Search

Abstract A multi-exit network is an important technique for achieving adaptive inference by dynamically allocating computational resources based on different input samples. The existing works mainly treat the final classifier as the teacher, enhancing the classification accuracy by transferring knowledge to the intermediate classifiers. However, this traditional self-distillation training strategy only utilizes the knowledge contained in the final classifier, neglecting potentially distinctive knowledge in the other classifiers. To address this limitation, we propose a novel multi-level collaborative self-distillation learning strategy (MLCSD) that extracts knowledge from all the classifiers. MLCSD dynamically determines the weight coefficients for each classifier’s contribution through a learning process, thus constructing more comprehensive and effective teachers tailored to each classifier. These new teachers transfer the knowledge back to each classifier through a distillation technique, thereby further improving the network’s inference efficiency. We conduct experiments on three datasets, CIFAR10, CIFAR100, and Tiny-ImageNet. Compared with the baseline network that employs traditional self-distillation, our MLCSD-Net based on ResNet18 enhances the average classification accuracy by 1.18%. The experimental results demonstrate that MLCSD-Net improves the inference efficiency of adaptive inference applications, such as anytime prediction and budgeted batch classification. Code is available at https://github.com/deepzlk/MLCSD-Net .

Abstract Background Artificial intelligence is a growing phenomenon that will soon facilitate wide-scale changes in many professions, and is expected to play an important role in the field of medical education. This study explored the realistic feelings and experiences of nursing undergraduates participating in different stages of artificial intelligence + project task driven learning, and provide a basis for artificial intelligence participation in nursing teaching. Methods We conducted face-to-face semi-structured interviews with nursing undergraduates participating in Nursing Research Course which adopts artificial intelligence + project task driven learning from a medical university in Ningxia from September to November 2023, to understand their experience of using artificial intelligence for learning and the emotional changes at different stages. The interview guide included items about their personal experience and feelings of completing project tasks through dialogue with artificial intelligence, and suggestions for course content. Thematic analysis was used to analyze interview data. This study followed the COREQ checklist. Results According to the interview data, three themes were summarized. Undergraduate nursing students have different experiences in participating in artificial intelligence + project task driven learning at different stages, mainly manifested as diverse emotional experiences under initial knowledge deficiency, the individual growth supported by external forces during the adaptation period, and the expectations and suggestions after the birth of the results in the end period. Conclusions Nursing undergraduates can actively adapt to the integration of artificial intelligence into nursing teaching, dynamically observe students’ learning experience, strengthen positive guidance, and provide support for personalized teaching models, better leveraging the advantages of artificial intelligence participation in teaching.

To clarify the effects of different frying temperatures and grain colors on volatile organic compounds (VOCs) in highland barley (HB) tsampa flour, gas chromatography-ion mobility spectrometry (GC-IMS) was used to analyze the VOCs in two types of HB with two colors, Goumangzi and Kunlun-15. The VOCs were analyzed at different frying temperatures (160, 180, 200, 220 and 240 ℃). The results showed that a total of 62 compounds was detected, among which 44 organic compounds could be accurately identified, including 19 aldehydes, 10 alcohols, 5 ketones, 5 esters, 4 pyrazines and 1 furan. Frying had a significant effect on the composition of VOCs in tsampa flour, with the increase of frying temperature, the total amount of alcohol VOCs tended to decrease gradually, while aldehydes, ketones, esters, pyrazines and furans VOCs tended to increase. Pyrazines, aldehydes and ketones were the characteristic and main flavor substances of HB tsampa flour, and frying at higher temperature (220, 240 ℃) was favorable to their production. The variation of VOCs with frying temperature was more significant in WHB, except for furan VOCs, the relative changes of other compounds were higher than those in BHB. The principal component analysis showed that there were significant differences in the flavor of BHB and WHB tsampa flour, which could be classified into two different flavor types. This study was expected to provide a theoretical basis for the development of technical specifications for the production of highland barley tsampa flour.

