state brain networks alterations in adolescents with Internet Gaming Disorder associate with cognitive control impairments.

Objective: Research indicates that cognitive control is compromised in individuals with internet gaming disorder (IGD). However, the neural mechanisms behind it are still unclear. This study aims to investigate alterations in resting-state brain networks in adolescents with IGD and the potential neurobiological mechanisms underlying cognitive dysfunction. Materials and methods: A total of 44 adolescent IGD subjects (male/female: 38/6) and 50 healthy controls (male/female: 40/10) were enrolled. Participants underwent demographic assessments, Young's Internet Addiction Scale, Barratt Impulsiveness Scale 11 Chinese Revised Version, the Chinese Adolescents' Maladaptive Cognitions Scale, exploratory eye movement tests, and functional magnetic resonance imaging (fMRI). FMRI data were analyzed using the GIFT software for independent component analysis, focusing on functional connectivity within and between resting-state brain networks. Results: In comparison to the control group, impulsivity in adolescent IGD subjects showed a positive correlation with the severity of IGD (r=0.6350, p < 0.001), linked to impairments in the Executive Control Network (ECN) and a decrease in functional connectivity between the Salience Network (SN) and ECN (r=0.4307, p=0.0021; r=-0.5147, p=0.0034). Decreased resting state activity of the dorsal attention network (DAN) was associated with attentional dysregulation of IGD in adolescents (r=0.4071, p=0.0017), and ECN increased functional connectivity with DAN. The degree of IGD was positively correlated with enhanced functional connectivity between the ECN and DAN (r=0.4283, p=0.0037). Conclusions: This research demonstrates that changes in the ECN and DAN correlate with heightened impulsivity and attentional deficits in adolescents with IGD. The interaction between cognitive control disorders and resting-state brain networks in adolescent IGD is related.

Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia.

In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656-0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237-0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

Investigating the bearing performance of the foundation under the combined effects of flood scouring and soaking.

Bearing capacity degradation of foundations under the impact of the flood is one of the major reasons responsible for the collapse and damage to the rural buildings, posing a serious threat to the local village societies. Based on a case study of a rural building foundation had been destroyed by flooding. This paper investigated the deterioration process of rural building foundations under the combined effect of dynamic scouring and static soaking caused by flooding. Using the two-dimensional shallow water equation, erosion depth was calculated for different flood velocities. Then, the bearing capacity degradation under the combined scouring-soaking effect was analyzed using the finite element method. Finally, investigating the influence of inflow direction and building group masking on the foundation's bearing capacity. The results indicate that under the combined effect, the bearing capacity of village building foundations decreases by 47.88%, with scouring slightly more impactful than soaking. Inflow angle has minimal effect on bearing performance, while the masking effect of the building group provides better protection for the foundation of rear buildings.

Identification of watermelon H3K4 and H3K27 genes and their expression profiles during watermelon fruit development.

BACKGROUND: The ClaH3K4s and ClaH3K27s gene families are subfamilies of the SET family, each with a highly conserved SET structure domain and a PHD structural domain. Both participate in histone protein methylation, which affects the chromosome structure and gene expression, and is essential for fruit growth and development. METHODS AND RESULTS: In order to demonstrate the structure and expression characteristics of ClaH3K4s and ClaH3K27s in watermelon, members of the watermelon H3K4 and H3K27 gene families were identified, and their chromosomal localization, gene structure, and protein structural domains were analyzed. The phylogeny and covariance of the gene families with other species were subsequently determined, and the expression profiles were obtained by performing RNA-Seq and qRT-PCR. The watermelon genome had five H3K4 genes with 3207-8043 bp nucleotide sequence lengths and four H3K27 genes with a 1107-5499 bp nucleotide sequence. Synteny analysis revealed the close relationship between watermelon and cucumber, with the majority of members displaying a one-to-one covariance. Approximately half of the 'Hua-Jing 13 watermelon' ClaH3K4s and ClaH3K27s genes were expressed more in the late fruit development stages, while the changes were minimal for the remaining half. H3K4-2 expression was observed to be slightly greater on day 21 compared to other periods. Moreover, ClaH3K27-1 and ClaH3K27-2 were hardly expressed throughout the developing period, and ClaH3K27-4 exhibited the highest expression. CONCLUSION: These results serve as a basis for further functional characterization of the H3K4 and H3K27 genes in the fruit development of watermelon.

