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This study numerically simulated and investigated the flow field characteristics of a typical dual-pulse solid rocket motor with a soft pulse separation device through thermal insulation ablation under high-temperature dual-pulse erosion. The ablation rate of ethylene -propylene-diene monomer (EPDM) insulator was measured after the experiment. Experimental results were analyzed through scanning electron microscopy and microcomputed tomography. The ablation mechanism of the EPDM insulator under the operation conditions of a dual-pulse solid rocket motor was evaluated by analyzing the results. The results reveal that the internal flow field of the motor with a soft pulse separation device is uniform. The original charred layer existing on the EPDM insulator surface in the first pulse combustor is the decisive factor affecting the final ablation rate of the dual-pulse motor during the second pulse operation, and the ablation characteristic region is easily formed with the exfoliation of the charred layer. The ablation rate difference of the insulator increases with gas velocity.

Introduction: Osteoarthritis (OA) is a dominant cause of morbidity and disability. As a chronic disease, its etiological risk factors and most therapies at present, are empirical and symptomatic. Regenerating gene 4 (Reg4) is involved in cell growth, survival, regeneration, adhesion, and resistance to apoptosis, which are partially thought to be the pathogenic mechanisms of OA. However, the proper role of Reg4 in OA is still unknown. Methods: In this study, a consecutive administration of rhReg4 was applied to normal Sprague- Dawley rats or rats after OA induction. Histological changes and chondrocyte proliferation in the articular cartilage were measured. Results: We found that RhReg4 promotes chondrocyte proliferation in normal rats, and RhReg4 attenuated the severity of OA in rats by promoting chondrocytes’ proliferation in OA rats. Conclusion: In conclusion, recombinant human regenerating gene 4 (rhReg4) attenuates the severity of osteoarthritis in OA animal models and may be used as a new method for the treatment of osteoarthritis.

Existing studies of coal self-ignition and impact frictional sparks do not provide valid support for the analysis of ignition sources in all cases of methane explosions in the gob. In this paper, the explosion in the gob of the Renlou coal mine is used to investigate the piezoelectric effect and ignition characteristics of roof collapse in identifying a new ignition source of gas explosion. Experimental and theoretical analyses conclude that the piezoelectric effect is produced by quartz, which is the main constituent of the roof sandstone. During the loading process, the piezoelectric effect and compressive strength are key factors in the gathering of free charges on rock tips. During rupture, the rock tip retains a large number of charges, forming a ″point-surface″ effect, which triggers an electron avalanche accompanied by an orange-yellow spark lasting over 22 ms, far exceeding the ionization energy and ignition induction period of methane–air mixtures. The piezoelectric effect and compressive strength of the rock cause the generation of electrical sparks, which is the ignition source of the explosion in the gob of Renlou mine II7322.

In reinforcement learning an agent may explore ineffectively when dealing with sparse reward tasks where finding a reward point is difficult. To solve the problem, we propose an algorithm called hierarchical deep reinforcement learning with automatic sub-goal identification via computer vision (HADS) which takes advantage of hierarchical reinforcement learning to alleviate the sparse reward problem and improve efficiency of exploration by utilizing a sub-goal mechanism. HADS uses a computer vision method to identify sub-goals automatically for hierarchical deep reinforcement learning. Due to the fact that not all sub-goal points are reachable, a mechanism is proposed to remove unreachable sub-goal points so as to further improve the performance of the algorithm. HADS involves contour recognition to identify sub-goals from the state image where some salient states in the state image may be recognized as sub-goals, while those that are not will be removed based on prior knowledge. Our experiments verified the effect of the algorithm.

Objective. To investigate the role of curcumin in regulating pathogenesis of pulmonary arterial smooth muscle cells (PASMCs) derived from pulmonary arterial hypertension (PAH) model. Methods. Male Sprague Dawley rats were injected with monocrotaline (MCT) to establish the PAH experimental model. The rats were divided into control group, MCT group, and curcumin group. At the end of the study, hemodynamic data were measured to determine pulmonary hypertension. Proliferation ability of PASMCs, a remodeling indicator of pulmonary artery and right ventricle, was detected. In addition, the morphology and function of mitochondria, antiglycolysis and antiproliferation pathways, and genes were also analyzed. Results. Curcumin may function by reversing MCT-mediated pulmonary vascular remodeling in rats. Curcumin effectively improved pulmonary vascular remodeling, promoted PASMC apoptosis, and protected mitochondrial function. In addition, curcumin treatment suppressed the PI3K/AKT pathway in PASMCs and regulated the expression of antiproliferative genes. Conclusion. Curcumin can improve energy metabolism and reverse the process of PAHS. However, there were side effects of curcumin in MCT-induced rats, suggesting that the dosage should be treated with caution and its toxicological mechanism should be further studied and evaluated.

BACKGROUND Congenital transmesenteric hernia in children is a rare and potentially fatal form of internal abdominal hernia, and no specific clinical symptoms can be observed preoperatively. Therefore, this condition is not widely known among clinicians, and it is easily misdiagnosed, resulting in disastrous effects. CASE SUMMARY This report presents the case of a 13-year-old boy with a chief complaint of abdominal pain and vomiting and a history of duodenal ulcer. The patient was misdiagnosed with gastrointestinal bleeding and treated conservatively at first. Then, the patient’s symptoms were aggravated and he presented in a shock-like state. Computed tomography revealed a suspected internal hernia, extensive small intestinal obstruction, and massive effusion in the abdominal and pelvic cavity. Intraoperative exploration found a small mesenteric defect approximately 3.5 cm in diameter near the ileocecal valve, and there was about 1.8 m of herniated small intestine that was treated by resection and anastomosis. The patient recovered well and was followed for more than 5 years without developing short bowel syndrome. CONCLUSION In this report, we review the pathogenesis, presentation, diagnosis, and treatment of congenital transmesenteric hernia in children.

Generative Adversarial Imitation Learning (GAIL) has been successfully applied to imitation learning in control tasks. However, most GAIL-like approaches require complete and high-quality demonstrations that are scarcely available in practice, which leads to unsatisfactory performances. Researches have proposed algorithms for incomplete demonstrations, which, however, are supposed to be effective only when exceptionally high-quality demonstrations are provided. To solve the problem, the Action-Rank Adversarial Imitation Learning (ARAIL) algorithm is introduced to target the issue of incomplete demonstrations. By reconstructing the standard GAIL framework and introducing the ranker model, ARAIL reshapes the reward function from the discriminator and auxiliary information from the ranker. The primary insight is that the ranker makes a better assessment of missing actions, which in turn helps to learn a better policy. We empirically compare our approach with SOTA algorithms on Atari and Mujoco platforms with imitation learning benchmarks, demonstrating that ARAIL improves both performance and robustness on various levels of incompleteness of actions in demonstrations.

For the control of low-frequency noise in complex external-pressure environment, a new two-dimensional phononic crystal plate which is made of the lead stub with rubber coatings connected by narrow...