In order to promote the modernisation process of rural roads and improve road capacity, the problem of bottleneck sections of rural roads needs to be solved urgently. The phenomenon of wide-road-and-narrow-bridge sections is particularly prominent in rural roads. Based on this, this paper analyses the degree of influence of roadway one-way lane width, bridge deck oneway lane width, motorised vehicles to non-motorised vehicles ratio, and road-bridge connection dimension on the capacity of the wide-road-and-narrow-bridge section based on the combination of VISSIM simulation and random forest algorithm. The result of the coefficient of determination (R2) of the random forest-based capacity prediction model shows that the random forest fits the data very well; the degree of influence on the capacity is in descending order of the bridge deck one-way lane width, motorised vehicles to non-motorised vehicles ratio, roadway one-way lane width and the road-bridge connection dimension. The model can, on the one hand, provide a reference for improving the capacity of bottleneck sections of rural roads; on the other hand, it can provide decision value for the order of measures to be taken when rural roads are rebuilt and expanded, according to the order of importance.

In this study, the effects of inulin, as a fat substitute, on the quality of mung bean protein low-fat plant yogurt were investigated. The mung bean protein yogurt with 3% of sunflower oil was taken as a high-fat yogurt control, the fat-replacement effect of inulin was evaluated by analyzing the effects of different concentrations of inulin (2%, 4% and 6%) on the viscoelasticity, texture, water holding capacity, microstructure and sensory quality of mung bean protein low-fat yogurt (with 1% of sunflower oil). The results indicated that compared with the mung bean protein high-fat yogurt, the viscoelasticity, hardness, chewiness, water holding capacity, and sensory quality of mung bean protein low-fat plant yogurt with 2% of inulin were equal to those of mung bean protein high-fat yogurt (P>0.05), with a uniform and dense protein network structure. The hardness and chewiness of mung bean protein low-fat yogurt with 4% inulin were significantly improved by 21.56% and 32.34% (P

This study investigated the effect of oat β-glucan as a fat substitute on the structure formation, texture, and sensory properties of pea protein yogurt. The results showed that the incorporation of 0.5% β-glucan significantly accelerated the lactic acid bacteria-induced fermentation, with the time for reaching the target pH of 4.6 shortened from 3.5 h to 3 h (p < 0.05); increased the plastic module (G′) from 693 Pa to 764 Pa when fermenting 3 h (p < 0.05); and enhanced the water-holding capacity from 77.29% to 82.15% (p < 0.05). The identification of volatile organic compounds (VOCs) in low-fat pea protein yogurt by GC-IMS revealed a significant decrease in aldehydes and a significant increase in alcohols, ketones and acids in the pea yogurt after fermentation (p < 0.05). Among them, the levels of acetic acid, acetone, 2,3-butanedione, 3-hydroxy-2-butanone, and ethyl acetate all significantly increased with the addition of oat β-glucan (p < 0.05), thereby providing prominent fruity, sweet, and creamy flavors, respectively. Combined with the results of sensory analysis, the quality characteristics of pea protein yogurt with 1% oil by adding 1% oat β-glucan were comparable to the control sample with 3% oil. Therefore, oat β-glucan has a good potential for fat replacement in pea protein yogurt.

Siliqua minima (Gmelin, 1791) is an important economic shellfish species belonging to the family Pharidae. To date, the complete mitochondrial genome of only one species in this family (Sinonovacula constricta) has been sequenced. Research on the Pharidae family is very limited; to improve the evolution of this bivalve family, we sequenced the complete mitochondrial genome of S. minima by next-generation sequencing. The genome is 17,064 bp in length, consisting of 12 protein-coding genes (PCGs), 22 transfer RNA genes (tRNA), and two ribosomal RNA genes (rRNA). From the rearrangement analysis of bivalves, we found that the gene sequences of bivalves greatly variable among species, and with closer genetic relationship, the more consistent of the gene arrangement is higher among the species. Moreover, according to the gene arrangement of seven species from Adapedonta, we found that gene rearrangement among families is particularly obvious, while the gene order within families is relatively conservative. The phylogenetic analysis between species of the superorder Imparidentia using 12 conserved PCGs. The S. minima mitogenome was provided and will improve the phylogenetic resolution of Pharidae species.