Lineage-specific amplification and epigenetic regulation of LTR-retrotransposons contribute to the structure, evolution, and function of Fabaceae species.

BACKGROUND: Long terminal repeat (LTR)-retrotransposons (LTR-RTs) are ubiquitous and make up the majority of nearly all sequenced plant genomes, whereas their pivotal roles in genome evolution, gene expression regulation as well as their epigenetic regulation are still not well understood, especially in a large number of closely related species. RESULTS: Here, we analyzed the abundance and dynamic evolution of LTR-RTs in 54 species from an economically and agronomically important family, Fabaceae, and also selected two representative species for further analysis in expression of associated genes, transcriptional activity and DNA methylation patterns of LTR-RTs. Annotation results revealed highly varied proportions of LTR-RTs in these genomes (5.1%~68.4%) and their correlation with genome size was highly positive, and they were significantly contributed to the variance in genome size through species-specific unique amplifications. Almost all of the intact LTR-RTs were inserted into the genomes 4 Mya (million years ago), and more than 50% of them were inserted in the last 0.5 million years, suggesting that recent amplifications of LTR-RTs were an important force driving genome evolution. In addition, expression levels of genes with intronic, promoter, and downstream LTR-RT insertions of Glycine max and Vigna radiata, two agronomically important crops in Fabaceae, showed that the LTR-RTs located in promoter or downstream regions suppressed associated gene expression. However, the LTR-RTs within introns promoted gene expression or had no contribution to gene expression. Additionally, shorter and younger LTR-RTs maintained higher mobility and transpositional potential. Compared with the transcriptionally silent LTR-RTs, the active elements showed significantly lower DNA methylation levels in all three contexts. The distributions of transcriptionally active and silent LTR-RT methylation varied across different lineages due to the position of LTR-RTs located or potentially epigenetic regulation. CONCLUSION: Lineage-specific amplification patterns were observed and higher methylation level may repress the activity of LTR-RTs, further influence evolution in Fabaceae species. This study offers valuable clues into the evolution, function, transcriptional activity and epigenetic regulation of LTR-RTs in Fabaceae genomes.

[Comparative Analysis of Primary and Reactivated EB Virus Infection Associated Hemophagocytic Lymphohistiocytosis].

OBJECTIVE: To compare the clinical characteristics of children with hemophagocytic lymphocytosis (HLH) associated with primary Epstein-Barr virus (EBV) infection and EBV reactivation, and explore the effects of different EBV infection status on the clinical indexes and prognosis of HLH. METHODS: The clinical data of 51 children with EBV associated HLH treated in Henan Children's Hospital from June 2016 to June 2021 were collected. According to the detection results of plasma EBV antibody spectrum, they were divided into EBV primary infection-associated HLH group (18 cases) and EBV reactivation-associated HLH group (33 cases). The clinical features, laboratory indexes and prognosis of the two groups were analyzed and compared. RESULTS: There were no significant differences in age, gender, hepatomegaly, splenomegaly, lymphadenopathy, neutrophil count in peripheral blood, hemoglobin content, platelet count, plasma EBV-DNA load, lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, albumin, fibrinogen, triglyceride, ferritin, hemophagocytosis in bone marrow, NK cell activity and sCD25 between the two groups(P>0.05). The central nervous system involvement and CD4/CD8 in EBV reactivation-associated HLH group were significantly higher than those in primary infection-associated HLH group, but the total bilirubin was significantly lower than that in primary infection-associated HLH group (P<0.05). After treatment according to HLH-2004 protocol, the remission rate, 5-year OS rate and 5-year EFS rate of patients in EBV reactivation-associated HLH group were significantly lower than those in EBV primary infection-associated HLH group (P<0.05). CONCLUSION: EBV reactivation-associated HLH is more likely to cause central nervous system involvement and the prognosis is worser than EBV primary infection-associated HLH, which requires intensive treatment.