The traditional method for detecting cracks in concrete bridges has the disadvantages of low accuracy and weak robustness. Combined with the crack digital image data obtained from bending test of reinforced concrete beams, a crack identification method for concrete structures based on improved U-net convolutional neural networks is proposed to improve the accuracy of crack identification in this article. Firstly, a bending test of concrete beams is conducted to collect crack images. Secondly, datasets of crack images are obtained using the data augmentation technology. Selected cracks are marked. Thirdly, based on the U-net neural networks, an improved inception module and an Atrous Spatial Pyramid Pooling module are added in the improved U-net model. Finally, the widths of cracks are identified using the concrete crack binary images obtained from the improved U-net model. The average precision of the test set of the proposed model is 11.7% higher than that of the U-net neural network segmentation model. The average relative error of the crack width of the proposed model is 13.2%, which is 18.6% less than that measured by using the ACTIS system. The results indicate that the proposed method is accurate, robust, and suitable for crack identification in concrete structures.

The edge authentication of graphs has been studied in the literature because graphs are one of the most widely used data organization structures. The majority of such schemes cannot be used to authenticate general directed graphs (GDGs); other schemes cannot be used for addressing either the issue of dynamic update or the issue of information leakage (such as the existence of nodes/edges and structural relationship of the graph). Also, all the existing schemes do not consider the forward security: if the signer’s secret key has been compromised, all previously generated signatures remain valid. This property provides high-level security protection for authentication schemes. To address these issues, in this work, we propose a forward-secure edge authentication scheme for GDGs. Observe that existing such schemes can only give a proof such that ‘there is an edge between nodes $u$ and $v$’. Our scheme, however, can directly give a proof such that ‘there is no edge between nodes $u$ and $v$’, which makes the function of edge authentication schemes more diverse. Moreover, our proposed scheme is proven to be secure against an adaptive chosen-message adversary in the random oracle model. To show its desirable performance, we analyze the computational costs of our scheme and compare it with other related schemes in terms of features.

Background To develop an effective model of predicting fatal outcomes in the severe coronavirus disease 2019 (COVID-19) patients. Methods Between February 20, 2020 and April 4, 2020, consecutive confirmed 2541 COVID-19 patients from three designated hospitals were enrolled in this study. All patients received chest computed tomography (CT) and serological examinations at admission. Laboratory tests included routine blood tests, liver function, renal function, coagulation profile, C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and arterial blood gas. The SaO2 was measured using pulse oxygen saturation in room air at resting status. Independent high-risk factors associated with death were analyzed using Cox proportional hazard model. A prognostic nomogram was constructed to predict the survival of severe COVID-19 patients. Results There were 124 severe patients in the training cohort, and there were 71 and 76 severe patients in the two independent validation cohorts, respectively. Multivariate Cox analysis indicated that age ≥ 70 years (HR = 1.184, 95% CI 1.061–1.321), panting (breathing rate ≥ 30/min) (HR = 3.300, 95% CI 2.509–6.286), lymphocyte count 9/L (HR = 2.283, 95% CI 1.779–3.267), and interleukin-6 (IL-6) > 10 pg/ml (HR = 3.029, 95% CI 1.567–7.116) were independent high-risk factors associated with fatal outcome. We developed the nomogram for identifying survival of severe COVID-19 patients in the training cohort (AUC = 0.900, 95% CI 0.841–0.960, sensitivity 95.5%, specificity 77.5%); in validation cohort 1 (AUC = 0.811, 95% CI 0.763–0.961, sensitivity 77.3%, specificity 73.5%); in validation cohort 2 (AUC = 0.862, 95% CI 0.698–0.924, sensitivity 92.9%, specificity 64.5%). The calibration curve for probability of death indicated a good consistence between prediction by the nomogram and the actual observation. The prognosis of severe COVID-19 patients with high levels of IL-6 receiving tocilizumab were better than that of those patients without tocilizumab both in the training and validation cohorts, but without difference (P = 0.105 for training cohort, P = 0.133 for validation cohort 1, and P = 0.210 for validation cohort 2). Conclusions This nomogram could help clinicians to identify severe patients who have high risk of death, and to develop more appropriate treatment strategies to reduce the mortality of severe patients. Tocilizumab may improve the prognosis of severe COVID-19 patients with high levels of IL-6.

Recent years has witnessed the success of convolutional neural networks (CNNs) in many machine learning and pattern recognition applications, especially in image recognition. However, due to the increasing model complexity, the parameter redundancy problem arises, and greatly degrades the performance of CNNs. To alleviate this problem, various regularization techniques, such as Dropout, have been proposed and proved their effectiveness. In this paper, we propose a novel adaptive kernel-based weight decorrelation (AKWD) framework, in order to regularize CNNs for better generalization. Different from existing works, the correlation between paring weights is measured by the cosine distance defined in RKHS associated with a specific kernel. The case with the well-known Gaussian kernel is investigated in detail, where the bandwidth parameter is adaptively estimated. By regularizing CNN models of different capacities using AKWD, better performance is achieved on several benchmark databases for both object classification and face verification tasks. In particular, when Dropout or BatchNorm is present, even higher improvements are obtained using the proposed AKWD, that demonstrates a good compatibility of the proposed regularizer with other regularization techniques.

BACKGROUND Blepharoplasty is the most common type of plastic surgery, used to improve most of the eyelid skin sag caused by aging. In the past, local infiltration anesthesia was widely used in blepharoplasty. Tumescent local analgesia (TLA) is safe and reliable method for anesthesia, even children can use this method. AIMS This research aimed to systematically compare the differences between conventional local infiltration anesthesia and TLA in blepharoplasty. PATIENTS/METHODS One hundred and seventy-eight bilateral upper blepharoplasty patients participated in this research. Visual analog scale (VAS) was employed to evaluate the postoperative pain in the patients. Periorbital appearances are based on light photography and judged by both medical and nonmedical panel. RESULTS The use of TLA decreased the surgery duration but had no influence on the other surgery characteristics of upper blepharoplasty. Using TLA for anesthesia in bilateral upper blepharoplasty generated less pain than using local infiltration anesthesia. At day 7 after upper blepharoplasty, the rate of generation of both ecchymosis and erythema in normal anesthesia (NA) side were higher than in TLA side. The satisfaction of patients after upper blepharoplasty was not influenced by the use of different anesthesia methods. CONCLUSION Compared with the normal anesthesia technology, the use of TLA in the upper blepharoplasty shortened the surgery duration, alleviated the postoperative pain, and mitigated the generation of ecchymosis and erythema. So, TLA is suitable for the performance of anesthesia in blepharoplasty.