The complete mitochondrial genome of the Omphalius rusticus has been determined. The complete genome is 18,067 bp and contained 13 protein-coding genes, two rRNA genes and 22 tRNA genes. The overall base composition is 33.48% (A), 33.52% (T), 15.58% (G) and 17.42% (C). The all start codon for 13 protein-coding genes is ATG and the most common termination codon is TAA. The phylogenetic tree showed that O. rusticus is most closely related to the Tectus pyramis. We suggest that this result will further supplement the genome information in mitochondria of the family Tegulidae and facilitate the study on population genetics.

The complete mitochondrial genome of the Littorina brevicula was determined in this study. The complete mitogenome (mtDNA) is 16,356 base pairs (bp) in length and contains 13 protein-coding genes, two rRNA genes, and 22 tRNA genes. The control region was divided into two parts. The overall base composition of the genome in descending order was 35.33%—T, 28.41%—A, 20.43%—C, and 15.81%—G. In 13 protein-coding genes, 12 genes start with ATG, except nad5 starts with ATT. For the stop codon, seven genes end with TAA, atp6, nad41, and nad3 end with TAG. Phylogenetic analysis indicated that L. brevicula is close to Naticidea family. This study first determined the complete mitochondrial genome of L. brevicula. It would be a supplement for the genetic analysis of L. brevicula and promote the phylogenetic of Littorinidea.

The complete mitochondrial genome of Nerita yoldii has been determined. The whole sequence was 15,719 bp in length and included 13 protein-coding genes, 22 transfer RNA genes, and two ribosomal RNA genes (12S rRNA and 16S rRNA). The overall base composition is A 29.5%, C 13.8%, G 21.5%, and T 35.2%. In 13 protein-coding genes, the nad2, nad5, and nad6 gene start with ATT, whereas nad4 started with ATA, the other nine genes start with ATG. For the stop codon, COX1, COX3, nad3, and atp8 end with TAG, other nine genes end with TAA. Phylogenetic tree was constructed based on 13 protein-coding genes sequences of Archaeogastropoda species, and the result showed that N. yoldii is most closely related to Clithon retropictus. These mitogenome sequence data will be useful for population genetics and phylogenetic analysis of the family Neritidae.

The complete mitochondrial genome of Nerita albicilla was determined. The mitochondrial genome is 15,314 bp in length, comprising two ribosomal RNA (12S and 16S) genes, 13 protein-coding genes, and 22 transfer RNA genes. Of these 37 genes identified, seven protein-coding genes, and eight transfer RNA genes are encoded on the heavy strand and the other genes on the light strand. This gene order is consistent with the previously published mitochondrial genomes of the other neritid species. The length of 22 tRNAs ranges from 65 bp to 73 bp and the overall base composition is 14.9% of C, 20.7% of G, 34.0% of T, and 30.5% of A. The phylogenetic tree was constructed based on 13 protein-coding genes of N. albicilla and other 13 Archaeogastropoda species, Argopecten purpuratus as outgroup using the Neighbor-joining method, the tree showed that N. albicilla is most closely related to the Nerita yoldii. We believe that this result will further supplement the genome information in mitochondria of the family Neritidae and facilitate the study on population genetic.

The complete mitochondrial genome of the Chasmagnathus convexus has been determined in this study. The complete genome (mtDNA) was 15,107 bp in length and contained 13 protein-coding genes, 1 rRNA genes, and 22 tRNA genes. The overall base composition of the genome in descending order was 34.2% T, 32.8% A, 20.9% C, and 12.1% G. In 13 protein-coding genes, most of the protein-coding genes start with ATG (COX1, COX2, COX3 and ATP8) and ATT (NAD5, NAD4, NAD4L, NAD6, ATP6 and NAD2), only CYTB, NAD3, and NAD1 genes start with ATA. For the stop codon, only NAD2 end with TAG, the other 12 genes end with TAA. Phylogenetic analysis indicated that C. convexus is closely related to Hemigrapsus penicillatus family. It would be a supplement for the genetic analysis of C. convexus and promote the phylogenesis of Grapsidae.