Descriptions of two new species of Phaecadophora Walsingham, 1900 (Lepidoptera, Tortricidae, Olethreutinae) from China.

Two new species of the genus Phaecadophora, P.dactylinasp. nov. and P.vascularissp. nov., are described from the southwest China. Photographs of the adults and the genitalia are provided. Keys to the species of the genus based on the male and female genitalia are given.

Micro-expression recognition model based on TV-L1 optical flow method and improved ShuffleNet.

Micro-expression is a kind of facial action that reflects the real emotional state of a person, and has high objectivity in emotion detection. Therefore, micro-expression recognition has become one of the research hotspots in the field of computer vision in recent years. Research with neural networks with convolutional structure is still one of the main methods of recognition. This method has the advantage of high operational efficiency and low computational complexity, but the disadvantage is its localization of feature extraction. In recent years, there are more and more plug-and-play self-attentive modules being used in convolutional neural networks to improve the ability of the model to extract global features of the samples. In this paper, we propose the ShuffleNet model combined with a miniature self-attentive module, which has only 1.53 million training parameters. First, the start frame and vertex frame of each sample will be taken out, and its TV-L1 optical flow features will be extracted. After that, the optical flow features are fed into the model for pre-training. Finally, the weights obtained from the pre-training are used as initialization weights for the model to train the complete micro-expression samples and classify them by the SVM classifier. To evaluate the effectiveness of the method, it was trained and tested on a composite dataset consisting of CASMEII, SMIC, and SAMM, and the model achieved competitive results compared to state-of-the-art methods through cross-validation of leave-one-out subjects.

Lightweight ViT Model for Micro-Expression Recognition Enhanced by Transfer Learning.

As opposed to macro-expressions, micro-expressions are subtle and not easily detectable emotional expressions, often containing rich information about mental activities. The practical recognition of micro-expressions is essential in interrogation and healthcare. Neural networks are currently one of the most common approaches to micro-expression recognition. Still, neural networks often increase their complexity when improving accuracy, and overly large neural networks require extremely high hardware requirements for running equipment. In recent years, vision transformers based on self-attentive mechanisms have achieved accuracy in image recognition and classification that is no less than that of neural networks. Still, the drawback is that without the image-specific biases inherent to neural networks, the cost of improving accuracy is an exponential increase in the number of parameters. This approach describes training a facial expression feature extractor by transfer learning and then fine-tuning and optimizing the MobileViT model to perform the micro-expression recognition task. First, the CASME II, SAMM, and SMIC datasets are combined into a compound dataset, and macro-expression samples are extracted from the three macro-expression datasets. Each macro-expression sample and micro-expression sample are pre-processed identically to make them similar. Second, the macro-expression samples were used to train the MobileNetV2 block in MobileViT as a facial expression feature extractor and to save the weights when the accuracy was highest. Finally, some of the hyperparameters of the MobileViT model are determined by grid search and then fed into the micro-expression samples for training. The samples are classified using an SVM classifier. In the experiments, the proposed method obtained an accuracy of 84.27%, and the time to process individual samples was only 35.4 ms. Comparative experiments show that the proposed method is comparable to state-of-the-art methods in terms of accuracy while improving recognition efficiency.

Long-Term Antipsychotic Effectiveness and Comparison of the Efficacy of Monotherapy and Polypharmacy in Schizophrenia: A 3-Years Follow-Up "Real World" Study in China.

Background: Discontinuation of antipsychotic treatment is a common problem in patients with schizophrenia and could reduce the effectiveness of treatment. Time to discontinuation (TTD) is one of the indicators of compliance and may also be an effective indicator of medication efficacy. The aim of the study was to compare the clinical effectiveness of quetiapine, olanzapine, risperidone, and aripiprazole in the real-world treatment of schizophrenia with 3-years follow-up. Method: A multi-center, open, cohort, prospective, real-world study was conducted. 706 patients were analyzed without intervention in medication selection and use, followed up for 3 years. Kaplan-Meier survival curves were used to draw the treatment discontinuation rates (TDR) curves at each time point. Cox proportional hazard regression model was used to assess the relative risk of TTD of antipsychotics. Results: There was a significant difference among monotherapy groups in all-cause antipsychotic treatment discontinuation (p = 0.0057). Among the four medications, the TDR of risperidone was the highest. Compared with polypharmacy, except for aripiprazole, the TDR of other three monotherapy medications were lower than that of polypharmacy, and olanzapine was statistically different (p = 0.0325). The cox regression analysis showed that after correction of Hochberg with multiple tests, only olanzapine had a relative risk lower than risperidone (p < 0.0083). Conclusions: The findings indicated that risperidone monotherapy and polypharmacy had the highest TDR and the shortest TTD. Olanzapine monotherapy had a relative risk lower than risperidone and was superior to polypharmacy.

