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Regional promotion of school-based research and study to improve the relevant systems, Focusing on the actual situation of rural schools, Found that school-based study in rural schools, Uneven development, Lack of teachers in rural schools, Insufficient funds for school-based research and training, The reward mechanism causes the vicious competition among teachers, The knowledge structure of the left-behind teachers is old, Teachers have limited competence, School-based teaching and research interest is not high, The lack of organizational forms of school-based training, The ways to solve these problems include the following aspects: turning regional resources into teaching materials, Integrating school-based research and training to promote teachers' professional development, Give full play to the practical advantages of the region, Promote the diversification of school-based research and study forms, Establish a mechanism for sustainable development, Realize the normalization of regional school-based research and training.

Atomically precise synthesis of topological molecular carbons such as Möbius carbon nanobelts (MCNBs) represents a big challenge in synthetic organic chemistry as it requires careful control of both twist and strain. So far, only one singly twisted MCNB has been reported and the MCNBs with more than two twists remain unknown. Herein, we report the facile synthesis of the first triply twisted MCNB by rational design and via a synthetic route involving Suzuki coupling-mediated macrocyclization, Bi(OTf)3-catalyzed cyclization of vinyl ethers, followed by oxidative dehydrogenation. The Möbius band-like structure was unambiguously confirmed by X-ray crystallographic analysis, which also revealed coexistence of (P,P,P)- and (M,M,M)- enantiomers. The racemic isomers were resolved by chiral HPLC and the isolated enantiomers exhibited a large absorption dissymmetry factor (|gabs| = 0.019) according to circular dichroism spectroscopy, which can be explained by the fully conjugated structure and the desirable orientation of the electric and magnetic transition moments.

Background During our clinical practice, some patients with Chlamydia psittaci pneumonia were found to have secondary pulmonary fungal infections; consequently, this study analyzed the risk factors for their combined pulmonary fungal infections. We also compared the efficacy of tetracycline and moxifloxacin in the treatment of C. psittaci pneumonia to guide the treatment of this disease.Methods Eighty cases of C. psittaci pneumonia in Chongqing were selected and divided into a non-fungal group (56 cases) and a fungal group (24 cases) according to the combination of pulmonary fungal infection. The risk factors for combined pulmonary fungal infection were analyzed. According to the type of medication used, the patients were divided into five treatment groups, including (I) 12 cases of omadacycline, (II) 12 cases of tigecycline, (III) 10 cases of doxycycline, (IV) 8 cases of minocycline, and (V) 38 cases of moxifloxacin, and the efficacy of the drugs was compared.Results (1) Comparisons of factors, including hospitalization cost, length of stay, and duration of fever, showed that, first, the prognosis of the non-fungal group was better than that of the fungal group, and second, there were statistically significant differences between the two groups in the use of broad-spectrum antibacterial drugs; the co-administration of antimicrobials; combined structural lung disease, diabetes mellitus, and liver disease; and serum ferritin levels at admission. A logistic regression analysis showed the co-administration of antimicrobials; combined structural lung disease, diabetes mellitus, and liver disease; and relatively low serum ferritin were independent risk factors for combined pulmonary fungal infections. (2) Comparison of drug efficacy: The white blood cell count in Group I was better than in groups II and V, while fever, imaging improvement, and calcitoninogen decrease time in Group I were significantly better than in groups II, III, IV, and V. The cost in Group V was lower than in groups I, II, and III, and no significant difference was seen in the occurrence of major adverse reactions.Conclusions Patients with C. psittaci pneumonia who are co-administered with antimicrobials and are combined with structural lung disease, diabetes mellitus, and liver disease along with relatively low serum ferritin need to be alerted to combined pulmonary fungal infections. The efficacy of tetracyclines in treating such infections is more pronounced than that of other drugs, while the cost of moxifloxacin is lower than that of other antibiotics.