In the multi-effect evaporation salt making process, the smooth operation of the salt making process is crucial. As the salt production process continues, many unstable factors will cause the salt production process not to proceed smoothly. These factors can be discovered in advance by predicting the salt production data, thus, it is of great significance to predict the multi-effect evaporation salt production data. In the process of multi-effect evaporation and salt production, the multiple salt-making devices make the influence between the parameters closer, and the influence of a single parameter on itself is sometimes ductile. Therefore, the data of multi-effect evaporation and salt production have the characteristics of high dimensions, high complexity and temporal information. If the historical salt production data is used for data prediction directly, the prediction model will take a long time and the prediction effect is not good. Thus, how to predict the multi-effect evaporation salt production data is the main research problem of this paper. In view of the above problems, according to the characteristics of multi-effect evaporation salt production data, this paper analyzes and improves the self encoder for feature extraction of multi effect-evaporation salt production data, so as to solve the problem of high dimensions and high complexity of salt production data. On this basis, combined with the time-series information contained in the salt production data, a multi-effect evaporation salt production data prediction model is proposed based on long-term and short-term memory cycle neural network to solve the prediction problem of time-series salt production data. Experiments show that the prediction model can predict and prevent the problems in salt production line in advance. It has a certain theoretical research value and application value in the intelligent production process and production line optimization of salt chemical industry.

Perovskite single-crystal (SC) or quasi-single-crystal (QSC) films are promising candidates for excellent performance of photoelectric devices. However, it is still a great challenge to fabricate large-area continuous SC or QSC films with proper thickness. Herein, we propose a pressure-assisted high-temperature solvent-engineer (PTS) strategy to grow large-area continuous MAPbI3 QSC films with uniformly thin thickness and orientation. Dramatic grain growth (∼100 μm in the lateral dimension) and adequate boundary fusion are realized in them, vastly eliminating the grain boundaries. Thus, remarkable diminution of the trap density (ntrap: 7.43 × 1011 cm-3) determines a long carrier lifetime (τ2: 1.7 μs) and superior photoelectric performance of MAPbI3-based lateral photodetectors; for instance, an ultrahigh on/off ratio (>2.4 × 106, 2 V), great stability, fast response (283/306 μs), and high detectivity (1.41 × 1013) are achieved. The combination properties and performance of the QSC films surpass most of the reported MAPbI3. This effective approach in growing perovskite QSC films points out a novel way for perovskite-based optoelectronic devices with superior performance.

OBJECTIVES The efficacy of pulse index contour continuous cardiac output (PiCCO) monitoring in patients with constrictive pericarditis undergoing pericardiectomy remains unclear. The goal of this study was to explore whether PiCCO monitoring could improve clinical outcomes in these patients. METHODS We retrospectively studied 74 patients with constrictive pericarditis undergoing pericardiectomy and assigned them to a PiCCO group and a control group. Postoperative and survival outcomes were compared between the 2 groups. RESULTS There were 33 (44.6%) cases in the PiCCO group and 41 (55.4%) cases in the control group. The baseline characteristics were comparable between the 2 groups. In comparison to the control group, the PiCCO group showed more intraoperative fluid infusion (P = 0.003), higher postoperative central venous pressure (P = 0.007) and lower levels of postoperative brain natriuretic peptide (P = 0.021). The incidence of postoperative complications (P = 0.004) including cardiac complications (P = 0.033) was also lower in the PiCCO group. Despite no difference in survival outcomes, duration of chest drainage (P = 0.032), length of stay in the intensive care unit (P CONCLUSIONS This study confirmed the clinical significance of PiCCO monitoring in the enhanced recovery of patients with constrictive pericarditis undergoing pericardiectomy and provided new evidence for applying PiCCO monitoring in these patients.

Wet age-related macular degeneration (AMD), which can cause progressive blindness, is characterised by choroid neovascularization (CNV) in the macular area. Although close attention has been paid to AMD, and anti-vascular endothelial growth factor (VEGF) drugs are available, its complex pathogenesis is still elusive. Tie2-expressing macrophages (TEMs) have been found to promote angiogenesis in remodel tissues and tumours. This study aimed to elucidate the role of macrophage Tie2 signalling in laser-induced CNV (LCNV). We observed that TEMs were responsible for the severity of CNV. Mechanistically, TEM deletion resulted in impaired LCNV due to the suppression of inflammatory angiogenesis and the promotion of apoptosis. We also observed that TEMs prevented apoptosis of b.End3 cells, but promoted their migration, proliferation and tube formation via VEGF, extracellular signal-regulated kinase (ERK) and v-akt murine thymoma viral oncogene (AKT)-dependent signalling pathways. The flow cytometry results comparing dry AMD patients and healthy controls with wet AMD patients showed that the percentage of Tie2+CD14+ cells was higher in the wet AMD patients’ peripheral blood. This study demonstrates that Tie2 expression by macrophages intensifies CNV in LCNV murine models, thereby proposing an additional intervention option to inhibit CNV.

The functional and cosmetic outcomes of defect reconstruction of the lower eyelid are very important because of the specialised functions and complex anatomy of this region. Several techniques can be used to reconstruct the anterior lamella defect of the lower eyelid. We aimed to introduce a new technique for reconstructing the lateral or medial anterior lamella defects while preventing ectropion and gaining good appearance. The local temporal island flap combined with orbicularis oculi muscle flap was designed. From 1 January 2014 to 1 January 2018, the local temporal island flap combined with orbicularis oculi muscle flap was designed to reconstruct the anterior lamella defects of the lower eyelids in 10 patients. The cause of the defects, its location, the postoperative cosmetic and functional results, and complications were recorded and analysed. The survival rate of the flaps was 100% postoperatively. No ectropion or other complications were observed during the follow-up period. The aesthetic and functional result was satisfactory. The local temporal island flap combined with orbicularis oculi muscle flap may be an alternative for a single-stage reconstruction of anterior lamella defects of the lower eyelid with good functional and cosmetic results.

Background To investigate the loco-regional progression-free survival (LPFS) of intensity-modulated radiotherapy (IMRT) with different fraction sizes for locally advanced non-small-cell lung cancer (LANSCLC), and to apply a new radiobiological model for tumor control probability (TCP). Methods One hundred and three LANSCLC patients treated with concurrent radiochemotherapy were retrospectively analyzed. Factors potentially predictive of LPFS were assessed in the univariate and multivariate analysis. Patients were divided into group A (2.0 ≤ fraction size Results With a median follow-up of 22.1 months, the median LPFS was 23.8 months. Fraction size was independently prognostic of LPFS. The median LPFS of group A, B and C was 13.8, 35.7 months and not reached, respectively. Using the new LQRG/TCP model, the average absolute and relative fitting errors for LPFS were 6.9 and 19.6% for group A, 5.5 and 8.8% for group B, 6.6 and 9.5% for group C, compared with 9.5 and 29.4% for group A, 16.6 and 36.7% for group B, 24.8 and 39.1% for group C using the conventional LQ/TCP model. Conclusions Hypo-fractionated IMRT could be an effective approach for dose intensification in LANSCLC. Compared with conventional LQ model, the LQRG model showed a better performance in predicting follow-up time dependent LPFS.