Landslide Susceptibility Evaluation Using Different Slope Units Based on BP Neural Network.

Landslides are one of the most widespread natural hazards that cause damage to both property and life every year. Therefore, the landslide susceptibility evaluation is necessary for land hazard assessment and mitigation of landslide-related losses. Selecting an appropriate mapping unit is an essential step for landslide susceptibility evaluation. This study tested the back propagation (BP) neural network technique to develop a landslide susceptibility map in Qingchuan County, Sichuan Province, China. It compared the results of applying six different slope unit scales for landslide susceptibility maps obtained using hydrological analysis. We prepared a dataset comprising 973 historical landslide locations and six conditioning factors (elevation, slope degree, aspect, lithology, distance to fault lines, and distance to drainage network) to construct a geospatial database and divided the data into the training and testing datasets. We based on the BP learning algorithm to generate landslide susceptibility maps using the training dataset. We divided Qingchuan County into six different scales of slope unit: 4,401, 13,146, 39,251, 46,504, 56,570, and 69,013, then calculated the receiver operating characteristic (ROC) curve, and used the area under the curve (AUC) for the quantitative evaluation of 6 different slope unit scales of landslide susceptibility maps using the testing dataset. The verification results indicated that the evaluation generated by 56,570 slope units had the highest accuracy with a ROC curve of 0.9424. Overelaborate and rough division of slope units may not get the best evaluation results, and it is necessary to obtain the slope units most consistent with the actual situation through debugging. The results of this study will be useful for the development of landslide hazard mitigation strategies.

An Open-Label Exploratory Clinical Trial Evaluating the Effects of GLS (Coptidis Rhizoma-Evodiae Fructus 2 : 1) on Fibroblast Growth Factor 21 in Patients with Nonalcoholic Fatty Liver Disease.

Methods: In a 12-week, open-label, exploratory clinical trial, 126 NAFLD patients were randomly divided into the GLS group (lifestyle intervention plus GLS) or the polyene phosphatidylcholine (PPC) group (lifestyle intervention plus PPC). Random numbers generated by DPS software were used in combination with opaque, sealed envelopes for allocation concealment. At baseline as well as at the end of the study, anthropometric parameters, glucose, lipids, hepatic enzymes, and FGF 21 were measured, with hepatic fat accumulation assessed by ultrasound (US) and US-based controlled attenuation parameter (CAP). Results: 119 patients completed the study. Baseline parameters did not significantly differ between the two groups (P > 0.05). Compared with PPC, GLS decreased more significantly in hepatic fat accumulation, body weight index, waist circumference, waist-to-hip ratio, serum glucose, total cholesterol, triglyceride, low-density lipoprotein cholesterol, alanine transaminase, aspartate transaminase, gamma-glutamyl transferase, and FGF 21 (P < 0.05). The effects of GLS on waist circumference, waist-to-hip ratio, CAP, and gamma-glutamyl transferase (GGT) were positively correlated with serum FGF 21 (r = 0.343, 0.342, 0.315, and 0.374, respectively, P < 0.05). The GGT and FGF-21 changes were also confirmed by multiple linear regression analysis (B, 0.777; 95% CI: 0.307-1.247, P < 0.05). Conclusion: GLS has a significant hepatoprotective effect on NAFLD patients, causing a decrease in FGF-21 secretion in response to the damage itself.

Sulfonated polydivinylbenzene bamboo-like nanotube stabilized Pickering emulsion for effective oxidation of olefins to 1,2-diol.