Recently, there exist growing concerns about the interpretability of deep learning models. While few of these models have been applied to a duplicate question detection task, which aims at finding semantically equivalent question pairs of question answering forum. In this paper, based on an attention mechanism, we propose two modularized interpretable deep neural network models for such tasks. During the word precessing procedure, a filter operation is employed to enhance the relevant information contained in the pre-trained word embeddings. Regarding the word matching and sentence representation process, vanilla attention and structured attention mechanisms are utilized, respectively. Benefiting from the interpretability of attention techniques, our models can illustrate how the words match between sentence pairs and what aspects of the sentences are extracted to have an effect on the final decision. The attention visualization furnishes us with detailed representation at word and sentence level. And experimental results show that our models are comparable with other reported models.

Thermo-responsive shape memory polymers which are a class of important smart materials can recover permanent shape from temporary shape by simple thermal stimulus, but most of the polymers lack of biodegradability and biocompatibility. Poly(L-lactide) (PLLA) is a green degradable thermoplastic, however, only limited studies involve controlling its shape change. In the work, a new x-shaped copolymer with defined architecture has been devised by using tetramethyltetravinylcyclotetrasiloxane (D4vi) as centronucleus and polytetrahydrofuran-co-poly(e-caprolactone) (PTMG-co-PCL) as branch to achieve PLLA shape memory. When the weight ratio of DAPP and PLLA is 50/50, the composite exhibits good thermo-responsive shape memory capacity because a balance between Tm of the x-shaped polymer rand Tg of PLLA is kept. The shape fixation ratio is 84% at 15 °C, and the recovery ratio 94% at 55 °C. And the shape memory capability does not change evidently after the reversible spiral transition is repeated for 30 times. At the same time, the composite shows great flexibility. So the obtained composite is promising for medical and bionic devices, self-healing systems, self-assembly structures.

Storyline generation has emerged to be an effective method to describe the evolution of disaster. However, due to the temporal-spatial, heterogeneous, and information overload, most of the existing storylines are only based on textual data and deliver limited information. In this paper, we introduce a novel framework for generating multimedia storylines to provide more concise and vivid information and deeper understanding of real-time events. We first adopt generative adversarial networks to implement an unsupervised bilingual document summarizing model. Then, we transform image and text incorporation problem into a multi-label learning problem and use convolutional neural networks to train a classification model. And finally, the bilingual documents and images are jointly summarized and embedded into a two-layer storyline generating framework. The experiments on real Hurricane data sets demonstrate the effectiveness of the proposed methods in each level and the overall framework.

Venue recommendation has attracted a lot of research attention with the rapid development of Location-Based Social Networks. The effectiveness of venue recommendation largely depends on how well it captures users’ contexts or preferences. However, it is quite difficult, if not impossible, to capture the whole information about users’ preferences. In addition, users’ preferences are often heterogeneous (i.e., some preferences are static and common to all users while some preferences are dynamic and diverse). Existing venue recommendation does not well address the aforementioned issues and often recommends the most popular, the cheapest, or the closest venues based on simple contexts. In this paper, we cast the venue recommendation as a ranking problem and propose a recommendation framework named VRer (Context-Based V enue R ecommendation using e mbedded space r anking SVM) employing an embedded space ranking SVM model to separate the venues in terms of different characteristics. Our proposed approach makes use of ‘check-in’ data to capture users’ preferences and utilizes a machine learning model to tune the importance of different factors in ranking. The major contribution of this paper are: (1) VRer combines various contexts (e.g., the temporal influence and the category of locations) with the check-in records to capture individual heterogeneous preferences; (2) we propose an embedded space ranking SVM optimizing the learning function to reduce the time consumption of training the personalized recommendation model for each group or user; (3) we evaluate our proposed approach against a real world LBSN and compare it with other baseline methods. Experimental results demonstrate the benefits of our proposed approach.