Recently, many methods based on deep learning (DL) have been used for hyperspectral image (HSI) classification and achieved good performance. But such approaches often need numerous labelled traini...

The combination of area-scan camera and 2D laser rangefinder (LRF) can capture both textural and geometrical information from a scene at the same time, and has been widely used in various fields. Due to the differences of the installation position and acquisition mode, calibrating the extrinsic parameters, including the rotation and translation, of two sensors is necessary for fusing the camera image and LRF data. In this paper, a simple and flexible extrinsic calibration method is proposed by only acquiring a checkerboard trihedron once. Using checkerboard trihedron as a mobile referenced control field, the proposed method includes three steps to calibrate the extrinsic parameters. First, the rotation and translation between the trihedron and LRF are solved with a simplified perspective-three-point (P3P) solution; Second, using the collinear equation of checkerboard corners and their pixels in the image, the camera is calibrated with respect to the trihedron; Third, combining the last two steps, the rotation and translation parameters between the camera and LRF are finally calibrated with the intermediate referenced trihedron. After a lot of simulation and real experiments, the proposed method has been demonstrated to have the advantages of simple operation, strong robustness and high accuracy in real experiment.

The white spot syndrome virus (WSSV) causes mass mortalities in the aquaculture of shrimps worldwide. The mud shrimp Austinogebia edulis (Ngoc-Ho & Chan, 1992) is an economically important sea food item occurring along the west coast of Taiwan. While the population of A. edulis began to decrease with some fluctuations in the last decade, the current study aims to discover the causes for such sporadic population decline. This study explores the effects of microbial pathogens and innate immunity on the populations of A. edulis. Here, we report firstly about WSSV infection of A. edulis from the coastal zone of western Taiwan which is one of the possible causes of population decrease of A. edulis in Shengang. However, WSSV infection is not the only reason for its population decrease because a similar infection rate of WSSV was found in Wangong. Population changes may be related to both environmental pollution stress and WSSV. Both factors likely caused a massive reduction of hemocytes and an abnormal increase of phenoloxidase and superoxide dismutase activity, which were spectrophotometrically measured. Since there is no effective way to treat WSSV infection, improving the coastal environment appears the most effective way to increase the population size of feral shrimps.

Inflammation is broadly recognized as an important factor in the pathogenesis of acute kidney injury (AKI), but pharmacological approaches to alleviate inflammation in AKI have not been proved successful in clinical trials. Macrophage infiltration into renal tissue promotes inflammatory responses that contribute to the pathogenesis of AKI. Suppression of renal tissue inflammatory responses is postulated to improve renal injury of patients and animals. Rhodomeroterpene (RMT) is a novel meroterpenoid isolated from the Rhododendron genus that was shown to exert anti-inflammatory action in vivo or in vitro in this study. We investigated the treatment effects of RMT on LPS-induced sepsis and two different AKI models. The results showed that pretreatment with RMT (30 mg kg-1 d-1 , ip, for 3 days) significantly inhibited acute inflammatory responses in LPS-induced septic mice. In both renal ischemia-reperfusion injury (I/R) and sepsis-induced AKI models, RMT (30 mg kg-1 d-1 , ip, for 3 days) ameliorated renal function and injury and alleviated inflammation by reducing the infiltration of immune cells, including macrophages and neutrophils. Furthermore, our study demonstrated that RMT inhibits inflammatory responses in macrophages. The anti-inflammatory effects of RMT may be due to the inactivation of the IKK/NF-κB and PI3K/PDK1/Akt inflammatory signaling pathways in macrophages. Collectively, our findings indicate that RMT ameliorates renal injury and alleviates the renal inflammatory state in different AKI models, suggesting that RMT may be a potential agent for the treatment of AKI.

Statins is widely used in clinical practice as lipid-lowering drugs and has been proven to be effective in the treatment of cardiovascular, endocrine, metabolic syndrome and other diseases. The latest preclinical evidence shows that statins have anti-proliferation, pro-apoptotic, anti-invasion and radiotherapy sensitization effects on tumor cells, suggesting that statins may become a new type of anti-tumor drugs. For a long time, mevalonate pathway has been proved to play a supporting role in the development of tumor cells. As an effective inhibitor of mevalonate pathway, statins have been proved to have a direct auxiliary anti-tumor effect in a large number of studies. In addition, anti-tumor effects of statins through ferroptosis, pyroptosis, autophagy and tumor microenvironment (TME) have also been gradually discovered. However, the specific mechanism of the antitumor effect of statins in the tumor microenvironment has not been clearly elucidated. Herein, we reviewed the antitumor effects of statins in tumor microenvironment, focusing on hypoxia microenvironment, immune microenvironment, metabolic microenvironment, acid microenvironment and mechanical microenvironment.

Previous solutions on security and privacy in Industrial Internet of Things (IIoT) focus primarily on the data or the deployment and communication problems of devices. However, the management and authentication of IoT devices for IIoT systems has received less attention. To facilitate the research on this area, we take the IIoT control system as an example. It is crucial to authenticate the relationships among devices to ensure that data can only be accessed by authenticated parties. In this paper, we provide a feasible solution to address the aforementioned issue. Considering that a directed graph can be used to intuitively represent such relationships, we present a dynamically updatable privacy-preserving authentication scheme for general directed graphs. Specifically, our scheme is based on the cryptographic accumulator and an underlying standard digital signature scheme. We formalize its security notions and prove its security under the adaptive chosen-message attacks. The efficiency of our scheme is evaluated in order to illustrate its practically for real-world applications.

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease that eventually leads to joint deformities and loss of joint function. Previous studies have demonstrated a close relationship between autophagy and the development of RA. Although autophagy and apoptosis are two different forms of programmed death, the relationship between them in relation to RA remains unclear. In this study, we explored the effect of autophagy on apoptosis of articular chondrocytes in vivo and in vitro. Adjuvant arthritis (AA) and acid‐induced primary articular chondrocyte apoptosis were used as in vivo and in vitro models, respectively. Articular chondrocyte autophagy and apoptosis were both observed dynamically in AA rat articular cartilage at different stages (15 days, 25 days and 35 days). Moreover, chondrocyte apoptosis and articular cartilage injury in AA rats were increased by the autophagy inhibitor 3‐methyladenine (3‐MA) and decreased by the autophagy activator rapamycin. In addition, pre‐treatment with 3‐MA increased acid‐induced chondrocyte apoptosis, while pre‐treatment with rapamycin reduced acid‐induced chondrocyte apoptosis in vitro. These results suggest that autophagy might be a potential target for the treatment of RA.

