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Abstract TnpBs encoded by the IS200/IS605 family transposon are among the most abundant prokaryotic proteins from which type V CRISPR-Cas nucleases may have evolved. Since bacterial TnpBs can be programmed for RNA-guided dsDNA cleavage in the presence of a transposon-adjacent motif (TAM), these nucleases hold immense promise for genome editing. However, the activity and targeting specificity of TnpB in homology-directed gene editing remain unknown. Here we report that a thermophilic archaeal TnpB enables efficient gene editing in the natural host. Interestingly, the TnpB has different TAM requirements for eliciting cell death and for facilitating gene editing. By systematically characterizing TAM variants, we reveal that the TnpB recognizes a broad range of TAM sequences for gene editing including those that do not elicit apparent cell death. Importantly, TnpB shows a very high targeting specificity on targets flanked by a weak TAM. Taking advantage of this feature, we successfully leverage TnpB for efficient single-nucleotide editing with templated repair. The use of different weak TAM sequences not only facilitates more flexible gene editing with increased cell survival, but also greatly expands targeting scopes, and this strategy is probably applicable to diverse CRISPR-Cas systems.

IntroductionEchinococcus granulosus, known as cystic echinococcosis, is a prominent zoonotic parasitic disease of significant global concern. The definitive hosts serves as the primary reservoir for the transmission of echinococcosis, as well as a main factor in the prevention and control of the disease. Unfortunately, there is currently no commercially available vaccine for these hosts. Nevertheless, DNA vaccines show potential as a feasible strategy for the control and management of parasitic diseases.MethodsIn this study, the EgM123 antigen was selected for its well-documented immunogenic properties to develop a DNA vaccine aimed at combating E. granulosus infection in canines.ResultsThe results showed a marked increase in IgG levels in the group vaccinated with pVAX1-EgM123 DNA compared to the PBS group. Additionally, the cytokines IL-1, IFN-γ, IL-4, and IL-6 were significantly upregulated in the pVAX1-EgM123 DNA vaccine group. Furthermore, in comparison to the PBS control group, the EgM123 DNA vaccine group exhibited a notable 87.85% reduction in worm burden and a 65.00% inhibition in segment development.DiscussionThese findings indicate that the pVAX1-EgM123 DNA vaccine shows promising immunogenicity, successfully eliciting a targeted immune response in canines. Moreover, it significantly diminishes the worm burden and hinders the progression of tapeworms in the pVAX1-EgM123 DNA vaccine group. These findings suggest that the pVAX1-EgM123 DNA vaccine holds promise as a potential candidate vaccine for combating E. granulosus infection in dogs.

Abstract Saccharolobus islandicus REY15A represents one of the very few archaeal models with versatile genetic tools, which include efficient genome editing, gene silencing, and robust protein expression systems. However, plasmid vectors constructed for this crenarchaeon thus far are based solely on the pRN2 cryptic plasmid. Although this plasmid coexists with pRN1 in its original host, early attempts to test pRN1‐based vectors consistently failed to yield any stable host–vector system for Sa. islandicus. We hypothesized that this failure could be due to the occurrence of CRISPR immunity against pRN1 in this archaeon. We identified a putative target sequence in orf904 encoding a putative replicase on pRN1 (target N1). Mutated targets (N1a, N1b, and N1c) were then designed and tested for their capability to escape the host CRISPR immunity by using a plasmid interference assay. The results revealed that the original target triggered CRISPR immunity in this archaeon, whereas all three mutated targets did not, indicating that all the designed target mutations evaded host immunity. These mutated targets were then incorporated into orf904 individually, yielding corresponding mutated pRN1 backbones with which shuttle plasmids were constructed (pN1aSD, pN1bSD, and pN1cSD). Sa. islandicus transformation revealed that pN1aSD and pN1bSD were functional shuttle vectors, but pN1cSD lost the capability for replication. These results indicate that the missense mutations in the conserved helicase domain in pN1c inactivated the replicase. We further showed that pRN1‐based and pRN2‐based vectors were stably maintained in the archaeal cells either alone or in combination, and this yielded a dual plasmid system for genetic study with this important archaeal model.