The complete mitochondrial genome of the Apogonichthys lineatus has been determined in this study. The complete genome (mtDNA) is 16,510 base pairs in length and contains 13 protein-coding genes, 2 rRNA genes, and 22 tRNA genes. The overall base composition of the genome in descending order was28.4% C, 27.3% A, 26.7% T, 17.6% G. In 13 protein-coding genes, most of the protein-coding genes start with ATG, except ND1 start with ATA, COX3 and ND5 start with ATT. For the stop codon, nine protein-coding genes end with TAA, two protein-coding genes end with TAG (ND3 and ND1) and two protein-coding genes end with TGA (ND4 and COX2). Phylogenetic analysis indicated that A. lineatus is close to Pterapogon kauderni families. This study was determined the complete mitochondrial genome of Apogonidae species. It would be a supplement for the genetic analysis of A. lineatus and promote the phylogenetic of Apogonidae.

Herein, we first determined the complete mitochondrial genome of Macridiscus multifarius in this study. The circular mitochondrial genome is 20,248 bp in length, consisting of 12 protein-coding genes, 22 tRNA genes and 2 ribosomal RNA genes. The nucleotide composition is 28.6% of A, 39.3% of T, 10.4% of C and 21.7% of G. In 12 protein-coding genes, Cytb, atp6, and nad6 start with ATG, nad1,3 and COX2 with GTT, COX3 and nad4 with ATT, and COX1 and nad5 with ATA. For the stop codon, seven genes with TAA, nad3,4,5 and COX3 with TAG, atp8 ends with AAA. The phylogenetic tree was constructed based on 12 protein-coding genes of 11 species using the Neighbour-joining method, and the result showed that the M. multifarius was closed to the Ruditapes philippinarum. The mitochondrial genome would be helpful for the study of population genetic and phylogenetic analysis of Marcidiscus.

We first determined the complete mitochondrial genome of Fusinus longicaudus (Gastropoda: Fasciolariidae). The circular mitochondrial genome is 16,319 bp in length, consisting of 13 protein-coding genes, 22 tRNA genes, and two ribosomal RNA genes. The nucleotide composition is 14.7% of C, 15.9% of G, 38.9% of T, and 30.5% of A. The control region with the length of 1029 bp is between tRNAPhe and COX3 genes. In 13 protein-coding genes, the nad4 gene starts with ATT, the other eleven genes start with ATG. For the stop codon, atp6, nad4l, nad5 and nad6 end with TAG, other 9 genes end with TAA. The phylogenetic tree was constructed based on 13 protein-coding genes of F. longicaudus and other 13 Neogastropoda species, Perna viridis as outgroup using the Neighbor-joining method, the result showed that F. longicaudus is most closely related to the Buccinidae. The mitochondrial genome would be helpful for the study of population genetic and phylogenetic analysis of the family Fasciolariidae.

Herein, we first determined the complete mitochondrial genome of Turricula nelliae spurius in this study. The circular mitochondrial genome is 16,450 bp in length, consisting of 13 protein-coding genes, 22 tRNA genes, and two ribosomal RNA genes. The nucleotide composition is 15.0% of C, 15.8% of G, 38.0% of T, and 31.2% of A. The control region is between tRNAPhe and COX3 genes and has 1,144 bp. In 13 protein-coding genes, three genes (nad2, nad4, atp6) start with ATA, the other 10 genes are with ATG. For the stop codon, nad3 and nad4l end with TAG, other 11 genes end with TAA. The phylogenetic tree was constructed based on 13 protein-coding genes of T. nelliae spurius and other 11 species using the Neighbor-joining method, and the result showed that T. nelliae spurius is closed to the Gemmuloborsonia moosai and clustered in the same branch with its same family species—Lophiotoma cerithiformis. The mitochondrial genome would be helpful for the study of population genetic and phylogenetic analysis of the family Turridae.

The complete mitochondrial genome of the Epitonium scalare has been determined in this study. The complete genome (mtDNA) is 15,140 base pairs (bp) in length and contained of 13 protein-coding genes, two rRNA genes, and 22 tRNA genes. The control region was divided into two parts. The overall base composition of the genome in descending order was 41.1%—T, 28.3%—A, 19.2%—G, and 11.4%—C. In 13 protein-coding genes, COX3, atp6, and nad1 start with ATA. For the stop codon, 11 genes with TAA, COX3, and nad3 end with TAG. Phylogenetic analysis indicated that E. scalare is not closely to any other families and separate into a single branch. This study was the first study that determined the complete mitochondrial genome of Epitonidae species. It would be a supplement for the genetic analysis of E. scalare and promote the phylogenetic of Epitonidae.