The structural resilience of a steel frame with posttensioned (PT) connections under a column-removal scenario is numerically investigated. Four high-fidelity PT connections finite element (FE) models are developed and compared with the experimental results in the literature, and the developed models describe the behavior of the connections accurately. A method to evaluate middle column removal scenario in a one-story, two-bay frame with PT connections is proposed. The corresponding resisting mechanisms are quantitatively evaluated, which consists of beam mechanism contributed mainly by beam arching action and strand catenary mechanism. A three-dimensional FE model of beam-column substructure with PT connections are developed considering the effect of increasing vertical displacement. Vertical responses associated with different working cases are assessed and the influences of strands, beams and top-seat angles are investigated. In addition, a quantitative evaluation index of the structural resilience under a column-removal scenario for a PT steel frame is proposed based on vertical response displacement. A resilience-based design approach is proposed for the practical engineering design.

Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are used to help diagnose heart disease by recording the heart’s activity. However, automated medical-aided diagnosis with computers usually requires a large volume of labeled clinical data without patients' privacy to train the model, which is an empirical problem that still needs to be solved. To address this problem, we propose a generative adversarial network (GAN), which is composed of a bidirectional long short-term memory(LSTM) and convolutional neural network(CNN), referred as BiLSTM-CNN,to generate synthetic ECG data that agree with existing clinical data so that the features of patients with heart disease can be retained. The model includes a generator and a discriminator, where the generator employs the two layers of the BiLSTM networks and the discriminator is based on convolutional neural networks. The 48 ECG records from individuals of the MIT-BIH database were used to train the model. We compared the performance of our model with two other generative models, the recurrent neural network autoencoder(RNN-AE) and the recurrent neural network variational autoencoder (RNN-VAE). The results showed that the loss function of our model converged to zero the fastest. We also evaluated the loss of the discriminator of GANs with different combinations of generator and discriminator. The results indicated that BiLSTM-CNN GAN could generate ECG data with high morphological similarity to real ECG recordings.

Protandrous black porgy (Acanthopagrus schlegelii) is a popular and valuable commercial marine fish in China and East Asian countries. Controlling and managing its breeding has been an imperative step towards obtaining a sustainable supply of this fish in aquaculture production systems. Therefore, study on the molecular mechanisms of sex change in black porgy has both scientific and commercial importance. Previously, we identified some candidate genes related to sex determination and differentiation from a high-quality genome assembly of the black porgy. In the present study, transcriptome sequencing of developmental gonads (including testis, ovotestis and ovary) of black porgy was performed to further investigate the sex-change mechanisms. Our results showed that the highly expressed male-related genes (dmrt1, piwi1, piwi2, sox9, sox30 and amh) at the male phase were significantly down-regulated to a substantial degree at the intersexual stage, and the female-related genes (jnk1, vasa, wnt4, figla and foxl2) were distinctly up-regulated when the fish grows into a female adult, suggesting the potential roles of these genes in sex change of the black porgy. These data also support a previous hypothesis that the femaleness will be switched on when the testis is entering the degenerated stage through the diminished dmrt1 expression. Our transcriptome data provide a very useful genomic resource for future studies on sex change and practical aquaculture in the black porgy.

Background Human hepatocellular carcinoma (HCC) lacks effective curative therapy and there is an urgent need to develop a novel molecular-targeted therapy for HCC. Selective tyrosine kinase inhibitors have shown promise in treating cancers including HCC. Tyrosine kinases c-Met and Trks are potential therapeutic targets of HCC and strategies to interrupt c-Met and Trks cross-signaling may result in increased effects on HCC inhibition. Methods The effects of Indo5 on c-Met and Trks activity were determined with in vitro kinase activity assay, cell-based signaling pathway activation, and kinases-driven cell transformation. The in vivo anti-tumor activity was determined with xenograft mice and liver orthotopic mice models. The co-expression of c-Met and TrkB in 180 pairs of HCC and adjacent normal tissues were detected using immunohistochemical staining. Results Indo5, a novel lead compound displayed biochemical potency against both c-Met and Trks with selectivity over 13 human kinases. Indo5 abrogated HGF-induced c-Met signaling activation and BDNF/NGF-induced Trks signal activation, c-Met or TrkB-mediated cell transformation and migration. Furthermore, Indo5 significantly decreased the growth of HCC cells in xenograft mice and improved the survival of mice with liver orthotopic tumors. In addition, co-expression of c-Met and TrkB in HCC patients was a predictor of poor prognosis, and combined inhibition of c-Met and TrkB exerted a synergistic suppressive effect on HCC. Conclusions These findings indicate that Indo5 is associated with marked suppression of c-Met and Trks co-expressing HCC, supporting its clinical development as an antitumor treatment for HCC patients with co-active c-Met and Trks signaling. Electronic supplementary material The online version of this article (10.1186/s13046-019-1104-4) contains supplementary material, which is available to authorized users.

Faced with the explosive demand of real-world applications, spatial crowdsourcing has attracted much attention, in which task assignment algorithms take the dominant role in the past few years. On the one hand, most recent studies concentrate on maximizing the overall benefits of the platform, ignoring the fact that user experience also plays an essential role in task allocation. On the other hand, they focus on matching, that is, how to assign tasks, rather than batching, that is, when to make assignment. In fact, user experience also depends on batching, but this is largely overlooked by current studies. In this paper, we propose a self-adaptive batching mechanism to enhance user experience in spatial crowdsourcing. With appropriate start-up timestamps, previous matching methods can perform better. Multi-armed bandit algorithm in reinforcement learning is adopted to split the batch dynamically according to historical current states. Extensive experimental results on both real and synthetic datasets demonstrate the effectiveness and efficiency of the proposed approach.

Traditional sensor nodes ignore the packet loss rate during information transmission and the access control security problem caused by server utilization when uploading data. To solve the problem, we propose a SARSA based access control method with approximation by TileCoding (SACT), which takes the sensor packet loss rate and the server error rate into account. The network state is estimated by the packet loss rate and variable bit error rate to get a server access control strategy to improve security performance. The eventual strategy complies with the minimum information loss and the maximum server utilization. Results of experiments show that the algorithm is capable of achieving good results in the total amount of information received by the server system. The SACT improves the server utilization rate and the overall security performance of the network.

Compared to multicomponent white light-emitting sources, a single-component luminophor of direct white-light emission may greatly simplify the manufacture of lighting devices and produce white light with better stability and reproducibility. On the other hand, the crystallization of luminescent materials commonly weakens their luminous efficiency. Therefore, scientific researchers have to fabricate amorphous films while constructing light-emitting diodes, although it is a truism that the crystalline films exhibit higher charge mobilities. In this work, A novel mononuclear gold(I) phosphor is reported, consisting of single-component white-emissive crystals, which exhibit bright phosphorescence at room temperature and have an outstanding luminescence quantum yield of up to 88.2%. Ideal mixing of blue luminescence and green luminescence affords a high-efficiency white luminescence.