Several factors (e.g., balancedness, good correlation immunity) are considered as important properties of Boolean functions for using in cryptographic primitives. A Boolean function is perfect algebraic immune if it is with perfect immunity against algebraic and fast algebraic attacks. There is an increasing interest in construction of Boolean function that is perfect algebraic immune combined with other characteristics, like resiliency. A resilient function is a balanced correlation-immune function. This paper uses bivariate representation of Boolean function and theory of finite field to construct a generalized and new class of Boolean functions on even variables by extending the Carlet-Feng functions. We show that the functions generated by this construction support cryptographic properties of 1-resiliency and (sub)optimal algebraic immunity and further propose the sufficient condition of achieving optimal algebraic immunity. Compared experimentally with Carlet-Feng functions and the functions constructed by the method of first-order concatenation existing in the literature on even (from 6 to 16) variables, these functions have better immunity against fast algebraic attacks. Implementation results also show that they are almost perfect algebraic immune functions.

The rapid development of information era has influenced to realize the notion of Smart Bank via approaches like paperless services and interactive self-service systems. Since the traditional methods of identity verification are insecure and cumbersome for supporting these services, Smart Bank has been questioned. To overcome the limitations of current identity verification, it is imperative to explore an effective recognition strategy considering the trade-off between security and customer experience, which can conveniently collect identity information and accurately distinguish people. However, few research and existing systems have been reported for an integrated solution of identity verification satisfying convenient and secure banking environment. In this paper, we propose, implement, and deploy an integrated system named FIRST (Face Identity Recognition in SmarT Bank), which is a customized platform for the identity verification via face recognition in Smart Bank. FIRST uses Gabor surface feature and Fisherfaces, which can provide accurate face recognition within acceptable training time. For information acquisition, our system employs the patch-based face quality assessment, which efficiently extracts valuable faces (i.e. front face) from video streams. Furthermore, FIRST provides a distributed environment to effectively manage recognition tasks and massive data. Since March 2015, FIRST has been successfully deployed on 1800 self-service terminals in Jiangsu Province by ABC (Agriculture Bank of China), and is under deployment by State Grid in China.

Poly(L-lactide) (PLLA) was one of the most well-known biodegradable polyesters. Although its thermo-responsive shape memory (SM) function has been studied by proper program, high transformation temperature is not suitable in some biomedical applications. Water-responsive SM polymer is an alternative choice and exhibits great potential because it is harmless to the cells and tissues of organisms. In the work, a novel PCL-(PMVS-s-PAA)-PCL-PTMG-PCL-(PMVS-s-PAA)-PCL copolymer was devised as an additive to endow PLLA with water-responsive SM capability. The incorporated PLLA was characterized by cross-section, water contact angle, differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). Inserted PTMG segment and assisted ambient temperature were contributed to its SM behaviors. The shape fixation ratio and shape recovery ratio were 92.0% and 94.2%, respectively. The schematic diagram between internal microstructures and macroscopic properties was proposed. At the same time, the incorporated PLLA showed excellent toughness. So the obtained SM material would be promising for medical and biomimetic fields.

Proposed a stable structural damage detection method based on information fusion.Improved the accuracy and stability of the damage detection than using single sensor.Solved the bad impact of any sensor failure and give more robust detection results. An intelligent detection method is proposed in this paper to enrich the study of applying machine learning and data mining techniques to building structural damage identification. The proposed method integrates the multi-sensory data fusion and classifier ensemble to detect the location and extent of the damage. First, the wavelet package analysis is used to transform the original vibration acceleration signal into energy features. Then the posteriori probability support vector machines (PPSVM) and the Dempster-Shafer (DS) evidence theory are combined to identify the damage. Empirical study on a benchmark structure model shows that, compared with popular data mining approaches, the proposed method can provide more accurate and stable detection results. Furthermore, this paper compares the detection performance of the information fusion at different levels. The experimental analysis demonstrates that the proposed method with the fusion at the decision level can make good use of multi-sensory information and is more robust in practice.

