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The rockburst and spalling problems encountered in the Jinping Underground Laboratory are to be investigated using 3-D physical model testing. New similarity relationships for the brittleness, brittle–ductile transition and ductility characteristics of deep hard rock are first established based on the characteristics of the deep rock mass, thereby providing guidance for the development of analog materials with new characteristics that are appropriate for investigating deep rock engineering disasters via large-scale 3-D physical model tests. Achieving similarity simultaneously among the multiple physical–mechanical properties of deep hard rock constitutes the major challenge of research on analog materials. Consequently, a new method for designing analog materials by controlling the aggregate characteristics is proposed. The test results indicate that the aggregates of the analog materials can be controlled to achieve properties that are similar to those of the original rock. The newly developed analog material exhibits basic mechanical parameters and properties that are similar to those of Jinping marble, including high strength, high brittleness, and high unit weight in addition to brittle–ductile transition and ductility characteristics and deformation and failure modes. The new analog material successfully simulates the major physical–mechanical properties of Jinping marble and overcomes the limitations of preexisting methods, which develop analog materials via cementing agents, in which the achievement of similarity simultaneously among multiple properties is impossible. [ABSTRACT FROM AUTHOR]

The common practice in understanding some puzzling geotechnical and geomechanical issues by large-scale three-dimensional physical model tests is recently much improved by the introduction of 3D-printing technology which can realize the reconstruction of complex geological structures. However, during 3D printing process, the regular rock-like material suffers from some general problems such as short initial setting time, water segregation, decreasing fluidity induced by chemical reaction, and some other unclear influencing factors. To promote further development of physical model via 3D printing method and to fabricate large-scale high-precision 3D geological models, in this paper, the flow characteristics of rock-like materials were first investigated using a new fluidity testing apparatus. Based on the test results, a novel 3D-printing technology of geological material was formulated. Then, the technologies of fabricating the desired structural specimens, acquiring samples with mechanical properties and cracking behaviors similar to natural rock, printing large-scale complex geological models were formulated. The results show that the 3D-printing technology of geological materials had a principle: no losing fluidity during printing time. The parameters of print head diameter, line width, line span, and line slump were the four key factors affecting desired structural samples. From the enlightenment of printing small-scale sample, the printing methods of complex large-scale geological models including decreasing printing time, acquiring heterogeneous geological model with inner structures, desired density, and surrounding smooth surface were proposed. [ABSTRACT FROM AUTHOR]

Schwann cells (SCs) are unique glial cells in the peripheral nerve and may secrete multiple neurotrophic factors, adhesion molecules, extracellular matrix molecules to form the microenvironment of peripheral nerve regeneration, guiding and supporting nerve proliferation and migration. Cdc42 plays an important regulatory role in dynamic changes of the cytoskeleton. However, there is a little study referred to regulation and mechanism of Cdc42 on glial cells after peripheral nerve injury. The present study investigated the role of Cdc42 in the proliferation and migration of SCs after sciatic nerve injury. Cdc42 expression was tested, showing that the mRNA and protein expression levels of Cdc42 were significantly up-regulated after sciatic nerve injury. Then, we isolated and purified SCs from injuried sciatic nerve at day 7. The purified SCs were transfected with Cdc42 siRNA and pcDNA3.1-Cdc42, and the cell proliferation, cell cycle and migration were assessed. The results implied that Cdc42 siRNA remarkably inhibited Schwann cell proliferation and migration, and resulted in S phase arrest. While pcDNA3.1-Cdc42 showed a contrary effect. Besides, we also observed that Cdc42 siRNA down-regulated the protein expression of β-catenin, Cyclin D1, c-myc and p-p38, which were up-regulated by pcDNA3.1-Cdc42. Meanwhile, the inhibitor of Wnt/β-catenin and p38 MAPK signaling pathway IWP-2 and SB203580 significantly inhibited the effect of pcDNA3.1-Cdc42 on cell proliferation and migration. Overall, our data indicate that Cdc42 regulates Schwann cell proliferation and migration through Wnt/β-catenin and p38 MAPK signaling pathway after sciatic nerve injury, which provides further insights into the therapy of the sciatic nerve injury. [ABSTRACT FROM AUTHOR]

