Observation study of using a small dose of rituximab treatment for thyroid-associated ophthalmopathy in seven Chinese patients: One pilot study

ObjectiveTo report the efficacy, long-term safety, and tolerability of using a small dose (125 mg/m2 weekly for 4 weeks) of rituximab to treat Chinese patients with thyroid-associated ophthalmopathy (TAO).MethodsSeven patients with active moderate-to-severe TAO were prospectively recruited in this study. A small dose of rituximab (125mg/m2 body surface area) was given weekly with a duration of four weeks. Thyroid function, thyrotropin receptor antibody (TRAb), B cell and T cell subsets, ophthalmological examination, magnetic resonance imaging derived parameters, and adverse reactions were recorded at each visit.ResultsSeven patients were followed for an average of 224 weeks. B-cell depletion was observed in all patients following rituximab infusion. The clinical activity score (CAS) decreased from 4.86 ± 0.69 to 3.00 ± 0.82 at 5 weeks after treatment (P = 0.033) and remained significantly lower than baseline values at the end of follow-up (P = 0.001). Compared to baseline values, significant decreases in exophthalmos of the right eye, the thickness of extraocular muscles with maximum signal intensity, and the highest signal intensity ratio (SIR) of extraocular muscle to ipsilateral temporal muscle values were observed at the last follow-up (all P < 0.05). Disease progressions or recurrences were not observed during follow-up. Only mild fatigue was observed after the first infusion as a side effect (n = 1).ConclusionSmall dose of rituximab may be a promising option with adequate safety, tolerability, and long-term efficacy for patients with active moderate-to-severe TAO

Study of Parameters and Theory of Sucrose Dust Explosion

To investigate the parameters of sucrose dust explosion, the minimum ignition energy (MIE) and minimum ignition temperature (MIT) were evaluated. The experiments tested the MIE of sucrose dust under different conditions of dust quantity, ignition delay time (IDT), and powder injection pressure (PIP). The experiments tested the MIT of different particle sizes. The results demonstrate that the MIE of sucrose powder under three conditions was an open-up quadratic polynomial. When the dust quantity, the IDT, and PIP were 0.5 g (417 g/m3), 90 ms, and 150 kPa, respectively, the MIE was 58.9 mJ, 62.6 mJ, and 52.4 mJ. The MIT was positively correlated with the particle size of sucrose dust, and the MIT was 340 °C. At the molecular level, the 'O–H' bonds of the sucrose molecule hydroxyl groups were broken by the discharge of electrodes or high temperature to generate H2. The combustion of H2 caused the explosion to spread to the surrounding sucrose dust and made the deposited dust rise, forming an interlocking explosion. The explosion would not stop until the dust concentration dropped below the lowest explosion limit. The results of this study can provide guidance for sucrose enterprises to prevent dust explosion accident

A Retroreflection Reduction Technique Based on the Wavefront Coded Imaging System

A novel anti-cat-eye effect imaging technique based on wavefront coding is proposed as a solution to the problem of previous anti-cat-eye effect imaging techniques where imaging quality was sacrificed to reduce the retroreflection from the photoelectric imaging equipment. With the application of the Fresnel–Kirchhoff diffraction theory, and the definition of generalized pupil function combining both phase modulation and defocus factors, the cat-eye echo formation of the wavefront coded imaging system is theoretically modeled. Based on the physical model, the diffracted spot profile distribution and the light intensity distribution on the observation plane are further simulated with the changes in the defocus parameter and the phase modulation coefficient. A verification test on the cat-eye laser echo power of the wavefront coded imaging system and that of the conventional imaging system at a 20 m distance are conducted, respectively. Simulations and experiment results show that compared with conventional imaging systems, the wavefront coding imaging system can reduce the retroreflection echo by two orders of magnitude while maintaining better imaging quality through defocusing

KG2Vec: A node2vec-based vectorization model for knowledge graph.

Since the word2vec model was proposed, many researchers have vectorized the data in the research field based on it. In the field of social network, the Node2Vec model improved on the basis of word2vec can vectorize nodes and edges in social networks, so as to carry out relevant research on social networks, such as link prediction, and community division. However, social network is a network with homogeneous structure. When dealing with heterogeneous networks such as knowledge graph, Node2Vec will lead to inaccurate prediction and unreasonable vector quantization data. Specifically, in the Node2Vec model, the walk strategy for homogeneous networks is not suitable for heterogeneous networks, because the latter has distinguishing features for nodes and edges. In this paper, a Heterogeneous Network vector representation method is proposed based on random walks and Node2Vec, called KG2vec (Heterogeneous Network to Vector) that solves problems related to the inadequate consideration of the full-text semantics and the contextual relations that are encountered by the traditional vector representation of the knowledge graph. First, the knowledge graph is reconstructed and a new random walk strategy is applied. Then, two training models and optimizing strategies are proposed, so that the contextual environment between entities and relations is obtained, semantically providing a full vector representation of the Heterogeneous Network. The experimental results show that the KG2VEC model solves the problem of insufficient context consideration and unsatisfactory results of one-to-many relationship in the vectorization process of the traditional knowledge graph. Our experiments show that KG2vec achieves better performance with higher accuracy than traditional methods