Current evidence indicates that carotid atherosclerosis is an independent risk factor for cognitive impairment. Serum metabolomic analysis holds significant promise for uncovering the relationship between carotid atherosclerosis and cognitive impairment. In this study, we aimed to evaluate the profiling of serum carbonyl compounds in subclinical carotid atherosclerosis (SCA) patients and to explore the relationship between serum carbonyl compounds and cognitive performance. We enrolled 51 SCA patients and 45 healthy control individuals using carotid ultrasound assessment. All the participants were subjected to a neuropsychological assessment and their fasting serum samples were collected for untargeted stable isotope-labeling strategy combined with liquid chromatography-double precursor ion scan-mass spectrometry analysis. Compared with the control, the SCA group showed lower scores in global cognition, immediate memory, verbal fluency, executive function, and visual attention. For the isotope-labeling strategy combined with liquid chromatography-double precursor ion scan-mass spectrometry analysis, 149 potential carbonyl candidates were discovered in the pooled serum. In the SCA serum, 41 carbonyl compounds showed significantly increased levels and 14 carbonyl compounds showed significantly decreased levels. In addition, six carbonyl compounds involved in the oxidation of polyunsaturated fatty acids and vitamin E were correlated with cognitive performance. A negative correlation was observed between cognitive performance and the levels of octanal, nonanal, α-tocopherolquinone, and heptanal, respectively. A positive correlation was observed between cognitive performance and the levels of acetophenone and 1-(3-aminopropyl)-4-aminobutanal, respectively. In summary, the SCA individuals have poor cognitive performance, which may be reflected by aberrant serum carbonyl compound profiles.

BackgroundAccurate evaluation of lymph node (LN) status is critical for determining the treatment options in patients with non-small cell lung cancer (NSCLC). This study aimed to develop and validate a 18F-FDG PET-based radiomic model for the identification of metastatic LNs from the hypermetabolic mediastinal–hilar LNs in NSCLC.MethodsWe retrospectively reviewed 259 patients with hypermetabolic LNs who underwent pretreatment 18F-FDG PET/CT and were pathologically confirmed as NSCLC from two centers. Two hundred twenty-eight LNs were allocated to a training cohort (LN = 159) and an internal validation cohort (LN = 69) from one center (7:3 ratio), and 60 LNs were enrolled to an external validation cohort from the other. Radiomic features were extracted from LNs of PET images. A PET radiomics signature was constructed by multivariable logistic regression after using the least absolute shrinkage and selection operator (LASSO) method with 10-fold cross-validation. The PET radiomics signature (model 1) and independent predictors from CT image features and clinical data (model 2) were incorporated into a combined model (model 3). A nomogram was plotted for the complex model, and the performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness.ResultsThe area under the curve (AUC) values of model 1 were 0.820, 0.785, and 0.808 in the training, internal, and external validation cohorts, respectively, showing good diagnostic efficacy for lymph node metastasis (LNM). Furthermore, model 2 was able to discriminate metastatic LNs in the training (AUC 0.780), internal (AUC 0.794), and external validation cohorts (AUC 0.802), respectively. Model 3 showed optimal diagnostic performance among the three cohorts, with an AUC of 0.874, 0.845, and 0.841, respectively. The nomogram based on the model 3 showed good discrimination and calibration.ConclusionsOur study revealed that PET radiomics signature, especially when integrated with CT imaging features, showed the ability to identify true and false positives of mediastinal–hilar LNM detected by PET/CT in patients with NSCLC, which would help clinicians to make individual treatment decisions.

ObjectiveTo examine the clinical characteristics of autoimmune encephalitis associated with the contactin-associated protein-2 (CASPR2) antibody.Materials and MethodsMedical records of all patients diagnosed with CASPR2 antibody-associated encephalitis were retrospectively analysed. Data regarding demographic features, neurological symptoms and signs, laboratory tests, imaging results, treatments, and prognosis were collected.ResultsA total of 25 patients aged from 3 to 79 years old were enrolled in this study, with a median age of 43. Eight of 25 (32%) were female, and 17 of 25 (68%) were male. The median age of symptom onset was 42 years old with the course of disease from onset to hospital admission ranging from 2 days to 6 months (median was 17 days). Six patients (6/25) had fever as an onset symptom. During the course of disease, cognitive disturbance was the most common symptom, which was observed in 17 patients (17/25) in total. Eight patients (8/25) met the criteria for limbic encephalitis. Epileptic seizure occurred in six of these eight patients. Four patients (4/25) were diagnosed as Morvan syndrome. All patients were positive for anti-CASPR2 antibody in the serum (1:10–1:300). In six patients, antibodies were detected both in the blood and CSF (1:32–1:100). White blood cell (WBC) counts in the CSF were elevated in eight patients (8/25). The concentration of proteins in CSF increased in 10 patients (ranging from 480 to 1,337.6 mg/dl), decreased in seven patients (ranging from 23.2 to 130.5 mg/dl) and remained at a normal range in the other eight patients (ranging from 150 to 450 mg/dl). Abnormal electroencephalogram (EEG) activities included slow background activity and epileptic patterns. Abnormal signals in the bilateral hippocampus were detected by magnetic resonance imaging (MRI) in three patients presenting cognitive disturbance. In one patient who had limbic encephalitis, increased metabolism of bilateral basal ganglia and the mesial temporal lobe was revealed by PET-CT. Eleven of 15 patients receiving immunotherapy experienced varying degrees of improvement. Relapse occurred in four of 25 patients (4/25) after 2 months.ConclusionCASPR-antibody-mediated autoimmune encephalitis is characterized by diverse clinical manifestations. The most prominent conclusion revealed by this retrospective analysis is the involvement of both central and peripheral nerve systems, as well as a lower relapse rate, a good response to immunotherapy, and favorable short-term prognosis after treatment was also demonstrated. Besides, additional work is necessary to evaluate the long-term prognosis.

With the progress of medical technology, biomedical field ushered in the era of big data, based on which and driven by artificial intelligence technology, computational medicine has emerged. People need to extract the effective information contained in these big biomedical data to promote the development of precision medicine. Traditionally, the machine learning methods are used to dig out biomedical data to find the features from data, which generally rely on feature engineering and domain knowledge of experts, requiring tremendous time and human resources. Different from traditional approaches, deep learning, as a cutting-edge machine learning branch, can automatically learn complex and robust feature from raw data without the need for feature engineering. The applications of deep learning in medical image, electronic health record, genomics, and drug development are studied, where the suggestion is that deep learning has obvious advantage in making full use of biomedical data and improving medical health level. Deep learning plays an increasingly important role in the field of medical health and has a broad prospect of application. However, the problems and challenges of deep learning in computational medical health still exist, including insufficient data, interpretability, data privacy, and heterogeneity. Analysis and discussion on these problems provide a reference to improve the application of deep learning in medical health.