It is well known that the unusual expression of long non-coding RNAs (lncRNAs) is closely related to the physiological and pathological processes of diseases. Therefore, inferring the potential lncRNA−disease associations are helpful for understanding the molecular pathogenesis of diseases. Most previous methods have concentrated on the construction of shallow learning models in order to predict lncRNA-disease associations, while they have failed to deeply integrate heterogeneous multi-source data and to learn the low-dimensional feature representations from these data. We propose a method based on the convolutional neural network with the attention mechanism and convolutional autoencoder for predicting candidate disease-related lncRNAs, and refer to it as CNNDLP. CNNDLP integrates multiple kinds of data from heterogeneous sources, including the associations, interactions, and similarities related to the lncRNAs, diseases, and miRNAs. Two different embedding layers are established by combining the diverse biological premises about the cases that the lncRNAs are likely to associate with the diseases. We construct a novel prediction model based on the convolutional neural network with attention mechanism and convolutional autoencoder to learn the attention and the low-dimensional network representations of the lncRNA−disease pairs from the embedding layers. The different adjacent edges among the lncRNA, miRNA, and disease nodes have different contributions for association prediction. Hence, an attention mechanism at the adjacent edge level is established, and the left side of the model learns the attention representation of a pair of lncRNA and disease. A new type of lncRNA similarity and a new type of disease similarity are calculated by incorporating the topological structures of multiple bipartite networks. The low-dimensional network representation of the lncRNA-disease pairs is further learned by the autoencoder based convolutional neutral network on the right side of the model. The cross-validation experimental results confirm that CNNDLP has superior prediction performance compared to the state-of-the-art methods. Case studies on stomach cancer, breast cancer, and prostate cancer further show the ability of CNNDLP for discovering the potential disease lncRNAs.

Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Most of recent methods predict disease miRNAs by integrating the similarities and associations of miRNAs and diseases. However, these methods fail to learn the deep features of the miRNA similarities, the disease similarities, and the miRNA⁻disease associations. We propose a dual convolutional neural network-based method for predicting candidate disease miRNAs and refer to it as CNNDMP. CNNDMP not only exploits the similarities and associations of miRNAs and diseases, but also captures the topology structures of the miRNA and disease networks. An embedding layer is constructed by combining the biological premises about the miRNA⁻disease associations. A new framework based on the dual convolutional neural network is presented for extracting the deep feature representation of associations. The left part of the framework focuses on integrating the original similarities and associations of miRNAs and diseases. The novel miRNA and disease similarities which contain the topology structures are obtained by random walks on the miRNA and disease networks, and their deep features are learned by the right part of the framework. CNNDMP achieves the superior prediction performance than several state-of-the-art methods during the cross-validation process. Case studies on breast cancer, colorectal cancer and lung cancer further demonstrate CNNDMP’s powerful ability of discovering potential disease miRNAs.

BackgroundThe identification of human disease-related microRNAs (disease miRNAs) is important for further investigating their involvement in the pathogenesis of diseases. More experimentally validated miRNA-disease associations have been accumulated recently. On the basis of these associations, it is essential to predict disease miRNAs for various human diseases. It is useful in providing reliable disease miRNA candidates for subsequent experimental studies.Methodology/principal findingsIt is known that miRNAs with similar functions are often associated with similar diseases and vice versa. Therefore, the functional similarity of two miRNAs has been successfully estimated by measuring the semantic similarity of their associated diseases. To effectively predict disease miRNAs, we calculated the functional similarity by incorporating the information content of disease terms and phenotype similarity between diseases. Furthermore, the members of miRNA family or cluster are assigned higher weight since they are more probably associated with similar diseases. A new prediction method, HDMP, based on weighted k most similar neighbors is presented for predicting disease miRNAs. Experiments validated that HDMP achieved significantly higher prediction performance than existing methods. In addition, the case studies examining prostatic neoplasms, breast neoplasms, and lung neoplasms, showed that HDMP can uncover potential disease miRNA candidates.ConclusionsThe superior performance of HDMP can be attributed to the accurate measurement of miRNA functional similarity, the weight assignment based on miRNA family or cluster, and the effective prediction based on weighted k most similar neighbors. The online prediction and analysis tool is freely available at http://nclab.hit.edu.cn/hdmpred.