Abstract The issue of poor sexual performance of some male giant pandas seriously impairs the growth and the genetic diversity of the captive population, yet there is still no clear understanding of the cause of the loss of this ability and its underlying mechanism. In this study, we analyzed the gut microbiota and its function in 72 fecal samples obtained from 20 captive male giant pandas, with an equal allocation between individuals capable and incapable of natural mating. Additionally, we investigated fecal hormone levels and behavioral differences between the two groups. A correlation analysis was then conducted among these factors to explore the influencing factors of their natural mating ability. The results showed significant differences in the composition of gut microbiota between the two groups of male pandas. The capable group had significantly higher abundance of Clostridium sensu stricto 1 (padjusted = .0021, GLMM), which was positively correlated with fatty acid degradation and two‐component system functions (Spearman, padjusted

This meta-analysis aims to systematically compare the efficacy between phacoemulsification (PE) combined with goniosynechialysis (GSL) and PE alone for primary angle-closure disease (PACD) patients. All the data were searched from the PubMed, EMBASE and the Cochrane Library. The Cochrane Handbook was used to evaluate the quality of the included studies. Additionally, this meta-analysis was performed by using the Revman 5.4 software. Nine randomized controlled trials (RCTs) were included in this study. Compared with PE alone group, PE+GSL could result significant reduction in the IOP (MD, 1.81; p = 0.002). In the instrumental subgroup, also more reduction of IOP was shown in the PE+GSL group (MD, 2.11; p = 0.02). In the viscogonioplasty (VGP) subgroup, there was not no statistical difference between PE alone group and PE+GSL group (MD, 1.53; p = 0.11). Also, more reduction of peripheral anterior synechiae (PAS) was shown in the PE+GSL group (MD,59.15; p

Abstract Background Semen cryopreservation has become an essential tool for conservation efforts of the giant panda (Ailuropoda melanoleuca); however, it is severely detrimental to sperm quality. Evidence has shown that antioxidants have the potential to reverse cryopreservation-induced damage in sperm. The purpose of this study was to screen effective antioxidants that could retain sperm quality during cryopreservation and to determine the optimal dose. Seven antioxidant groups, including resveratrol (RSV = 50 μM, RSV = 100 μM, RSV = 150 μM), lycium barbarum polysaccharide (LBP = 2 mg/mL, LBP = 4 mg/mL), laminaria japonica polysaccharides (LJP = 1 mg/mL) or combination (LBP = 2 mg/mL, LJP = 1 mg/mL and RSV = 100 μM) were assessed. Results RSV, LBP, LJP, or a combination of RSV, LBP, and LJP added to the freezing medium significantly improved sperm progressive motility, plasma membrane integrity, acrosome integrity, and mitochondrial activity during the cryopreservation process. Furthermore, the activities of glutathione peroxidase and superoxide dismutase were also improved. The levels of reactive oxygen species and malondialdehyde in semen were notably reduced. Hyaluronidase activity and acrosin activity were significantly increased in LBP-treated sperm. However, sperm total motility and DNA integrity were not significantly different between the groups. Conclusions RSV (50 μM) or LBP (2 mg/mL) are the best candidate antioxidants for inclusion in the freezing medium to improve the quality of giant panda spermatozoa during semen cryopreservation.

Abstract Background Cystic echinococcosis (CE) is a serious parasitic zoonosis caused by the larvae of the tapeworm Echinococcus granulosus. The development of an effective vaccine is one of the most promising strategies for controlling CE. Methods The E. granulosus 3-hydroxyacyl-CoA dehydrogenase (EgHCDH) gene was cloned and expressed in Escherichia coli. The distribution of EgHCDH in protoscoleces (PSCs) and adult worms was analyzed using immunofluorescence. The transcript levels of EgHCDH in PSCs and adult worms were analyzed using quantitative real-time reverse transcription PCR (RT-qPCR). The immune protective effects of the rEgHCDH were evaluated. Results The 924-bp open reading frame sequence of EgHCDH, which encodes a protein of approximately 34 kDa, was obtained. RT-qPCR analysis revealed that EgHCDH was expressed in both the PSCs and adult worms of E. granulosus. Immunofluorescence analysis showed that EgHCDH was mainly localized in the tegument of PSCs and adult worms. Western blot analysis showed that the recombinant protein was recognized by E. granulosus-infected dog sera. Animal challenge experiments demonstrated that dogs immunized with recombinant (r)EgHCDH had significantly higher serum IgG, interferon gamma and interleukin-4 concentrations than the phosphate-buffered saline (PBS) control group. The rEgHCDH vaccine was able to significantly reduce the number of E. granulosus and inhibit the segmental development of E. granulosus compared to the PBS control group. Conclusions The results suggest that rEgHCDH can induce partial immune protection against infection with E. granulosus and could be an effective candidate for the development of new vaccines. Graphical abstract