• Brittle fracture of deep hard rock was simulated by physical model tests. • The evolution process of brittle fracture in deep tunnels was captured and analysed. • The onset conditions and mechanism of spalling failure in deep tunnels were revealed. • The spalling characteristics were verified by three research methods. Brittle fracture in deep hard rock tunnels in the Jinping laboratory, China, can often endanger the stability of engineering structures. This study describes physical model testing and real-time observations on the evolution process of v-shaped brittle fracture, failure characteristics, onset conditions, and influencing factors in hard rock tunnels. Real-time observations are presented integrated a high-speed camera, acoustic emission system, a digital image correlation, and distributed fiber optic strain sensing technologies. The results show that the process of spalling failure can be divided into two main stages, namely, the instantaneous cracking process in the sidewall surface, and the spalling process of the thin rock chips developing progressively from the excavation boundary to the far field, finally forming stable v-shaped notches. The deviatoric stress of spalling failure in the physical model test satisfies the constant deviatoric stress criterion. The critical strain at spalling failure is consistent with that calculated by the Hoek–Brown strength criterion. Spalling is a form of brittle failure caused by deferential tensile strain. The working face effect is observed in the physical model excavation process. The highest strain caused by overloading occurs near the free surface of the sidewall. The relationship between stress and geometric similarity constants in deep rock engineering is derived. The failure characteristics revealed in the physical model tests are verified by numerical simulations based on cellular automaton theory, which agree well with the experimental results. The research findings can provide theoretical support for the prevention and control of spalling disasters in deep engineering practice. [ABSTRACT FROM AUTHOR]

This paper develops an efficient algorithm that combines polynomial-chaos kriging (PCK) and adaptive radial-based importance sampling (ARBIS) for reliability analysis. The key idea of ARBIS is to adaptively determine a sphere with the center at the origin and radius equal to the smallest distance of the failure domain to the origin, also known as the optimal β -sphere, and only those samples outside the optimal β -sphere have a possibility of failure and thus need to evaluate the limit-state function to judge their states (safe or failure). In the proposed algorithm, both the PCK model and β -sphere are updated adaptively. In each iteration of determining the optimal β -sphere, the PCK model is updated sequentially based on an active learning function, which is used to select the most informative sample from the samples between the last and current β -spheres. Once the stopping criterion is met, the learning process of PCK in this iteration terminates, and the obtained PCK model is then used to determine the next β -sphere. The updating iteration of the β -sphere proceeds until the optimal sphere is found. Five representative examples are revisited, in which the results demonstrate the high accuracy and efficiency of the proposed PCK-ARBIS algorithm. [ABSTRACT FROM AUTHOR]

Circular RNA (CircRNA)-microRNA (miRNA) interaction (CMI) is an important model for the regulation of biological processes by non-coding RNA (ncRNA), which provides a new perspective for the study of human complex diseases. However, the existing CMI prediction models mainly rely on the nearest neighbor structure in the biological network, ignoring the molecular network topology, so it is difficult to improve the prediction performance. In this paper, we proposed a new CMI prediction method, BEROLECMI, which uses molecular sequence attributes, molecular self-similarity, and biological network topology to define the specific role feature representation for molecules to infer the new CMI. BEROLECMI effectively makes up for the lack of network topology in the CMI prediction model and achieves the highest prediction performance in three commonly used data sets. In the case study, 14 of the 15 pairs of unknown CMIs were correctly predicted., (© 2024. The Author(s).)