[This corrects the article on p. e70204 in vol. 8.].

SMN (Survival motor neuron protein) was characterized as a dimethyl-arginine binding protein over ten years ago. TDRD3 (Tudor domain-containing protein 3) and SPF30 (Splicing factor 30 kDa) were found to bind to various methyl-arginine proteins including Sm proteins as well later on. Recently, TDRD3 was shown to be a transcriptional coactivator, and its transcriptional activity is dependent on its ability to bind arginine-methylated histone marks. In this study, we systematically characterized the binding specificity and affinity of the Tudor domains of these three proteins quantitatively. Our results show that TDRD3 preferentially recognizes asymmetrical dimethylated arginine mark, and SMN is a very promiscuous effector molecule, which recognizes different arginine containing sequence motifs and preferentially binds symmetrical dimethylated arginine. SPF30 is the weakest methyl-arginine binder, which only binds the GAR motif sequences in our library. In addition, we also reported high-resolution crystal structures of the Tudor domain of TDRD3 in complex with two small molecules, which occupy the aromatic cage of TDRD3.

Expansion of the CGG trinucleotide repeat in the 5'-untranslated region of the FMR1, fragile X mental retardation 1, gene results in suppression of protein expression for this gene and is the underlying cause of Fragile X syndrome. In unaffected individuals, the FMRP protein, together with two additional paralogues (Fragile X Mental Retardation Syndrome-related Protein 1 and 2), associates with mRNA to form a ribonucleoprotein complex in the nucleus that is transported to dendrites and spines of neuronal cells. It is thought that the fragile X family of proteins contributes to the regulation of protein synthesis at sites where mRNAs are locally translated in response to stimuli.Here, we report the X-ray crystal structures of the non-canonical nuclear localization signals of the FXR1 and FXR2 autosomal paralogues of FMRP, which were determined at 2.50 and 1.92 Å, respectively. The nuclear localization signals of the FXR1 and FXR2 comprise tandem Tudor domain architectures, closely resembling that of UHRF1, which is proposed to bind methylated histone H3K9.The FMRP, FXR1 and FXR2 proteins comprise a small family of highly conserved proteins that appear to be important in translational regulation, particularly in neuronal cells. The crystal structures of the N-terminal tandem Tudor domains of FXR1 and FXR2 revealed a conserved architecture with that of FMRP. Biochemical analysis of the tandem Tudor domains reveals their ability to preferentially recognize trimethylated peptides in a sequence-specific manner.This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.

The hard-shelled mussel, Mytilus unguiculatus, is one of main aquaculture bivalve species in Southeast China Sea, and excellent growth characteristics. For mussel breeding, farmers use wild individuals to multiply the cultured populations. However, blind selection of wild parents has inevitably resulted in inbreeding and decreased genetic variation. In this study, four wild specimens groups (ZSW, WZW, NNW, and FZW) and four cultured specimens groups (ZSC, WZC, NDC, and FZC) of M. unguiculatus were used to analyze their genetic diversity, population structure and understand the relationship between the wild and cultured specimens groups. The results showed that haplotype diversity (h) of the cultured specimens groups (from 0.621 to 0.797; average, 0.717) was higher than that of three wild specimens groups (ZSW, WZW, and NNW; from 0.428 to 0.668; average, 0.560). The pairwise FST values suggested that only the FZW sample showed significant divergence from the others. The wild and cultured ZS and WZ specimens groups were similar, and the wild and cultured ND specimens groups were crossed. Thus, we need to establish genetic protection units for M. unguiculatus, limit the selection of breeding parents, and maintain a high-quality germplasm bank for M. unguiculatus. [ABSTRACT FROM AUTHOR]