Sulfonated polydivinylbenzene bamboo-like nanotube (SPDVB) with effective olefins oxidation activity is prepared by combining cationic polymerization and sulfonation. By merely adjusting sulfonation time, SPDVB with different sulfonic acid group (-SO3H) contents is achieved. SPDVB is used as both a solid emulsifier and catalyst to fabricate Pickering emulsion interface catalytic system for oxidizing olefins with 30% H2O2 acting as oxidant/water phase and olefins acting as reactants/oil phase. It is shown that Pickering emulsion interface catalytic system stabilized by SPDVB exhibits enhanced olefins oxidation efficiency than the conventional ones. At the optimum catalyst and reaction condition, the conversion of olefins by Pickering emulsion interface catalytic system stabilized by SPDVB for cyclohexene, 1-methylcyclohexene, cyclooctene, 2,3-dimethyl-2-butene oxidation is higher than 90.00% and the corresponding 1,2-diol selectivity exceeds 93.00% except the selectivity to 1-methyl-1,2-cyclohexanediol. The catalytic system also exhibits excellent cycling performance (>95.00% olefins conversion and >89.00% 1,2-diol selectivity for cyclohexene/2,3-dimethyl-2-butene oxidation after four cycles). A possible mechanism for oxidation of olefins to 1,2-diol by SPDVB stabilized Pickering emulsion is proposed: the high catalytic interface area between sulfonic acid group and H2O2 in water phase enhances the sulfonic acid group of SPDVB to convert into peroxysulfonic acid (catalytic activity centre) firstly; then the formed peroxysulfonic acid attacks the double bond of olefins to form epoxide intermediates, which will be hydrolyzed to 1,2-diol.

Sex differences between serum total bilirubin levels and cognition in patients with schizophrenia.

BACKGROUND: Cognitive deficits are common in patients with schizophrenia (SCZ). Abnormal serum total bilirubin (TBIL) levels have been involved in cognitive deficits associated with neuropsychiatric diseases such as mild cognitive impairment and subcortical ischemic vascular disease. However, this relationship has not yet been fully investigated in patients with SCZ. Therefore, the aim of this study was to investigate the association between the serum TBIL concentration and cognitive deficits in SCZ patients and to determine whether a sex difference exists in the association. METHODS: A total of 455 participants were eligible and included in this cross-sectional study. Cognition was evaluated using the Montreal Cognitive Assessment. Serum TBIL concentration was measured with an automatic biochemistry analyzer according to the routine protocol in the hospital medical laboratory. RESULTS: Serum TBIL levels were lower in the cognition impairment group than in the cognition normal group in male patients. In contrast, serum TBIL levels tended to be increased in the cognition impairment group in female patients, although the difference was not significant. Further stepwise multiple regression analysis stratified by sex showed that serum TBIL was independently and positively associated with cognitive function in male patients but not in female patients. Moreover, the association between serum TBIL level and cognitive function was also identified by the propensity score matching (PSM) method in male patients, but not in female patients. CONCLUSION: These findings suggest that lower serum TBIL levels may be associated with cognitive impairment in male SCZ patients.

A Random Forest Model for Predicting Social Functional Improvement in Chinese Patients with Schizophrenia After 3 Months of Atypical Antipsychotic Monopharmacy: A Cohort Study.