Objectives: To dynamically observe the changes in hypoxia-inducible factor 1α (HIF-1α) and Bcl-2/adenovirus E1B19kDa-interacting protein 3 (BNIP3) in children with traumatic brain injury (TBI) and evaluate their clinical value in predicting the severity and prognosis of pediatric TBI., Methods: A prospective study included 47 children with moderate to severe TBI from January 2021 to July 2023, categorized into moderate (scores 9-12) and severe (scores 3-8) subgroups based on the Glasgow Coma Scale. A control group consisted of 30 children diagnosed and treated for inguinal hernia during the same period, with no underlying diseases. The levels of HIF-1α, BNIP3, autophagy-related protein Beclin-1, and S100B were compared among groups. The predictive value of HIF-1α, BNIP3, Beclin-1, and S100B for the severity and prognosis of TBI was assessed using receiver operating characteristic (ROC) curves., Results: Serum levels of HIF-1α, BNIP3, Beclin-1, and S100B in the TBI group were higher than those in the control group ( P <0.05). Among the TBI patients, the severe subgroup had higher levels of HIF-1α, BNIP3, Beclin-1, and S100B than the moderate subgroup ( P <0.05). Correlation analysis showed that the serum levels of HIF-1α, BNIP3, Beclin-1, and S100B were negatively correlated with the Glasgow Coma Scale scores ( P <0.05). After 7 days of treatment, serum levels of HIF-1α, BNIP3, Beclin-1, and S100B in both non-surgical and surgical TBI patients decreased compared to before treatment ( P <0.05). ROC curve analysis indicated that the areas under the curve for predicting severe TBI based on serum levels of HIF-1α, BNIP3, Beclin-1, and S100B were 0.782, 0.835, 0.872, and 0.880, respectively ( P <0.05), and for predicting poor prognosis of TBI were 0.749, 0.775, 0.814, and 0.751, respectively ( P <0.05)., Conclusions: Serum levels of HIF-1α, BNIP3, and Beclin-1 are significantly elevated in children with TBI, and their measurement can aid in the clinical assessment of the severity and prognosis of pediatric TBI.

Growing studies reveal that Circular RNAs (circRNAs) are broadly engaged in physiological processes of cell proliferation, differentiation, aging, apoptosis, and are closely associated with the pathogenesis of numerous diseases. Clarification of the correlation among diseases and circRNAs is of great clinical importance to provide new therapeutic strategies for complex diseases. However, previous circRNA-disease association prediction methods rely excessively on the graph network, and the model performance is dramatically reduced when noisy connections occur in the graph structure. To address this problem, this paper proposes an unsupervised deep graph structure learning method GSLCDA to predict potential CDAs. Concretely, we first integrate circRNA and disease multi-source data to constitute the CDA heterogeneous network. Then the network topology is learned using the graph structure, and the original graph is enhanced in an unsupervised manner by maximize the inter information of the learned and original graphs to uncover their essential features. Finally, graph space sensitive k-nearest neighbor (KNN) algorithm is employed to search for latent CDAs. In the benchmark dataset, GSLCDA obtained 92.67% accuracy with 0.9279 AUC. GSLCDA also exhibits exceptional performance on independent datasets. Furthermore, 14, 12 and 14 of the top 16 circRNAs with the most points GSLCDA prediction scores were confirmed in the relevant literature in the breast cancer, colorectal cancer and lung cancer case studies, respectively. Such results demonstrated that GSLCDA can validly reveal underlying CDA and offer new perspectives for the diagnosis and therapy of complex human diseases.

With a growing body of evidence establishing circular RNAs (circRNAs) are widely exploited in eukaryotic cells and have a significant contribution in the occurrence and development of many complex human diseases. Disease-associated circRNAs can serve as clinical diagnostic biomarkers and therapeutic targets, providing novel ideas for biopharmaceutical research. However, available computation methods for predicting circRNA-disease associations (CDAs) do not sufficiently consider the contextual information of biological network nodes, making their performance limited. In this work, we propose a multi-hop attention graph neural network-based approach MAGCDA to infer potential CDAs. Specifically, we first construct a multi-source attribute heterogeneous network of circRNAs and diseases, then use a multi-hop strategy of graph nodes to deeply aggregate node context information through attention diffusion, thus enhancing topological structure information and mining data hidden features, and finally use random forest to accurately infer potential CDAs. In the four gold standard data sets, MAGCDA achieved prediction accuracy of 92.58%, 91.42%, 83.46% and 91.12%, respectively. MAGCDA has also presented prominent achievements in ablation experiments and in comparisons with other models. Additionally, 18 and 17 potential circRNAs in top 20 predicted scores for MAGCDA prediction scores were confirmed in case studies of the complex diseases breast cancer and Almozheimer's disease, respectively. These results suggest that MAGCDA can be a practical tool to explore potential disease-associated circRNAs and provide a theoretical basis for disease diagnosis and treatment.

Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influence of non-Euclidean data and multisource information, and there is still a critical issue for graph neural networks regarding how to set the feature diffuse distance. To solve the problems, we proposed SiSGC, which makes full use of the biological knowledge information as initial features and learns the structure information from the constructed heterogeneous graph with the adaptive selection of the information diffuse distance. Then, the structural features are fused with the denoised similarity information and fed to the advanced classifier of CatBoost to make predictions. Three different data sets are used to confirm the robustness and generalization of SiSGC under two splitting strategies. Experiment results demonstrate that the proposed model achieves superior performance compared with the six leading methods and four variants. Our case study on breast neoplasms further indicates that SiSGC is trustworthy and robust yet simple. We also present four drugs for breast cancer treatment with high confidence and further give an explanation for demonstrating the rationality. There is no doubt that SiSGC can be used as a beneficial supplement for drug repositioning.

Motivation: Accumulating clinical evidence shows that circular RNA (circRNA) plays an important regulatory role in the occurrence and development of human diseases, which is expected to provide a new perspective for the diagnosis and treatment of related diseases. Using computational methods can provide high probability preselection for wet experiments to save resources. However, due to the lack of neighborhood structure in sparse biological networks, the model based on network embedding and graph embedding is difficult to achieve ideal results., Results: In this paper, we propose BioDGW-CMI, which combines biological text mining and wavelet diffusion-based sparse network structure embedding to predict circRNA-miRNA interaction (CMI). In detail, BioDGW-CMI first uses the Bidirectional Encoder Representations from Transformers (BERT) for biological text mining to mine hidden features in RNA sequences, then constructs a CMI network, obtains the topological structure embedding of nodes in the network through heat wavelet diffusion patterns. Next, the Denoising autoencoder organically combines the structural features and Gaussian kernel similarity, finally, the feature is sent to lightGBM for training and prediction. BioDGW-CMI achieves the highest prediction performance in all three datasets in the field of CMI prediction. In the case study, all the 8 pairs of CMI based on circ-ITCH were successfully predicted., Availability: The data and source code can be found at https://github.com/1axin/BioDGW-CMI-model., Competing Interests: Declaration of competing interest None Declared., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Circular RNA (circRNA) plays an important role in the diagnosis, treatment, and prognosis of human diseases. The discovery of potential circRNA-miRNA interactions (CMI) is of guiding significance for subsequent biological experiments. Limited by the small amount of experimentally supported data and high randomness, existing models are difficult to accomplish the CMI prediction task based on real cases. In this paper, we propose KS-CMI, a novel method for effectively accomplishing CMI prediction in real cases. KS-CMI enriches the 'behavior relationships' of molecules by constructing circRNA-miRNA-cancer (CMCI) networks and extracts the behavior relationship attribute of molecules based on balance theory. Next, the denoising autoencoder (DAE) is used to enhance the feature representation of molecules. Finally, the CatBoost classifier was used for prediction. KS-CMI achieved the most reliable prediction results in real cases and achieved competitive performance in all datasets in the CMI prediction., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

Objective: Combined surgical and endovascular treatment for vascular disorders has become prevalent in recent years. However, reports on one-session hybrid surgery for arteriovenous malformations (AVMs) are relatively rare. The safety and efficiency of combined treatment for brain AVMs were analyzed in biplanar hybrid operating room (OR) at one stage., Methods: We retrospectively analyzed 20 patients with AVMs undergoing combined surgical and endovascular treatment from October 2015 to June 2018. The data for resection rate, microcatheter adhesion, surgical position and postoperative outcomes were analyzed. Total resection or near-total resection was achieved in all cases., Results: A total of 13 patients were under combined endovascular and surgical procedures, and 7 experienced surgery with intraoperative digital subtraction angiography. Sitting position was applied in 3 of them; 2 niduses in cerebellum, and 1 in parietal lobe. Compared with admission modified Rankin Scale (mRS) in all patients, postoperative 12-month mRS showed a significant decline. Besides, 3 patients experienced microcatheter adhesion after endovascular embolization, thereafter underwent surgical adhesion removal while nidus resection was done., Conclusion: Combined endovascular and surgical modality in a hybrid OR at one stage provides a safe strategy for the treatment of AVMs. The biplanar hybrid neurointerventional suite is endowed with unconstrained operating angle which enables combined endovascular and surgical treatment in sitting position. It also reduces the risk of microcatheter adhesion, which enables interventional radiologists to perform aggressively., (© 2021. Huazhong University of Science and Technology.)