Semi-supervised cluster ensemble usually introduces a small amount of supervision in the first stage of cluster ensemble, i.e., ensemble generation, by performing many runs of semi-supervised clustering algorithms. However, it is neither efficient in terms of computational complexity, nor flexible in a dynamic learning environment where limited supervision changes over time. In this article we propose a new framework which generates base partitions in an unsupervised manner and attributes different weights to each cluster of the base partitions. The weighting scheme considers both the internal validation measures of clustering and the degrees of satisfaction of pairwise constraints. A weighted co-association matrix based consensus approach is then applied to achieve a final partition. To handle high-dimensional data, we generate base partitions using k-means with both random sampling and random subspace techniques. The new framework retains a high accuracy, and is efficient since it avoids performing semi-supervised clustering in ensemble generation and the complexity of the weighting scheme is independent of the number of instances in a dynamic environment. It is more adaptive than the traditional approach because it does not require rerunning semi-supervised clustering algorithms when the limited supervision changes. Empirical results on 12 datasets demonstrate that it is also more robust to noisy constraints.

Inflammatory cardiomyopathy is the result of persistent myocardial inflammation which can arise from both infectious or noninfectious causes. While most patients with acute myocarditis recover, up to 20% develop inflammatory cardiomyopathy with chronic heart failure. The interaction between host factors and factors of the agent that triggered myocardial inflammation must be considered to fully understand the individual mechanism of disease. Several inflammatory biomarkers, histology, immunohistochemistry, advanced imaging technologies as well as molecular high-throughput sequencing techniques help to identify disease pathways and to establish a comprehensive, individualized treatment approach, which can include anti-inflammatory medication, antiviral drugs and heart failure therapy. This might help to prevent transition from acute inflammation to persistent heart failure and to restore cardiac function.

Circulation / Arrhythmia and electrophysiology 11(6), e006242 (2018). doi:10.1161/CIRCEP.118.006242, Published by Lippincott, Williams & Wilkins, Philadelphia, Pa.

Vehicular nodes are equipped with more and more sensing units, and a large amount of sensing data is generated. Recently, more and more research considers cooperative urban sensing as the heart of intelligent and green city traffic management. The key components of the platform will be a combination of a pervasive vehicular sensing system, as well as a central control and analysis system, where data-gathering is a fundamental component. However, the data-gathering and monitoring are also challenging issues in vehicular sensor networks because of the large amount of data and the dynamic nature of the network. In this paper, we propose an efficient continuous event-monitoring and data-gathering framework based on fog nodes in vehicular sensor networks. A fog-based two-level threshold strategy is adopted to suppress unnecessary data upload and transmissions. In the monitoring phase, nodes sense the environment in low cost sensing mode and generate sensed data. When the probability of the event is high and exceeds some threshold, nodes transfer to the event-checking phase, and some nodes would be selected to transfer to the deep sensing mode to generate more accurate data of the environment. Furthermore, it adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions. Simulation results showed that the proposed scheme could reduce more than 84 percent of the data transmissions compared with other existing algorithms, while it detects the events and gathers the event data.