In view of the influence of variability of low-frequency noise frequency on noise prevention in real life, we present a novel two-dimensional tunable phononic crystal plate which is consisted of lead columns deposited in a silicone rubber plate with periodic holes and calculate its bandgap characteristics by finite element method. The low-frequency bandgap mechanism of the designed model is discussed simultaneously. Accordingly, the influence of geometric parameters of the phononic crystal plate on the bandgap characteristics is analyzed and the bandgap adjustability under prestretch strain is further studied. Results show that the new designed phononic crystal plate has lower bandgap starting frequency and wider bandwidth than the traditional single-sided structure, which is due to the coupling between the resonance mode of the scatterer and the long traveling wave in the matrix with the introduction of periodic holes. Applying prestretch strain to the matrix can realize active realtime control of low-frequency bandgap under slight deformation and broaden the low-frequency bandgap, which can be explained as the multiple bands tend to be flattened due to the localization degree of unit cell vibration increases with the rise of prestrain. The presented structure improves the realtime adjustability of sound isolation and vibration reduction frequency for phononic crystal in complex acoustic vibration environments.

With the popularity of wireless network and mobile devices, spatial crowdsourcing has gained much attention from both academia and industry. One of the critical components in spatial crowdsourcing is task-worker matching, where workers are assigned to tasks to meet some pre-defined objectives. Previous works generally assume that the locations of tasks are known in advance. However, this does not always hold, since in many real world applications where to put tasks is not specific and needs to be determined on the fly. In this paper, we propose Incentive-aware Task Location (ITL), a novel problem in spatial crowdsourcing. Given a location-unspecific task with a fixed budget, the ITL problem seeks multiple locations to place the task and allocates the given budget to each location, such that the number of workers who are willing to participate the task is maximized. We prove that the ITL problem is NP-hard and propose three heuristic methods to solve it, including even clustering, uneven clustering and greedy location methods. Through extensive experiments on a real dataset, we demonstrate the efficiency and effectiveness of the proposed methods.

Studies aiming to identify the significance of the carotid artery perivascular fat density are limited. The present study investigated the distribution pattern of pericarotid fat and its association with imaging markers of cerebral small vessel disease (CSVD). In total, 572 subjects who underwent both neck computed tomography angiography and cranial magnetic resonance imaging were analyzed. The pericarotid fat density near the origin of the internal carotid artery (ICA) and imaging markers of CSVD, such as lacunes, white matter hyperintensities (WMHs) and dilated perivascular spaces (PVSs), were assessed. We found that an increased pericarotid fat density was associated with the presence of lacunes and a higher WMH grade in all subjects, but in the patients with acute ischemic stroke, there was a difference only among the WMH grades. There was no significant difference in the pericarotid fat density in different grades of PVSs. The patients with acute ischemic stroke had a significantly higher mean pericarotid fat density than those without stroke. In conclusion, our study provides evidence suggesting that an increased pericarotid fat density is associated with the presence and degree of WMHs and lacunes. Our findings suggested that features that appear to extend beyond the vessel lumen of the ICA may be linked to CSVD.

Few studies have described chimeric antigen receptor-modified T cell (CAR-T) therapy for central nervous system (CNS) B-cell acute lymphocytic leukemia (B-ALL) patients due to life-threatening CAR-T-related encephalopathy (CRES) safety issues. In this study, CAR-Ts targeting CD19 with short hairpin RNA (shRNA)-IL-6 gene silencing technology (ssCART-19s) were prepared. We conducted a phase 1 clinical trial (ClinicalTrials.gov number, NCT03064269). Three patients with relapsed CNS B-ALL were enrolled, conditioned with the fludarabine and cyclophosphamide for lymphocyte depletion and infused with ssCART-19s for three consecutive days. Clinical symptoms and laboratory examinations were monitored. After ssCART-19 treatment, three patients' symptoms resolved almost entirely. Brain leukemic infiltration reduced significantly based on magnetic resonance imaging (MRI), and there were no leukemic blasts in cerebrospinal fluid (CSF), which was confirmed by cytological and molecular examinations. Additionally, increases in the levels of cytokines and immune cells were observed in the CSF of all patients. Only grade 1 cytokine release syndrome (CRS) manifesting as fever was noted in patients. In conclusion, CAR-Ts with shRNA-IL-6 gene knockdown migrated into the CNS, eradicated leukemic cells and elevated cytokines in CSF with mild, acceptable side effects.

Background Anti-tumour necrosis factor (TNF)-α drugs are used by increasing numbers of reproductive-age women. Although the neonatal outcomes have been described, there are concerns regarding the risk of infection in offspring following exposure to anti-TNF-α. Methods A literature search was conducted using Pubmed, EMBASE, and the Cochrane Database, from inception through August 2020. We evaluated the risk of infection in autoimmune disease (AID) offspring unexposed to anti-TNF-α compared to AID offspring exposed to anti-TNF-α, as well as to unexposed non-AID offspring. Results Our primary analysis showed that both AID offspring unexposed to anti-TNF-α [risk ratio (RR) 1.09; 95% confidence interval (CI), 1.03–1.16; I2=0%] and AID offspring exposed to anti-TNF-α (RR 1.39; 95% CI, 1.2–1.61; I2=0%] was associated with an increased risk of infection during the first year of life compared with the unexposed non-AID offspring. However, our secondary analysis demonstrated that AID offspring exposed to anti-TNF-α was not associated with an increased risk of infection when compared with AID offspring unexposed to anti-TNF-α (RR=1.1; 95% CI, 0.86–1.4). Conclusion Our results suggest that in utero exposure to anti-TNF-α does not appear to increase the risk of infection during the first year of life in the offspring; however, AID itself was associated with a marked excess risk of infection in the children.

Background Shivering is a common side effect in women having cesarean delivery (CD) under spinal anesthesia, which can be bothersome to the patient, and it can also interfere with perioperative monitoring. In several studies, the intrathecal (IT) addition of a lipophilic opioid to local anesthetics has been shown to decrease the incidence of shivering. Objective We performed this network meta-analysis to evaluate the effects of intrathecal lipophilic opioids in preventing the incidence of shivering in patients undergoing CD. Methods This review was planned according to the PRISMA for Network Meta-Analysis (PRISMA-NMA) guidelines. An English literature search of multiple electronic databases was conducted. We included randomized controlled trials (RCTs) that reported on the incidence of shivering, with study groups receiving either IT fentanyl, sufentanil, or meperidine in women undergoing CD under spinal anesthesia. Quality of the studies was assessed using the modified Oxford scoring system. Using random-effects modeling, dichotomous data were extracted and summarized using odds ratio (OR) with a 95% credible interval (CrI). Statistical analysis was conducted using R studio version 1.0.153 - Inc. Results Twenty-one studies consisting of 1433 patients (Control group: 590 patients in twenty-one studies; Fentanyl group:199 patients in seven studies; Sufentanil group: 156 patients in five studies; Meperidine group: 488 patients in ten studies) met the inclusion criteria for this systematic review investigating the effect of intrathecal lipophilic opioids in preventing the incidence of shivering in women undergoing cesarean delivery under spinal anesthesia. Methodological validity scores ranged from 3 to 7. The Bayesian mixed network estimate showed the incidence of shivering was significantly lower with IT fentanyl (pooled odds ratio (OR): 0.13; 95% credible interval (CrI): 0.04 to 0.35; P = 0.0004) and IT meperidine (OR: 0.12; 95% CrI: 0.05 to 0.29; P P = 0.23). The IT fentanyl group had a significantly lower incidence of intraoperative discomfort [Risk Ratio (RR): 0.19; 95% CI: 0.10–0.35; P P = 0.03) The IT meperidine group had a significantly lower incidence of intraoperative discomfort (2.7% vs. 13.6%; RR: 0.22; 95% CI: 0.09–0.55; P = 0.001), but there was a significant increase in nausea and vomiting (IT meperidine group vs. Control group: 42.7% vs. 19.4%; RR: 2.56; 95% CI: 1.14–5.75; P = 0.02). Meta-regression analysis based on the opioid dose and quality of the study did not impact the final inference of our result. Conclusion IT fentanyl significantly decreased the incidence of shivering in women undergoing CD under spinal anesthesia without increasing maternal adverse events, confirming that routine use in this patient population is a good choice. IT sufentanil did not decrease the incidence of shivering. IT meperidine decreased the incidence and severity of shivering, but its use was also associated with significant nausea and vomiting.