Predicting the microRNA-disease associations by using computational methods is conductive to the efficiency of costly and laborious traditional bio-experiments. In this study, we propose a computational machine learning-based method (DANE-MDA) that preserves integrated structure and attribute features via deep attributed network embedding to predict potential miRNA-disease associations. Specifically, the integrated features are extracted by using deep stacked auto-encoder on the diverse orders of matrixes containing structure and attribute information and are then trained by using random forest classifier. Under 5-fold cross-validation experiments, DANE-MDA yielded average accuracy, sensitivity, and AUC at 85.59%, 84.23%, and 0.9264 in term of HMDD v3.0 dataset, and 83.21%, 80.39%, and 0.9113 in term of HMDD v2.0 dataset, respectively. Additionally, case studies on breast, colon, and lung neoplasms related disease show that 47, 47, and 46 of the top 50 miRNAs can be predicted and retrieved in the other database., Competing Interests: The authors declare that they have no competing interests., (© 2021 The Authors.)

The recognition and analysis of tables on printed document images is a popular research field of the pattern recognition and image processing. Existing table recognition methods usually require high degree of regularity, and the robustness still needs significant improvement. This paper focuses on a robust table recognition system that mainly consists of three parts: Image preprocessing, cell location based on contour mutual exclusion, and recognition of printed Chinese characters based on deep learning network. A table recognition app has been developed based on these proposed algorithms, which can transform the captured images to editable text in real time. The effectiveness of the table recognition app has been verified by testing a dataset of 105 images. The corresponding test results show that it could well identify high-quality tables, and the recognition rate of low-quality tables with distortion and blur reaches 81%, which is considerably higher than those of the existing methods. The work in this paper could give insights into the application of the table recognition and analysis algorithms.

MicroRNAs (miRNAs) play a critical role in human diseases. Determining the association between miRNAs and disease contributes to elucidating the pathogenesis of liver diseases and seeking the effective treatment method. Despite great recent advances in the field of the associations between miRNAs and diseases, implementing association verification and recognition efficiently at scale presents serious challenges to biological experimental approaches. Thus, computational methods for predicting miRNA-disease association have become a research hotspot. In this paper, we present a new computational method, named distance-based sequence similarity for miRNA-disease association prediction (DBMDA), that directly learns a mapping from miRNA sequence to a Euclidean space. The notable feature of our approach consists of inferring global similarity from region distances that can be figured by chaos game representation algorithm based on the miRNA sequences. In the 5-fold cross-validation experiment, the area under the curve (AUC) obtained by DBMDA in predicting potential miRNA-disease associations reached 0.9129. To assess the effectiveness of DBMDA more effectively, we compared it with different classifiers and former prediction models. Besides, we constructed two case studies for prostate neoplasms and colon neoplasms. Results show that 39 and 39 out of the top 40 predicted miRNAs were confirmed by other databases, respectively. BDMDA has made new attempts in sequence similarity and achieved excellent results, while at the same time providing a new perspective for predicting the relationship between diseases and miRNAs. The source code and datasets explored in this work are available online from the University of Chinese Academy of Sciences (http://220.171.34.3:81/)., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Rationale: Obturator dislocation of the femoral head combined with ipsilateral femoral neck and pubic fracture is a rare injury. We used cannulated screws combined with a femoral neck medial plate for the first time to treat this type of injury and achieved good follow-up results., Patient Concerns: The patient was hospitalized due to an accident resulting in swelling and deformity accompanied by limited mobility of the right hip and left knee., Diagnoses: X-ray examination and computed tomography confirmed that the patient suffered from right hip obturator dislocation, femoral head and neck fracture, pubic fracture, as well as open fracture of the left femoral shaft., Interventions: Open reduction and internal fixation with cannulated screws and a medial support plate of the femoral neck were performed for the right hip obturator dislocation, femoral head and neck fracture, and the pubic fracture. Artificial bone grafting was performed to support the femoral head defect. Debridement and the second phase of internal fixation were executed to cure the open fracture of the left femoral shaft., Outcomes: The patient was followed-up for 6 months and showed good hip function. X-ray examination and computed tomography indicated that the fractures healed well without fracture displacement or loosening of the implants. Meanwhile, there were no signs of femoral neck valgus and femoral head necrosis observed., Lessons: The combination of cannulated screws and medial support plate was suggested for the treatment of hip obturator dislocation and femoral head and neck fracture. Furthermore, partial weight loading exercise should be performed promptly to reduce the risk of muscular atrophy and myasthenia.