The Koktokay No. 3 pegmatite is the largest Li–Be–Nb–Ta–Cs pegmatitic rare-metal deposit of the Chinese Altai orogenic belt, and is famous for its concentric ring zonation pattern (nine internal zones). However, the formation age and evolution time span have been controversial. Here, we present the results of LA-ICP–MS zircon U–Pb dating and muscovite 40Ar–39Ar dating. Four groups of zircon U–Pb ages (∼210 Ma, ∼193–198 Ma, ∼186–187 Ma and ∼172 Ma) for Zones II, V, VI, VII, and VIII, and a weighed mean 206Pb/238U age of 965 ± 11 Ma for Zone IV are identified. Also, Zones II, IV, and VI have muscovite 40Ar–39Ar plateau ages of 179.7 ± 1.1 Ma, 182.1 ± 1.0 Ma, and 181.8 ± 1.1 Ma, respectively. Considering previous U–Pb age studies (Zones I, V, and VII), the ages of emplacement, Li mineralization peak, hydrothermal stage of the No. 3 pegmatite are in ranges of 193–198 Ma, 184–187 Ma and 172–175 Ma, with weighted mean 206Pb–238U ages of 194.8 ± 2.3 Ma, 186.6 ± 1.3 Ma and 173.1 ± 3.9 Ma, respectively. The No. 3 pegmatite formed in the early Jurassic. The results of xenocrysts suggest that there is another pegmatite forming event of around 210 Ma in the mining district and the old zircon U–Pb ages imply that Neoproterozoic crustal rocks pertain to sources of the No. 3 pegmatite. Including the previous muscovite 40Ar–39Ar age studies (Zones I and V), a cooling age range of 177–182 Ma is considered as the time of hydrothermal stage and end of formation. The evolution process of the No. 3 pegmatite lasted 16 Ma. Therein, the magmatic stage continued for 9–11 Myr and the magmatic–hydrothermal transition and hydrothermal stages were sustained at 5–7 Ma. These time spans are long because of huge scale, cupola shape, large formation depth, and complex internal zoning patterns and formation processes. Considering some pegmatite dikes in the Chinese Altai, there is an early Jurassic pegmatite forming event.

The Koktokay No. 3 pegmatite is the largest Li-Be-Nb-Ta-Cs pegmatitic rare-metal deposit of the Chinese Altai orogenic belt, and is famous for its concentric ring zonation pattern (nine internal zones) and rare-metal reserves. In this paper, we present the results of major and trace element analysis for garnet, tourmaline, and beryl from the outer to inner zones of the No. 3 pegmatite. From previous studies on tourmaline and beryl, potential tracers of the degree of pegmatite evolution could be found by comparing with accepted indicators and evolutionary trends from the outer to inner zones of this pegmatite. The Sc, Y, Li, Ta contents and Y/Ho value of garnet, together with the Ti, Ca, Na, Pb, Bi and REE contents of tourmaline, and the Fe, Ga and Rb concentrations of beryl could be possible tracers of the degree of evolution of pegmatites. The textures and internal structures (homogeneity, oscillatory pattern, heterogeneous rims, replacement structures) of minerals in the pegmatite suggest that the rock underwent (1) rapid undercooling and crystallization after emplacement, resulting in the formation of an unidirectional solidification texture (UST), and then (2) became relatively stable, forming coarse crystals in outer zones, and finally (3) experienced disequilibrium crystallization, leading to the formation of complex internal structures of minerals in the inner zones, mainly caused by exsolution of more fluid and the formation of immiscible melts with different alkali contents. The evolutionary trend and the internal structures of tourmaline and beryl indicate that the formation of the Koktokay No. 3 pegmatite was controlled mainly by fractional crystallization. The convex tetrad effect, non-CHARAC Y/Ho values, and extreme Eu depletion of garnet suggest that immiscibility, which is a significant mechanism during the formation of the No. 3 pegmatite, occurred during emplacement. The differences in composition and internal structures of the minerals between the outer and inner zones of the No. 3 pegmatite suggest that there was an abrupt change, during transition from the melt stage to the melt–fluid stage, resulting from a decompression event, which led to the exsolution of the fluid and initiated the Li-Ta-Cs deposition in the pegmatite.