Protein interactions play an essential role in studying living systems and life phenomena. A considerable amount of literature has been published on analyzing and predicting protein interactions, such as support vector machine method, homology-based method and similarity-based method, each has its pros and cons. Most existing methods for predicting protein interactions require prior domain knowledge, making it difficult to effectively extract protein features. Single method is dissatisfactory in predicting protein interactions, declaring the need for a comprehensive method that combines the advantages of various methods. On this basis, a deep ensemble learning method called EnAmDNN (Ensemble Deep Neural Networks with Attention Mechanism) is proposed to predict protein interactions which is an appropriate candidate for comprehensive learning, combining multiple models, and considering the advantages of various methods. Particularly, it encode protein sequences by the local descriptor, auto covariance, conjoint triad, pseudo amino acid composition and combine the vector representation of each protein in the protein interaction network. Then it takes advantage of the multi-layer convolutional neural networks to automatically extract protein features and construct an attention mechanism to analyze deep-seated relationships between proteins. We set up four different structures of deep learning models. In the ensemble learning model, second layer data sets are generated with five-fold cross validation from basic learners, then predict the protein interaction network by combining 16 models. Results on five independent PPI data sets demonstrate that EnAmDNN achieves superior prediction performance than other comparing methods.

Adrenocorticotropic hormone (ACTH) is an important modulator of steroidal hormone synthesis and secretion from the adrenal gland and its selective activity at the melanocortin type 2 receptor (MC2) dictates the synthesis and secretion of cortisol (corticosterone in rats). Excess ACTH action contribute to the pathophysiology of Cushing’s disease (CD), ectopic ACTH secreting tumors (EAS), and Congenital Adrenal Hyperplasia (CAH). Cushing’s disease results from a microadenoma derived from pituitary corticotrophic cells that secretes excess ACTH, whereas EAS arises from nonpituitary ACTH secreting tumors. Excess ACTH action at the adrenal gland and resulting hypercortisolemia presents in a myriad of symptoms that result in high morbidity. CAH results from inactivating mutations in steroid synthesis pathways, resulting in lack of cortisol and aldosterone production. Lack of negative feedback by cortisol at the level of the pituitary causes the over-secretion of ACTH, and overproduction of adrenal androgens, causing significant virilization and reduction in quality of life. We hypothesize that blocking ACTH action directly via a selective MC2 receptor antagonist may provide an important new therapeutic mechanism for these patients. To test this hypothesis, Crinetics launched an iterative medicinal chemistry program to identify potent and selective nonpeptide ACTH antagonists with pharmaceutical and safety characteristics suitable for evaluation in human clinical trials. Unlike most other G protein coupled receptors, MC2 requires the presence of an accessory protein (MRAP) for cell surface expression and recognition of ACTH. Using CHO-K cells stably expressing this MC2-MRAP complex, iterative optimization led to the discovery of multiple chemical classes of highly potent, nonpeptide MC2 receptor selective antagonist leads, which were then further optimized for drug-like characteristics. We identified multiple compounds that exhibit high potency for human and rat MC2 receptors (hMC2 Kb

Objective: Anti-GABA-B (gamma aminobutyric acid-B) receptor encephalitis is an autoimmune disease mediated by GABA-B-related antibodies. To fully understand the disease, we collected clinical data from patients with GABA-B receptor encephalitis and conducted an analysis to draw conclusions. Methods: All patients with GABA-B receptor encephalitis from the Neurology Department of Beijing Tiantan Hospital, affiliated with Capital Medical University, from August 2015 to September 2019 were accepted as study subjects. The clinical data of the patients were analyzed retrospectively and included the general demographic characteristics, clinical manifestations, and auxiliary examinations, including laboratory results, electroencephalograms (EEGs), brain magnetic resonance imaging (MRI), and positron emission tomography (PET-CT) results, as well as treatments. Results: From August 2015 to September 2019, 14 cases of anti-GABA-B receptor encephalitis were diagnosed. Among these patients, middle-aged and elderly men were the main demographic, with an average age of 52 years; moreover, the onset of the disease was relatively sudden, and the time from onset to diagnosis was ~1 month. The main clinical symptoms were frequent epileptic seizures, cognitive dysfunction, and mental behavioral disorders. In seven (50%) patients, the leukocyte in cerebrospinal fluid (CSF) were increased. Five (36%) patients had elevated cerebrospinal fluid protein. In most patients, the oligoclonal bands (83%) of CSF were positive, and 24 h IgG levels (92%) were increased. Anti-Hu or anti-Yo antibodies were positive in two (14%) patients. Tumor markers in 10 (71%) patients indicated that neuron-specific enolase, gastrin-releasing precursor, non-small cell lung cancer-related antigen, or carcinoembryonic antigen levels were increased. EEG results often indicated slow waves, sharp waves, or spike waves in temporal areas. Brain MRI always showed high T2 signals in the medial temporal lobe, hippocampus, and amygdala and swelling in the medial temporal lobe and hippocampus. PET-CT scans almost showed abnormal metabolism in the hippocampus and temporal lobe. Three (21%) patients who underwent systemic PET-CT showed hypermetabolism in pulmonary parenchymal nodules and enlargement of mediastinal lymph nodes. All patients underwent high-dose hormone therapy or immunoglobulin immunotherapy. After treatment, the symptoms of epilepsy, cognitive disorders, and mental behavioral disorders improved to varying degrees. However, one patient died of lung cancer. Conclusion: Anti-GABA-B receptor encephalitis mainly occurred in middle-aged and elderly men, and the disease onset was relatively sudden. Before disease onset, some patients experienced fever and non-specific respiratory symptoms, which mainly manifested as frequent epileptic seizures, cognitive dysfunction, and abnormal mental behavior. MRI and PET-CT revealed abnormal signals and local metabolism, respectively, in the temporal lobe. Moreover, the disease has a close relationship with lung cancer, which requires long-term follow-up observation.