Objective: To analyze the effect of Chinese medicine (CM) on mortality and quality of life (QOL) of acquired immunodefificiency syndrome (AIDS) patients treated with combined antiretroviral therapy (cART)., Methods: A random sample of AIDS patients enrolled in the National Chinese Medicine Treatment Trial Program (NCMTP) that met the inclusion criteria was included in this study. NCMTP patients were included as the CM+cART group, and those not in the NCMTP were included as the cART group. Survival from September 2004 to September 2012 was analyzed by retrospective cohort study. QOL was analyzed by cross-sectional study., Results: The retrospective cohort study included 528 AIDS patients, 322 in the CM+cART group and 206 in the cART group. After 8 years, the mortality in the CM+cART group was 3.3/100 person-years, which was lower than the cART group of 5.3/100 person-years (P<0.05). The hazard ratio (HR) for mortality in the cART group was 1.6 times that of the CM+cART group by Cox proportional hazard model analysis. After controlling for gender, age, marital status, education, and CD4 + T-cell count, the HR was 1.9 times higher in the cART group compared with the CM+cART group (P<0.05). The cross-sectional study investigated 275 AIDS patients. The mean scores of all QOL domains except spirituality/personal beliefs were higher in the CM+cART group than in the cART group (P<0.05)., Conclusions: For AIDS patients, CM could help to prolong life, decrease mortality, and improve QOL. However, there were limitations in the study, so prospective studies should be carried out to confifirm our primary results.

Polyhydroxyalkanoates (PHAs) are promising alternatives to plastics since they have similar properties to polyolefin but are biodegradable and biocompatible. Recently, the conversion of propionate wastewater to PHAs by undefined mixed microbial cultures becomes attractive. However, how microbial community changes remains unclear during the enrichment step, which is critical for a robust PHA-producing system. In this study, PHA-accumulating cultures were enriched under feast/famine condition using propionate-rich substrates. Our results showed that during the first 2 h of the enrichment, dissolved oxygen of cultures increased remarkably until saturation, and amounts of C, N, and chemical oxygen demand of cultures decreased significantly to a very low level. High-throughput sequencing revealed that bacterial populations affiliated with Alphaproteobacteria and Bacteroidetes dominated the cultures enriched. Most of these dominant populations contributed to the conversion of short-chain fatty acids to PHAs. Being fed with the substrate rich in propionate but without nitrogen, the cultures enriched could accumulate nearly 27% PHAs at 72 h with higher content of hydroxyvalerate. Our work reveals the process in which environmental microbes responded to propionate-rich condition and shifted to populations for accumulating PHAs; it also will be helpful to develop an efficient PHA-producing system using propionate-rich waste.