A framework for novelty detection using random forest is proposed.Two specific approaches using the vote distribution and the proximity matrix are presented.A comprehensive empirical study on both synthetic and real-world datasets is conducted. In many online classification tasks or non-exhaustive learning, it is often impossible to define a training set with a complete set of classes. The presence of new classes as well as the novelties caused by data errors can severely affect the performance of classifiers. Traditional proximity-based approaches usually utilize the distance to measure the proximity of different samples. In this study, we propose a framework that uses ensemble learning to detect novelty based on Random Forest (RF). The proposed framework is based on the observation that an ensemble of classifiers can provide a kind of metric to characterize different classes and measure their proximity. In particular, we apply ensemble methods with the decision tree as base classifiers and present two specific approaches, RFV and RFP, based on random forest. RFV uses the vote distribution of RF on a testing sample, and RFP takes the proximity matrix of RF as a special kernel metric to discover the novelty. The proposed approaches are compared against two common approaches: support vector domain description (SVDD) and Gaussian Mixed Model (GMM) on one artificial data set and five benchmark data sets. The experimental results show that the proposed methods achieve better performance in terms of accuracy and recall.

Apoptosis (type I programmed cell death) of cardiomyocytes is a major process that plays a role in the progression of heart failure. The early response gene IER3 regulates apoptosis in a wide variety of cells and organs. However, its role in heart failure is largely unknown. Here, we investigate the role of IER3 in an inducible heart failure mouse model. Heart failure was induced in a mouse model that imitates a human titin truncation mutation we found in a patient with dilated cardiomyopathy (DCM). Transferase dUTP nick end labeling (TUNEL) and ssDNA stainings showed induction of apoptosis in titin-deficient cardiomyocytes during heart failure development, while IER3 response was dysregulated. Chromatin immunoprecipitation and knock-down experiments revealed that IER3 proteins target the promotors of anti-apoptotic genes and act as an anti-apoptotic factor in cardiomyocytes. Its expression is blunted during heart failure development in a titin-deficient mouse model. Targeting the IER3 pathway to reduce cardiac apoptosis might be an effective therapeutic strategy to combat heart failure.

At the beginning of a new biennium, the first thing is always to have a look at what we have accomplished, where we are, and to think about what to do next. I thank the volunteers and the staff of the Union for their excellent work over the last two years. Highlights include the naming of four new elements, progress on the revision of IUPAC’s “color books,” the release of several IUPAC Recommendations, the granting of many awards, the establishment of the Interdivisional Committee on Green Chemistry for Sustainable Development, and strengthened cooperation with other international organizations, including the Organization for Prohibition of Chemical Weapons (OPCW) and the International Younger Chemists Network.

In designing cryptographic Boolean functions, it is challenging to achieve at the same time the desirable features of algebraic immunity, balancedness, nonlinearity, and algebraic degree for necessary resistance against algebraic attack, correlation attack, Berlekamp–Massey attack, etc. This paper constructs balanced rotation symmetric Boolean functions on n variables where n = 2 p and p is an odd prime. We prove the construction has an optimal algebraic immunity and is of high nonlinearity. We check that, at least for those primes p which are not of the form of a power of two plus one, the algebraic degree of the construction achieves in fact the upper bound n − 1 .

In order to better constrain the evolution and petrogenesis of pegmatite, geochemical analysis was conducted on a suite of apatite crystals from the Altay Koktokay No. 3 pegmatite, Xinjiang, China and from the granitic and amphibolitic wall rocks. Apatite samples derived from pegmatite zones show convex tetrad effects in their REE patterns, extremely negative Eu anomalies and non-chondritic Y/Ho ratios. In contrast, chondritic Y/Ho ratios and convex tetrad effects are observed in the muscovite granite suggesting that different processes caused non-chondritic Y/Ho ratios and lanthanide tetrad effects. Based on the occurrence of convex tetrad effects in the host rocks and their associated minerals, we propose that the tetrad effects are likely produced from immiscible fluoride and silicate melts. This is in contrast to previous explanations of the tetrad effect; i.e. surface weathering, fractional crystallization and/or fluid-rock interaction. Additionally, we put forward that extreme negative Eu and non-chondritic Y/Ho in apatite are likely caused by the large amount of hydrothermal fluid exsolved from the pegmatite melts. Evolution of melt composition was found to be the primary cause of inter and intra-crystal major and trace element variations in apatite. Mn entering into apatite via substitution of Ca is supported by the positive correlation between CaO and MnO. Different evolution trends in apatite composition imply different crystallization environments between wall rocks and pegmatite zones. Based on the geochemistry of apatite samples, it is likely that there is a genetic relationship between the source of muscovite granite and the source of the pegmatite.