Line detection is a fundamental technique in image processing. It can extract the required information, while the information that does not need attention can be ignored, thus reducing the amount of data. At the same time, line detection is also the basis of image segmentation and plays an important role in this process. In this paper, we implement a quantum algorithm based on a line detection mask for novel enhanced quantum representation (NEQR). We build a quantum algorithm for line detection in different directions and design a quantum circuit for line detection. The detailed module designed is also provided. On a classical computer, we simulate the quantum method, and the simulation results prove the feasibility of the quantum method. By analyzing the complexity of quantum line detection, we find that the computation complexity of the proposed method is improved compared to some similar edge detection algorithms.

With the rapid development of online shopping, interpretable personalized fashion recommendation using image has attracted increasing attention in recent years. The current work has been able to capture the user’s preferences for visible features and provide visual explanations. However, they ignored the invisible features, such as the material and quality of the clothes, and failed to offer textual explanations. To this end, we propose a Visual and Textual Jointly Enhanced Interpretable (VTJEI) model for fashion recommendations based on the product image and historical review. The VTJEI can provide more accurate recommendations and visual and textual explanations through the joint enhancement of textual information and visual information. Specifically, we design a bidirectional two-layer adaptive attention review model to capture the user’s visible and invisible preferences to the target product and provide textual explanations by highlighting some words. Moreover, we propose a review-driven visual attention model to get a more personalized image representation driven by the user’s preference obtained from the historical review. In this way, we not only realize the joint enhancement of visual information and textual information but also provide a visual explanation by highlighting some regions. Finally, we performed extensive experiments on real datasets to confirm the superiority of our model on Top-N recommendations. We also built a labeled dataset for evaluating our provided visible and invisible explanations quantitatively. The result shows that we can not only provide more accurate recommendations but also can provide both visual and textual explanations.

Cystic echinococcosis (CE) is a cosmopolitan zoonosis caused by the larval stage of Echinococcus granulosus, which affects humans and a wide range of mammalian intermediate hosts. Parasite tetraspanin proteins are crucial for host-parasite interactions, and therefore they may be useful for vaccine development or disease diagnosis. In the present study, the major antigen coding sequence of tetraspanin 11 (Eg-TSP11) from E. granulosus was determined. The results of immunolocalization showed that Eg-TSP11 was mainly located in the tegument of adult worms and protoscoleces. Western blotting analysis showed that the serum from dogs injected with recombinant Eg-TSP11 (rEg-TSP11) could recognize Eg-TSP11 among natural protoscolex proteins. Moreover, the serum from dogs with E. granulosus infection also recognized rEg-TSP11. Serum indirect enzyme-linked immunosorbent assays demonstrated that IgG levels gradually increased after the first immunization with rEg-TSP11 compared with those in the control group. Furthermore, the serum levels of interleukin 4, interleukin 5, and interferon gamma were significantly altered in the rEg-TSP11 group. Importantly, we found that vaccination with rEg-TSP11 significantly decreased worm burden and inhibited segment development in a dog model of E. granulosus infection. Based on these findings, we speculated that rEg-TSP11 might be a potential candidate vaccine antigen against E. granulosus infection in dogs.

The fruit and leaves of mulberry (Morus alba L.) contain a variety of health-beneficial components. At present, although both alcoholic and non-alcoholic mulberry beverages are commercially available, studies on fermented alcoholic beverages mixed with both mulberry fruit and mulberry leaf are rare. In this study, different amounts (1, 2 and 3%, g/mL dry weight) of mulberry leaves were added during the alcoholic fermentation of mulberry juice. After 9 days of fermentation, the 1-deoxynojirimycin (DNJ) content increased from 61.12 ± 3.10 to 153.39 ± 3.98 μg/mL, and the quercetin content increased from 0.45 ± 0.01 to 20.14 ± 0.08 mg/L in the mulberry alcoholic beverages with the addition of mulberry leaves at 2%. Moreover, the ABTS+ scavenging capacity at the end of fermentation for the same sample was enhanced by 40.9%. In addition, the total sugar, total phenols, total anthocyanins, and γ-aminobutyric acid (GABA) contents of the fermented samples all decreased significantly at the end of fermentation. A total of 33 volatile compounds and 17 free amino acids were detected in the fermented alcoholic beverages with mulberry leaves added. The total free amino acid content increased with the increase in mulberry leaf addition. Principal component analysis showed that the addition of mulberry leaves during fermentation increased the contents of GABA, DNJ, total flavonols and protocatechuic acid in mulberry alcoholic beverages. All these studies revealed the dynamic changes in functional components in the alcoholic fermentation of mulberry juices with the addition of mulberry leaves. Overall, the addition of mulberry leaf powder at 2% was selected as the appropriate addition for producing mulberry alcoholic beverages with enhanced nutritional value.