The histopathological features of the middle cerebral artery (MCA) and superficial temporal artery (STA) from moyamoya disease (MMD) and their relationships with gender, age, angiography stage were explored. The causes and the clinical significance of vasculopathy of STA were also discussed. The clinical data and specimens of MCA and STA from 30 MMD patients were collected. Twelve samples of MCA and STA from non-MMD patients served as control group. Histopathological examination was then performed by measuring the thickness of intima and media, and statistical analysis was conducted. The MCA and STA specimens from MMD group had apparently thicker intima and thinner media than those from the control group. There was no significant pathological difference between the hemorrhage group and non-hemorrhage group, and between the males and females in MMD patients. Neither the age nor the digital subtraction angiography (DSA) stage was correlated with the thickness of intima in MCA and STA. MMD is a systemic vascular disease involving both intracranial and extracranial vessels. Preoperative external carotid arteriography, especially super-selective arteriography of the STA, benefits the selection of donor vessel.

Background: A previous study found that brain natriuretic peptide (BNP) inhibited inflammatory pain via activating its receptor natriuretic peptide receptor A (NPRA) in nociceptive sensory neurons. A recent study found that functional NPRA is expressed in almost all the trigeminal ganglion (TG) neurons at membrane level suggesting a potentially important role for BNP in migraine pathophysiology., Methods: An inflammatory pain model was produced by subcutaneous injection of BmK I, a sodium channel-specific modulator from venom of Chinese scorpion Buthus martensi Karsch. Quantitative PCR, Western Blot, and immunohistochemistry were used to detect mRNA and protein expression of BNP and NPRA in dorsal root ganglion (DRG) and dorsal horn of spinal cord. Whole-cell patch clamping experiments were conducted to record large-conductance Ca 2+ -activated K + (BK Ca ) currents of membrane excitability of DRG neurons. Spontaneous and evoked pain behaviors were examined., Results: The mRNA and protein expression of BNP and NPRA was up-regulated in DRG and dorsal horn of spinal cord after BmK I injection. The BNP and NPRA was preferentially expressed in small-sized DRG neurons among which BNP was expressed in both CGRP-positive and IB4-positive neurons while NPRA was preferentially expressed in CGRP-positive neurons. BNP increased the open probability of BK Ca channels and suppressed the membrane excitability of small-sized DRG neurons. Intrathecal injection of BNP significantly inhibited BmK-induced pain behaviors including both spontaneous and evoked pain behaviors., Conclusions: These results suggested that BNP might play an important role as an endogenous pain reliever in BmK I-induced inflammatory pain condition. It is also suggested that BNP might play a similar role in other pathophysiological pain conditions including migraine.

Objective: To observe the effect of Chinese medicine and pharmacy (CMP) on the mortality of senile HIV/AIDS patients as adjunctive therapy., Methods: HIV/AIDS patients of a certain rural area of Hanna Province, who were recruited in national CMP HIV treatment trial program (NTCMTP) in 2004, were enrolled as the CMP treatment group. HIV/AIDS patients in the same village without recruiting in NTCMTP were enrolled as the non-CMP treatment group. Data related to subjects were collected from the database of NTCMTP and National HAART Reporting System. Multiple regression analysis under Cox proportional hazard model was applied to examine the risk factors for death of senile HIV/AIDS patients., Results: A total of 436 HIV/AIDS were enrolled in this study, 204 in the CMP treatment group and 232 in the non-CMP treatment group. There were 70 AIDS-relative deaths in the CMP treatment group, with 8-year mortality rate of 37.74%. There were 111 AIDS-relative deaths in the non-CMP treatment group, with 8-year mortality rate of 48.34%. The 8-year mortality rate was higher in the non-CMP treatment group than in the CMP treatment group (chi2 = 5.136, P < 0.05). Results of univariate Cox proportional hazards regression analysis showed the hazard ratio in the non-CMP treatment group was 1.41 times that of the CMP treatment group (P < 0.05). Result of multivariate Cox proportional hazards regression analysis showed the hazard ratio in the non-CMP treatment group was 1.44 times that of the CMP treatment group (P < 0.05). Besides, gender and marital conditions were significantly associated with death of HIV/AIDS patients., Conclusion: CMP treatment was favorable to lower the mortality rate of senile HIV/AIDS patients, and its objective evaluation awaits for further prospective study.