A recent survey conducted by British scientists shows that, though the public has a positive impression of chemistry’s role in social development and the improvement of human welfare, many people are not very sure about what chemists actually do (

Cell-mediated immunity and neutralizing antibodies contribute to control of human immunodeficiency virus/simian immunodeficiency virus (HIV/SIV) infection, but the role of nonneutralizing antibodies is not defined. Previously, we reported that sequential oral/oral or intranasal/oral (I/O) priming with replication-competent adenovirus type 5 host range mutant (Ad5hr)-SIV recombinants, followed by intramuscular envelope protein boosting, elicited systemic and mucosal cellular immunity and exhibited equivalent, significant reductions of chronic viremia after rectal SIV mac251 challenge. However, I/O priming gave significantly better control of acute viremia. Here, systemic and mucosal humoral immunity were investigated for potential correlates with the acute challenge outcome. Strong serum binding but nonneutralizing antibody responses against SIV mac251 were induced in both groups. Antibody responses appeared earlier and overall were higher in the I/O group. Reduced acute viremia was significantly correlated with higher serum binding titer, stronger antibody-dependent cellular cytotoxicity activity, and peak prechallenge and 2-week-postchallenge antibody-dependent cell-mediated viral inhibition (ADCVI). The I/O group consistently displayed greater anti-envelope immunoglobulin A (IgA) antibody responses in bronchoalveolar lavage and a stronger rectal anti-envelope IgA anamnestic response 2 weeks postchallenge. Pre- and postchallenge rectal secretions inhibited SIV transcytosis across epithelial cells. The inhibition was significantly higher in the I/O group, although a significant correlation with reduced acute viremia was not reached. Overall, the replicating Ad5hr-SIV priming/envelope boosting approach elicited strong systemic and mucosal antibodies with multiple functional activities. The pattern of elevated immune responses in the I/O group is consistent with its better control of acute viremia mediated, at least in part, by ADCVI activity and transcytosis inhibition.

Mutations in the giant sarcomeric protein titin (TTN) are a major cause for inherited forms of dilated cardiomyopathy (DCM). We have previously developed a mouse model that imitates a TTN truncation mutation we found in a large pedigree with DCM. While heterozygousTtnknock-in mice do not display signs of heart failure under sedentary conditions, they recapitulate the human phenotype when exposed to the pharmacological stressor angiotensin II or isoproterenol. In this study we investigated the effects of pressure overload by transverse aortic constriction (TAC) in heterozygous (Het)Ttnknock-in mice. Two weeks after TAC, Het mice developed marked impairment of left ventricular ejection fraction(p<0.05), while wild-type (WT) TAC mice did not. Het mice also trended toward increased ventricular end diastolic pressure and volume compared to WT littermates. We found an increase in histologically diffuse cardiac fibrosis in Het compared to WT in TAC mice. This study shows that a pattern of DCM can be induced by TAC-mediated pressure overload in a TTN-truncated mouse model. This model enlarges our arsenal of cardiac disease models, adding a valuable tool to understand cardiac pathophysiological remodeling processes and to develop therapeutic approaches to combat heart failure.