PURPOSE: Impaired social functions contribute to the burden of schizophrenia patients and their families, but predictive tools of social functioning prognosis and specific factors are undefined in Chinese clinical practice. This article explores a machine learning tool to identify whether patients will achieve significant social functional improvement after 3 months of atypical antipsychotic monopharmacy and finds the defined risk factors using a multicenter clinical study. PATIENTS AND METHODS: A multicenter study on atypical antipsychotic (AAP) treatment in Chinese patients with schizophrenia (SALT-C) was conducted from July 2011 to August 2018. Data from 550 patients with AAP monopharmacy from their baseline to their 3-month follow-up were used to establish machine learning tools after screening. The positive outcome was an increase in the Personal and Social Performance (PSP) scale score by ≥10 points. The predictors were a range of investigator-rated assessments on symptoms, functioning, the safety of AAPs and illness history. The Least Absolute Shrinkage and Selection Operator (LASSO) was used for the feature screening and ranking of the predicted variables. The random forest algorithm and five-fold cross-validation for optimizing the model were selected to ensure the generalizability and precision. RESULTS: There were 137 patients (mean [SD] age, 41.1 [16.8] years; 77 [58.8%] female) who had a good social functional prognosis. A lower PSP score, taking a mood stabilizer, a high total Positive and Negative Symptom Scale (PANSS) and PANSS general subscale score, unemployment, a hepatic injury with medication, comorbid cardiovascular disease and being male predicted poor PSP outcomes. The generalizability of the PSP predictive tool was estimated with the precision-recall curve (accuracy of 79.5%, negative predictive value of 92.6% and positive predictive value of 57.1%) and receiver operating characteristic curve (ROC) (specificity of 81.8% and sensitivity of 78.7%). CONCLUSION: The machine learning tool established using our current real-world data could assist in predicting PSP outcome by several clinical factors.

Hydrodynamic and topography based cellular automaton model for simulating debris flow run-out extent and entrainment behavior.

As for late, studies have indicated that cellular automaton (CA) models are among the most effective solutions for simulating the extent of debris-flow run-out. However, it is currently difficult to effectively simulate both the inundated area and the erosion pattern of the debris flow process. This difficulty is caused by the lack of detailing regarding debris flow hydrodynamics as the primary concern of most CA-based models is the topographic gradient of the gully. In this study, we propose a two-dimensional Monte Carlo simulation-based CA model with hydrodynamic methods describing debris-flow behavior to address these problems. Herein, a topography function concerning slope gradient and bed roughness, and a persistence function regarding flow inertia, are combined to improve the flow routing algorithm for better determining the run-out extent of debris flow. Hydraulic links and discharge exchange between neighboring cells using sink-filling approach, as well as the bed sediment entrainment function, are incorporated into the CA model to describe the mass migration process along the flow path. To verify the performance of our proposed model, we further select the 2010 Yohutagawa debris flow event in Japan as a case study. The results indicate that the proposed model better simulates the complex dynamic process of debris flow.

Modeling the progressive entrainment of bed sediment by viscous debris flows using the three-dimensional SC-HBP-SPH method.

Recent reports and experimental data closely indicate that bed-sediment entrainment by debris flows strongly impacts the evolution of the topographic signature of a valley. However, it is difficult to constrain the physics of the entrainment process in numerical models. The challenge is deeply embedded in the shape of the velocity profile, whose knowledge is fundamental for estimating debris-flow basal shear stress exerting on bed sediment. Most two-dimensional models are restricted because the depth-integrated shallow water assumption is problematic in this aspect. One alternative is to combine a three-dimensional, particle-based numerical model with a progressive entrainment law. In this paper, we propose a three-dimensional, surface cell (SC)-based smooth particle hydrodynamics (SPH) model for simulating bed-sediment entrainment by viscous debris flows. The dynamic behavior of a debris flow is simulated by the open-source DualSPHysics scheme, into which the Herschel-Bulkley-Papanastasiou (HBP) rheology model is incorporated. Subsequently, the bed surface is meshed, over which the particles belonging to a certain cell at each time step are identified to represent the basal velocity and flow depth using a novel SC-based algorithm. With the extracted velocities of these basal particles, the sediment entrainment rate of each cell can be estimated using the optimized progressive entrainment law. The proposed SC-HBP-SPH method is tested by means of a full-scale flume experiment carried out in a previous study. The results show that the proposed model can adequately describe and reproduce the complex dynamic process of bed-sediment entrainment by overriding debris flows.

[Expression Levels of HES1, C-MYC and NF-kB in Peripheral Blood of Patients with T Cell Acute Lymphoblastic Leukemia and Their Significance].