The freshwater discharge from river and ocean current system influenced the population genetic structure of marine mollusk organisms via promoting or limiting planktonic larval dispersal. The clam, Meretrix meretrix, is an important aquaculture species in the coastal regions of China. However, the previous studies of genetic information about M. meretrix were vague. None integrated research to reveal the population genetic and structure of M. meretrix in China from north to south. In this study, we investigated the genetic variation of seven location samples distributing the China coastline from north to south by mitochondrial DNA (COI and Cytb genes). The genetic diversity of seven samples was in a high level (h = 0.879-0.949, π =0.0033-0.0110). The Bayesian skyline plots showed that the samples were a stable population. The genetic divergence of seven samples was suggested that there was detected two obviously groups from pairwise FST values and networks. This differentiation was conformed to the geographic of the sampling sites. However, within the groups, the gene flow of the samples was frequency and showed non-significantly divergence. The results provided insights that the Yangtze diluting water and the ocean currents system resulted in the reduction of gene exchange from north to south during the spawning period and expanded the genetic divergence of M. meretrix between north and south samples. We believed that the results could provide genetic insights for fisheries management to plan the fisheries policy of M. meretrix and protect the natural resource. [ABSTRACT FROM AUTHOR]

The clam Meretrix lamarckii is an ecologically and economically important species in the coastal regions of China. In order to characterize the genetic diversity and population structure of M. lamarckii, a 750 bp region of mitochondrial COIII gene and an 822 bp region of 12S rRNA gene were sequenced and analyzed for 118 and 105 individuals from five populations (ZS, WZ, ZP, ST and ZJ) in the Southeast coastal areas of China, respectively. Results revealed that 33 haplotypes were defined in COIII gene, and 30 haplotypes were defined in 12S rRNA gene. The pairwise Fst values between the ZS population and other four populations were range from 0.122~0.154 (COIII, P< 0.05) and 0.052~0.228 (12S rRNA, P<0.05), respectively. The revealed that ZS population was significant divergence from other four populations, and no significant genetic divergence among WZ, ZP, ST and ZJ populations. Moreover, results from the median-joining network, plot of STRUCTURE and the UPGMA trees were similar to pairwise Fst values. Results from AMOVA indicated that the genetic variation of M. lamarckii populations was mainly from the variation within populations (COIII: 93.27%, 12S rRNA: 92.32%). The results of neutrality tests combined with the mismatch distribution indicated recent population expansion of M. lamarckii on large spatial scales in the period of late Pleistocene (0.1-0.12 Ma). [ABSTRACT FROM AUTHOR]

Motivation: Identifying microRNAs associated with diseases (disease miRNAs) is helpful for exploring the pathogenesis of diseases. Because miRNAs fulfill function via the regulation of their target genes and because the current number of experimentally validated targets is insufficient, some existing methods have inferred potential disease miRNAs based on the predicted targets. It is difficult for these methods to achieve excellent performance due to the high false-positive and false-negative rates for the target prediction results. Alternatively, several methods have constructed a network composed of miRNAs based on their associated diseases and have exploited the information within the network to predict the disease miRNAs. However, these methods have failed to take into account the prior information regarding the network nodes and the respective local topological structures of the different categories of nodes. Therefore, it is essential to develop a method that exploits the more useful information to predict reliable disease miRNA candidates. Results: miRNAs with similar functions are normally associated with similar diseases and vice versa. Therefore, the functional similarity between a pair of miRNAs is calculated based on their associated diseases to construct a miRNA network. We present a new prediction method based on random walk on the network. For the diseases with some known related miRNAs, the network nodes are divided into labeled nodes and unlabeled nodes, and the transition matrices are established for the two categories of nodes. Furthermore, different categories of nodes have different transition weights. In this way, the prior information of nodes can be completely exploited. Simultaneously, the various ranges of topologies around the different categories of nodes are integrated. In addition, how far the walker can go away from the labeled nodes is controlled by restarting the walking. This is helpful for relieving the negative effect of noisy data. For the diseases without any known related miRNAs, we extend the walking on a miRNA-disease bilayer network. During the prediction process, the similarity between diseases, the similarity between miRNAs, the known miRNA-disease associations and the topology information of the bilayer network are exploited. Moreover, the importance of information from different layers of network is considered. Our method achieves superior performance for 18 human diseases with AUC values ranging from 0.786 to 0.945. Moreover, case studies on breast neoplasms, lung neoplasms, prostatic neoplasms and 32 diseases further confirm the ability of our method to discover potential disease miRNAs. [ABSTRACT FROM AUTHOR]