As one of the most widely used recommender systems, movie recommendation plays an important role in our life. However, the data sparsity problem severely hinders the effectiveness of personalized movie recommendation, which requires more rich content information to be utilized. Posters and still frames, which directly display the visual contents of movies, have significant influences on movie recommendation. They not only reveal rich knowledge for understanding movies but also useful for understanding user preferences. However, existing recommendation methods rarely consider aesthetic features, which tell how the movie looks and feels, extracted from these pictures for the movie recommendation. To this end, in this paper, we propose an aesthetic-aware unified visual content matrix factorization (called UVMF-AES) to integrate visual feature learning and recommendation into a unified framework. Specifically, we first integrate the convolutional neural network (CNN) features and aesthetic features into probabilistic matrix factorization. Then we establish a unified optimization framework with these features for the movie recommendation. The experimental results on two real-world datasets show that our proposed method UVMF-AES is significantly superior to the state-of-the-art methods on movie recommendation.

Next basket recommendation with consideration of user sequential shopping behaviors plays a significant role in E-commerce to improve the user experience and service quality. Recently, recurrent neural networks (RNNs), especially attention-based RNN, have been widely adopted in the next basket recommendation. However, existing fixed attention mechanisms are not designed to model the dynamic and diverse characteristics of user appetites. In this paper, we propose an inter-basket and intra-basket adaptive attention network (IIAAN) for the next basket recommendation. Specifically, the inter-basket adaptive attention acts on all historical user baskets to model user's diverse long-term preferences, while the intra-basket adaptive attention is designed to act on item-level in the most recent basket to model user's dynamic and different short-term preferences. Then, we further integrate inter-basket and intra-basket adaptive attentions together to improve recommendation effectiveness. Finally, we evaluate the proposed model IIAAN using three real-world datasets from various E-commerce platforms. Our experimental results show that our model IIAAN significantly outperforms the state-of-the-art approaches for the next basket recommendation.

Lactic acid fermentation is a promising method for developing sandwich seaweed scraps. The objectives of this study were to investigate the effect of fermentation with Lactiplantibacillus plantarum MMB-05, Lactiplantibacillus casei FJAT-7928, mixed bacteria (1:1, v/v) and control on the physicochemical indexes, in vitro antioxidant activity, and volatile compounds of Porphyra yezoensis sauce. Sensory evaluation was also performed. The results indicated that all lactic acid bacteria strains grew well in P. yezoensis sauce after 72 h of fermentation, with the viable cell counts of L. plantarum MMB-05 exceeding 10.0 log CFU/mL, the total phenolic content increasing by 16.54%, and the lactic acid content increasing from 0 to 44.38 ± 0.11 mg/mL. Moreover, the metabolism of these strains significantly increased the content of umami, sweet and sour free amino acids in P. yezoensis sauce. The total antioxidant capacity of L. plantarum MMB-05, L. casei FJAT-7928, mix and control groups increased by 594.59%, 386.49%, 410.27%, and 287.62%, respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) analysis suggested that aldehydes and ketones accounted for the largest proportion, and the relative contents of acids and alcohols in P. yezoensis sauce increased significantly after lactic acid bacteria fermentation. In addition, the analysis of dynamic principal component analysis (PCA) and fingerprinting showed that the volatile components of the four treatment methods could be significantly distinguished. Overall, the L. plantarum MMB-05 could be recommended as an appropriate starter for fermentation of sandwich seaweed scraps, which provides a fundamental knowledge for the utilization of sandwiched seaweed scraps.

This paper presents the design, simulation, fabrication, assembly, and testing of a miniature thermo-pneumatic optofluidic lens. The device comprises two separate zones for air heating and fluid pressing on a flexible membrane. A buried three-dimensional spiral microchannel connects the two zones without pumps or valves. The three-dimensional microfluidic structure is realized using a high-resolution three-dimensional printing technique. Multi-physics finite element simulations are introduced to assess the optimized air chamber design and the low-temperature gradient of the optical liquid. The tunable lens can be operated using a direct-current power supply. The temperature change with time is measured using an infrared thermal imager. The focal length ranges from 5 to 23 mm under a maximum voltage of 6 V. Because of the small size and robust actuation scheme, the device can potentially be integrated into miniature micro-optics devices for the fine-tuning of focal lengths.