Modeling Disease Progression: Angiotensin II Indirectly Inhibits Nitric Oxide Production via ADMA Accumulation in Spontaneously Hypertensive Rats

Nitric oxide (NO) production impairment is involved in the onset and development of hypertension. Although NO production impairment in spontaneously hypertensive rat (SHR) has been reported in a variety of researches, the time course of this progressive procedure, as well as its relationship with asymmetric dimethylarginine (ADMA) and angiotensin II (Ang II), has not been quantified. The aim of this research is to establish a mechanism-based disease progression model to assess Ang II and ADMA’s inhibition of NO production in SHR’s disease progression with/without ramipril’s intervention. SHR were randomly divided into three groups: one disease group (n=8) and two treatment groups (n=8 for each group) ：standard treatment group (receiving ramipril 2mg/kg*day) and intensive treatment group (receiving ramipril 10mg/kg*day). ADMA, Ang II, NO and SBP were determined weekly. Intensive treatment with ramipril was found to have no further attenuation of plasma NO and ADMA than standard treatment beyond its significantly stronger antihypertensive effects. Four linked turnover models were developed to characterize the profiles of ADMA, Ang II, NO and SBP during hypertensive disease progression with/without ramipril intervention. Our model described Ang II and ADMA’s contribution to NO production impairment and their responses to ramipril treatment throughout the disease progression in SHR. Model simulations suggested that Ang II affected NO production mainly through inhibiting ADMA elimination rather than affecting nitric oxide synthase (NOS) directly

A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer's disease.

Mild cognitive impairment (MCI) is a precursor phase of Alzheimer's disease (AD). As current treatments may be effective only at the early stages of AD, it is important to track MCI patients who will convert to AD. The aim of this study is to develop a high performance semi-mechanism based approach to predict the conversion from MCI to AD and improve our understanding of MCI-to-AD conversion mechanism. First, analysis of variance (ANOVA) test and lasso regression are employed to identify the markers related to the conversion. Then the Bayesian network based on selected markers is established to predict MCI-to-AD conversion. The structure of Bayesian network suggests that the conversion may start with fibrin clot formation, verbal memory impairment, eating pattern changing and hyperinsulinemia. The Bayesian network achieves a high 10-fold cross-validated prediction performance with 96% accuracy, 95% sensitivity, 65% specificity, area under the receiver operating characteristic curve of 0.82 on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The semi-mechanism based approach provides not only high prediction performance but also clues of mechanism for MCI-to-AD conversion

A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer's disease.

Mild cognitive impairment (MCI) is a precursor phase of Alzheimer's disease (AD). As current treatments may be effective only at the early stages of AD, it is important to track MCI patients who will convert to AD. The aim of this study is to develop a high performance semi-mechanism based approach to predict the conversion from MCI to AD and improve our understanding of MCI-to-AD conversion mechanism. First, analysis of variance (ANOVA) test and lasso regression are employed to identify the markers related to the conversion. Then the Bayesian network based on selected markers is established to predict MCI-to-AD conversion. The structure of Bayesian network suggests that the conversion may start with fibrin clot formation, verbal memory impairment, eating pattern changing and hyperinsulinemia. The Bayesian network achieves a high 10-fold cross-validated prediction performance with 96% accuracy, 95% sensitivity, 65% specificity, area under the receiver operating characteristic curve of 0.82 on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The semi-mechanism based approach provides not only high prediction performance but also clues of mechanism for MCI-to-AD conversion

Mechanical Behavior and Sealing Performance Study of Subsea Connector Core-Sealing Components under the Combined Action of Internal Pressure, Bending Moment, and Axial Load

A complete subsea production system (SPS) is assembled by interconnecting subsea manufacturing facilities through subsea connectors. To ensure the reliability and longevity of the SPS, it is imperative to thoroughly investigate the mechanical behavior and sealing performance of the subsea connector’s core-sealing components. In this study, the loading conditions of the subsea clamp connector are examined to analyze the load transfer relationship between its components under different modes. A mathematical model for the load transfer between locking torque and sealing contact pressure is developed for the preloading mode, and the concept of mechanical transfer efficiency is introduced. Another mathematical model for the load transfer between the locking torque and the design pressure is developed for the operation mode. Furthermore, a three-dimensional full-size finite element model of the subsea clamp connector is established to analyze the effects of complex loads on the mechanical behavior and sealing performance of its core-sealing components. The simulation results indicate that internal pressure loading positively affects the sealing of the subsea connector, and that the stress distribution in the core-sealing components under bending moment loading exhibits significant asymmetric characteristics. Additionally, the superposition of axial tensile loads reduces the effect of the bending moment on the strength of the core seal member but further weakens the seal. Finally, an experimental system is designed to validate the simulation results