Background: Expansion of the CGG trinucleotide repeat in the 5′-untranslated region of the FMR1, fragile X mental retardation 1, gene results in suppression of protein expression for this gene and is the underlying cause of Fragile X syndrome. In unaffected individuals, the FMRP protein, together with two additional paralogues (Fragile X Mental Retardation Syndrome-related Protein 1 and 2), associates with mRNA to form a ribonucleoprotein complex in the nucleus that is transported to dendrites and spines of neuronal cells. It is thought that the fragile X family of proteins contributes to the regulation of protein synthesis at sites where mRNAs are locally translated in response to stimuli. Methodology/Principal Findings: Here, we report the X-ray crystal structures of the non-canonical nuclear localization signals of the FXR1 and FXR2 autosomal paralogues of FMRP, which were determined at 2.50 and 1.92 Å, respectively. The nuclear localization signals of the FXR1 and FXR2 comprise tandem Tudor domain architectures, closely resembling that of UHRF1, which is proposed to bind methylated histone H3K9. Conclusions: The FMRP, FXR1 and FXR2 proteins comprise a small family of highly conserved proteins that appear to be important in translational regulation, particularly in neuronal cells. The crystal structures of the N-terminal tandem Tudor domains of FXR1 and FXR2 revealed a conserved architecture with that of FMRP. Biochemical analysis of the tandem Tudor doamins reveals their ability to preferentially recognize trimethylated peptides in a sequence-specific manner. Enhanced version: This article can also be viewed as an enhanced version (http://plosone.org/enhanced/pone.0013559/) in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1. [ABSTRACT FROM AUTHOR]

Tudor domains are protein modules that mediate protein-protein interactions, potentially by binding to methylated ligands. A group of germline specific single and multiTudor domain containing proteins (TDRDs) represented by drosophila Tudor and its mammalian orthologs Tdrd1, Tdrd4/RNF17, and Tdrd6 play evolutionarily conserved roles in germinal granule/nuage formation and germ cell specification and differentiation. However, their physiological ligands, and the biochemical and structural basis for ligand recognition, are largely unclear. Here, by immunoprecipitation of endogenous murine Piwi proteins (Miwi and Mili) and proteomic analysis of complexes related to the piRNA pathway, we show that the TDRD group of Tudor proteins are physiological binding partners of Piwi family proteins. in addition, mass spectrometry indicates that arginine residues in RG repeats at the N-termini of Miwi and Mili are methylated in vivo. Notably, we found that Tdrkh/Tdrd2, a novel single Tudor domain containing protein identified in the Miwi compiex, is expressed in the cytoplasm of male germ cells and directly associates with Miwi. Mutagenesis studies mapped the Miwi-Tdrkh interaction to the very N-terminal RG/RA repeats of Miwi and showed that the Tdrkh Tudor domain is critical for binding. Furthermore, we have solved the crystal structure of the Tdrkh Tudor domain, which revealed an aromatic binding pocket and negatively charged binding surface appropriate for accommodating methylated arginine. Our findings identify a methylation-directed protein interaction mechanism in germ cells mediated by germline Tudor domains and methylated Piwi family proteins, and suggest a complex mode of regulating the organization and function of Piwi proteins in piRNA silencing pathways. [ABSTRACT FROM AUTHOR]

Background In recent years, with the development of mobile medicine and telemedicine technology, health management models such as Internet hospitals, online and offline cooperation have gradually become a development trend. However, the elderly have limitations in the use of "Internet+" technology, which affects the mobile health of the elderly, and develops a remote management model based on family members, helping improve the coverage and efficiency of health management for the elderly. Objective To construct an "Internet+" family nursing management model for the elderly, focusing on the contracting problem of the elderly in the context of contracted family doctor services. Methods From June 2020 to February 2021, the "Internet+" family nursing management model for the elderly was preliminarily formulated according to the policies related to the health management of the elderly, combined with domestic and foreign literature research and preliminary basic research. Applying the Delphi method, 15 experts were selected for two rounds of expert consultation, forming the final draft of the "Internet+" family nursing management model for the elderly. Results The positive coefficients of the two rounds of expert consultation were 100%, with the authority coefficients of 0.87 for both, and Kendall coordination coefficients of 0.253 and 0.226, respectively (P