Frameshift mutations in the TTN gene encoding titin are a major cause for inherited forms of dilated cardiomyopathy (DCM), a heart disease characterized by ventricular dilatation, systolic dysfunction, and progressive heart failure. To date, there are no specific treatment options for DCM patients but heart transplantation. Here, we show the beneficial potential of reframing titin transcripts by antisense oligonucleotide (AON)-mediated exon skipping in human and murine models of DCM carrying a previously identified autosomal-dominant frameshift mutation in titin exon 326. Correction of TTN reading frame in patient-specific cardiomyocytes derived from induced pluripotent stem cells rescued defective myofibril assembly and stability and normalized the sarcomeric protein expression. AON treatment in Ttn knock-in mice improved sarcomere formation and contractile performance in homozygous embryos and prevented the development of the DCM phenotype in heterozygous animals. These results demonstrate that disruption of the titin reading frame due to a truncating DCM mutation can be restored by exon skipping in both patient cardiomyocytes in vitro and mouse heart in vivo, indicating RNA-based strategies as a potential treatment option for DCM.

Objective: To determine if immunization with non-myristoylated nef would elicit enhanced cellular immune responses resulting from improved presentation of Nef peptides by MHC-I on the cell surface, and enhanced T-cell help. Design: The myristoylation site of HIV and SIV Nef is required for several Nef functions that modulate the immune response in an infected host, including downregulation of MHC-I, MHC-II, and CD4, and increased expression of the invariant chain on the cell surface. We constructed replication-competent Ad5-and Ad7-HIV recombinants encoding wild-type net(nef WT ) or a nef mutant (nef NM ) lacking 19 amino-terminal amino acids, including the myristoylation site, and sequentially immunized chimpanzees mucosally, first with Ad5-HIVnef recombinants and subsequently with Ad7-HIVnef recombinants. Methods: Peripheral blood lymphocytes were evaluated over the immunization course for Nef-specific cellular immune responses by interferon (IFN)-γ ELISPOT and T-cell proliferation assays. Nef-specific CD4 and CD8 memory T cells that produced intracellular IFN-γ, interleukin-2, and tumor necrosis factor (TNF)-a were assessed by flow cytometry. Results: In comparison to immunization with Ad-HlVnef WT , Ad-HIVnef NM elicited statistically significant increases in numbers of IFN-γ-secreting cells after the Ad7-HΙVnef NM immunization and increased T-cell proliferative responses following both Ad5- and Ad7-HIVnef NM immunizations. Nef-specific CD4 and CD8 memory T-cell populations secreting TNF-a were also significantly increased in the Ad-HIVnef NM immunization group. Conclusions: The results support the hypothesis that immunization with Ad-recombinants encoding HIVnef NM rather than HIVnef WT elicits enhanced cellular immunity resulting from improved antigen presentation and greater T-cell help.

Background Transfection in mammalian cells based on liposome presents great challenge for biological professionals. To protect themselves from exogenous insults, mammalian cells tend to manifest poor transfection efficiency. In order to gain high efficiency, we have to optimize several conditions of transfection, such as amount of liposome, amount of plasmid, and cell density at transfection. However, this process may be time-consuming and energy-consuming. Fortunately, several mathematical methods, developed in the past decades, may facilitate the resolution of this issue. This study investigates the possibility of optimizing transfection efficiency by using a method referred to as least-squares support vector machine, which requires only a few experiments and maintains fairly high accuracy. Results A protocol consists of 15 experiments was performed according to the principle of uniform design. In this protocol, amount of liposome, amount of plasmid, and the number of seeded cells 24 h before transfection were set as independent variables and transfection efficiency was set as dependent variable. A model was deduced from independent variables and their respective dependent variable. Another protocol made up by 10 experiments was performed to test the accuracy of the model. The model manifested a high accuracy. Compared to traditional method, the integrated application of uniform design and least-squares support vector machine greatly reduced the number of required experiments. What's more, higher transfection efficiency was achieved. Conclusion The integrated application of uniform design and least-squares support vector machine is a simple technique for obtaining high transfection efficiency. Using this novel method, the number of required experiments would be greatly cut down while higher efficiency would be gained. Least-squares support vector machine may be applicable to many other problems that need to be optimized.