Subcutaneous injection of BmK I could be adopted to well establish a novel pain model. Moreover, 5-hydroxytryptamine (serotonin, 5-HT) receptor is involved in regulating animal pain-related behaviors. However, the underlying mechanism of 5-HT3R on BmK I-induced pain remains unclear. Animal behavioral testing, RT-PCR and Western blotting were used to yield the following results: first, intraplantar (i.pl.) injection of BmK I (10 μg) induced elevated mRNA and protein levels of 5-HT3AR in bilateral L4-L5 spinal cord; Second, intrathecal (i.t.) injection of ondansetron (a specific antagonist of 5-HT3AR) reduced spontaneous pain responses, attenuated unilateral thermal and bilateral mechanical hypersensitivity elicited by BmK I; Microglia could be activated by BmK I (i.pl.) in both sides of L4-L5 spinal cord, and this effect was reversed by intrathecal pre-treatment with 5-HT3AR antagonist. Meanwhile, the 5-HT3AR in L4-L5 spinal cord was almost co-localized with NeuN (a marker of nerve cell), but not co-expressed with Iba-1 (a marker of microglia). Finally, the expression level of CX3CL1 and CX3CR1 was reduced by intrathecal pre-treatment with ondansetron. Our results indicate that both 5-HT3AR signaling pathway and microglia are activated in the process of induction and maintenance of BmK I-induced pain nociception. Meanwhile, our results suggest that the neuronal 5-HT3AR may communicate with microglia indirectly via CX3CL1 which is involved in regulating the BmK I-induced hyperalgesia and sensitization.

The transplantation of polylactic glycolic acid conduits combining bone marrow mesenchymal stem cells and extracellular matrix gel for the repair of sciatic nerve injury is effective in some respects, but few data comparing the biomechanical factors related to the sciatic nerve are available. In the present study, rabbit models of 10-mm sciatic nerve defects were prepared. The rabbit models were repaired with autologous nerve, a polylactic glycolic acid conduit + bone marrow mesenchymal stem cells, or a polylactic glycolic acid conduit + bone marrow mesenchymal stem cells + extracellular matrix gel. After 24 weeks, mechanical testing was performed to determine the stress relaxation and creep parameters. Following sciatic nerve injury, the magnitudes of the stress decrease and strain increase at 7,200 seconds were largest in the polylactic glycolic acid conduit + bone marrow mesenchymal stem cells + extracellular matrix gel group, followed by the polylactic glycolic acid conduit + bone marrow mesenchymal stem cells group, and then the autologous nerve group. Hematoxylin-eosin staining demonstrated that compared with the polylactic glycolic acid conduit + bone marrow mesenchymal stem cells group and the autologous nerve group, a more complete sciatic nerve regeneration was found, including good myelination, regularly arranged nerve fibers, and a completely degraded and resorbed conduit, in the polylactic glycolic acid conduit + bone marrow mesenchymal stem cells + extracellular matrix gel group. These results indicate that bridging 10-mm sciatic nerve defects with a polylactic glycolic acid conduit + bone marrow mesenchymal stem cells + extracellular matrix gel construct increases the stress relaxation under a constant strain, reducing anastomotic tension. Large elongations under a constant physiological load can limit the anastomotic opening and shift, which is beneficial for the regeneration and functional reconstruction of sciatic nerve. Better regeneration was found with the polylactic glycolic acid conduit + bone marrow mesenchymal stem cells + extracellular matrix gel grafts than with the polylactic glycolic acid conduit + bone marrow mesenchymal stem cells grafts and the autologous nerve grafts.

In the title compound, C12H12N2O2, synthesized by ammonolysis of 3-phenyl-isoxazole-5-carbonyl chloride in di-chloro-methane, the dihedral angle between the isoxazole ring and the phenyl ring is 14.05 (7)°. In the crystal, centrosym-metrically related mol-ecules are linked into dimers by pairs of C-H⋯O hydrogen bonds, generating rings of graph-set motif R 2 (2)(10).

In the title compound, C13H13NO3, the isoxazole ring is approximately coplanar with the phenyl ring, the dihedral angle between their planes being 7.37 (19)°. In the crystal, centrosymmetrically related mol-ecules are linked into dimers by pairs of C-H⋯O hydrogen bonds, generating a ring of graph-set motif R 2 (2)(10).