OBJECTIVE: To analyze and investigate the expression levels of HES1, C-MYC and NF-kB in peripheral blood of patients with T cell acute lymphoblastic leukemia (T-ALL) and their significance. METHODS: Sixty patients with T-ALL and 60 patients with acute myelogenous leukemia (AML) diagnosed in our hospital from June 2012 to March 2015 were enrolled in T-ALL group and AML group, respectively. Another 30 healthy people were enrolled in the control group. Peripheral blood was collected to detect the expression levels of HES1, C-MYC and NF-kB by RT-PCR. The general data and the expression of HES1, C-MYC and NF-kB in peripheral blood were compared among the patients with different type of leukemia, cytogenetical types and different prognosis. RESULTS: There was no significant difference in baseline data, such as age and sex among the 3 groups (P＞0.05). The Hb level, WBC and Plt count, BM blast cell ratio in T-ALL and AML groups all were significantly higher than those in control group (P＜0.01), but there were no statistical difference in above-mentioned indicators between T-ALL and AML groups (P＞0.05). The expression levels of HES1, C-MYC and NF-kB in peripheral blood among 3 groups were significantly differenct (P＜0.01), the expressions levels of HES1, C-MYC and NF-kB in T-ALL and AML groups were significantly higher than those in control were significantly group (P＜0.01), moreover, the expression levels of above-mentional indicators in T-ALL groups were significantly higher than than those in AML group (P＜0.01). The expression levels of HES1, C-MYC and NF-kB iin T-ALL patients with poor prognosis were significantly higher than those in T-ALL patients with favorable prognosis (P＜0.01); the expression levels of HES1, C-MYC and NF-kB in peripheral blood of patients with different theraptic efficacy were follow: complete remission group＜partial remission group＜no remission group (P＜0.01). CONCLUSION: The HES1, C-MYC and NF-kB are highly expressed in peripheral blood of the patients with T-ALL, moreover, the expression levels maybe different, because of the cytogenetic, and theraptic efficacy.

Quantitative efficacy of three antipsychotic drugs for schizophrenia based on a real-world study in China.

Atypical antipsychotics exert remarkable long-term efficacy on the personal and social functions of schizophrenic patients. However, quantitative information on the social function of schizophrenic patients treated with atypical antipsychotics is scarce in the current clinical guidelines. In this study, we established pharmacodynamic models to quantify the time-efficacy relationship of three antipsychotic drugs based on the data from a real-world study conducted in China. A total of 373 schizophrenic patients who received antipsychotic monotherapy with olanzapine (n = 144), risperidone (n = 160), or aripiprazole (n = 69) were selected from a three-year prospective, multicenter study. The follow-up times were 13, 26, 52, 78, 104, 130, and 156 weeks after baseline. A time-efficacy model was developed with nonlinear mixed effect method based on changes in Personal and Social Performance (PSP) score compared with the baseline level. Crucial pharmacodynamic parameters, including maximum efficacy and drug onset time, were used to distinguish the efficacy of the three drugs. We quantified the time course of PSP improvement in patients after treatment with these three antipsychotics: olanzapine, risperidone, and aripiprazole reached an Emax value of 80.3%, 68.2%, and 23.9% at weeks 56.7, 29.2, and 36.8, respectively. General psychotic symptoms, onset frequency, and illness course were identified as significant factors affecting the efficacy of these drugs. The newly constructed models provide an evidence of the benefit of long-term maintenance therapy with atypical antipsychotics in individualized schizophrenia treatment in China.

Comprehensive analysis of landslide stability and related countermeasures: a case study of the Lanmuxi landslide in China.

We report on a comprehensive method for analyzing landslide stability and the mitigation effect of countermeasures in this paper. The proposed method is a combination of theoretical method and numerical method. To address the uncertainties of the soil strength parameters, the rational values of these parameters are comprehensively determined by the back-analysis result of the reliability method and the result by the quantitative method, as well as the in-situ geological test. To evaluate the slope stability, the limit analysis using the 2D upper bound method and the FEM simulation using strength reduction method are performed, respectively. In order to illustrate the presented method, the so-called Lanmuxi landslide in China is selected as a case study. Results demonstrated that the stress and strain majorly concentrated at the toe and crown of the slope. According to the analysis results, countermeasures consisting of anchor lattice beams, landslide piles, and cracks filling, are suggested to reduce the failure risk of the landslide. Effect assessment based on the FEM analysis verifies the feasibility and effectiveness of the recommended countermeasures.