Recommender systems, e.g., movie recommendation, play an important role in our life. However, few movie recommendation methods have considered the rich visual content information in posters and still frames, which can be used to alleviate the data sparsity and cold start problems in recommendation. Moreover, no existing paper has taken visual feature learning and recommendation into a unified optimization process. To this end, in this paper, we focus on how to use visual contents to improve the performance of movie recommendation and propose a novel movie recommendation model named unified visual contents matrix factorization (UVMF) that integrates visual feature extraction and recommendation into a unified framework. Specifically, we integrate convolutional neural network into probabilistic matrix factorization, and the model can be trained end-to-end. Moreover, we unfix weights in the last few layers of VGG16 to learn features and adapt them for the movie recommendation task. Finally, the experimental results on real-world data show that UVMF outperforms other benchmark methods in terms of recommendation accuracy.

Multi‐label image classification has attracted considerable attention in machine learning recently. Active learning is widely used in multi‐label learning because it can effectively reduce the human annotation workload required to construct high‐performance classifiers. However, annotation by experts is costly, especially when the number of labels in a dataset is large. Inspired by the idea of semi‐supervised learning, in this study, the authors propose a novel, semi‐supervised multi‐label active learning (SSMAL) method that combines automated annotation with human annotation to reduce the annotation workload associated with the active learning process. In SSMAL, they capture three aspects of potentially useful information – classification prediction information, label correlation information, and example spatial information – and they use this information to develop an effective strategy for automated annotation of selected unlabelled example‐label pairs. The experimental results obtained in this study demonstrate the effectiveness of the authors' proposed approach.

Liquid phase segregation frequently occurs in the process of semi solid die forging, which makes the parts appear "weak point" or "weak region", and usually, the "weak point" or "weak area" is the reason of crack and service condition failure. In order to analyze the influence factors of the liquid phase segregation of the semi solid die forging, DEFORM-3D is used for the numerical simulation of semi-solid die forging forming process of 7075 aluminum alloy, to study the influence rule of forming velocity on the forming process of cup part. Based on the simulation results, the rheological die forging forming of 7075 aluminum alloythe part is conducted to research the influence of forming velocity on the uniformity of microstructure by means of press machine and cup mould. The simulation and experimental results show that as the filling velocity is faster, the forming process is more unstable; under the condition of head temperature of 400 ℃, the forming pressure of 50 MPa, and the alloy temperature 628 ℃, as the forming velocity increases, the liquid phase segregation degree of cup part increases, and the microstructure is far from uniformity. The segregation degree is up to 18.2% as the forming velocity is 5 mm/s.

The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

In most image classification algorithms, the classifier model needs to train a large number of training samples. In practical application, labeling numbers of samples is a tedious and time-consuming task. So, how to select fewer suitable training samples from the numbers of unlabeled samples is a difficulty in the image classification algorithm. This paper proposes a trademark number recognition technique based on active learning algorithm. The method uses the human interaction to get trademark number area, and then uses the projection method to extract character characteristic which using the characteristic to split characters. Finally, use BvSB active learning algorithm to select high information samples which was used to train support vector machine classifier, and use the trained classifier to recognize trademark number. The experimental result shows that the classifier trained by the method has higher classification accuracy in the case of labeled fewer samples.

A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity.

Big data from the Internet of Things may create big challenge for data classification. Most active learning approaches select either uncertain or representative unlabeled instances to query their labels. Although several active learning algorithms have been proposed to combine the two criteria for query selection, they are usually ad hoc in finding unlabeled instances that are both informative and representative and fail to take the diversity of instances into account. We address this challenge by presenting a new active learning framework which considers uncertainty, representativeness, and diversity creation. The proposed approach provides a systematic way for measuring and combining the uncertainty, representativeness, and diversity of an instance. Firstly, use instances’ uncertainty and representativeness to constitute the most informative set. Then, use the kernel k-means clustering algorithm to filter the redundant samples and the resulting samples are queried for labels. Extensive experimental results show that the proposed approach outperforms several state-of-the-art active learning approaches.