The genomes of obligately host-restricted bacteria suffer from accumulating mildly deleterious mutations, resulting in marked size reductions. Psyllids (Hemiptera) are phloem sap-sucking insects with a specialized organ called the bacteriome, which typically harbors two vertically transmitted bacterial symbionts: the primary symbiont \"Candidatus Carsonella ruddii\" (Gammaproteobacteria) and a secondary symbiont that is phylogenetically diverse among psyllid lineages. The genomes of several Carsonella lineages were revealed to be markedly reduced (158-174‍ ‍kb), AT-rich (14.0-17.9% GC), and structurally conserved with similar gene inventories devoted to synthesizing essential amino acids that are scarce in the phloem sap. However, limited genomic information is currently available on secondary symbionts. Therefore, the present study investigated the genomes of the bacteriome-associated dual symbionts, Secondary_AM (Gammaproteobacteria) and Carsonella_AM, in the mulberry psyllid Anomoneura mori (Psyllidae). The results obtained revealed that the Secondary_AM genome is as small and AT-rich (229,822 bp, 17.3% GC) as those of Carsonella lineages, including Carsonella_AM (169,120 bp, 16.2% GC), implying that Secondary_AM is an evolutionarily ancient obligate mutualist, as is Carsonella. Phylogenomic ana-lyses showed that Secondary_AM is sister to \"Candidatus Psyllophila symbiotica\" of Cacopsylla spp. (Psyllidae), the genomes of which were recently reported (221-237‍ ‍kb, 17.3-18.6% GC). The Secondary_AM and Psyllophila genomes showed highly conserved synteny, sharing all genes for complementing the incomplete tryptophan biosynthetic pathway of Carsonella and those for synthesizing B vitamins. However, sulfur assimilation and carotenoid-synthesizing genes were only retained in Secondary_AM and Psyllophila, respectively, indicating ongoing gene silencing. Average nucleotide identity, gene ortholog similarity, genome-wide synteny, and substitution rates suggest that the Secondary_AM/Psyllophila genomes are more labile than Carsonella genomes.

Over a hundred risk genes underlie risk for autism spectrum disorder (ASD) but the extent to which they converge on shared downstream targets to increase ASD risk is unknown. To test the hypothesis that cellular context impacts the nature of convergence, here we apply a pooled CRISPR approach to target 29 ASD loss-of-function genes in human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells, glutamatergic neurons, and GABAergic neurons. Two distinct approaches (gene-level and network-level analyses) demonstrate that convergence is greatest in mature glutamatergic neurons. Convergent effects are dynamic, varying in strength, composition, and biological role between cell types, increasing with functional similarity of the ASD genes examined, and driven by cell-type-specific gene co-expression patterns. Stratification of ASD genes yield targeted drug predictions capable of reversing gene-specific convergent signatures in human cells and ASD-related behaviors in zebrafish. Altogether, convergent networks downstream of ASD risk genes represent novel points of individualized therapeutic intervention.

The study of antibodies in jawed vertebrates (gnathostomes) provides every immunologist with a bird\'s eye view of how human immunoglobulins (Igs) came into existence and subsequently evolved into their present forms. It is a fascinating Darwinian history of conservation on the one hand and flexibility on the other, exemplified by the Ig heavy chain (H) isotypes IgM and IgD/W, respectively. The cartilaginous fish (e.g., sharks) Igs provide a glimpse of \"how everything got off the ground,\" while the amphibians (e.g., the model Xenopus) reveal how the adaptive immune system made an about face with the emergence of Ig isotype switching and IgG-like structure/function. The evolution of mucosal Igs is a captivating account of malleability, convergence, and conservation, and a call to arms for future study! In between there are spellbinding chronicles of antibody evolution in each class of vertebrates and rather incredible stories of how antibodies can adapt to occupy niches, for example, single-domain variable regions, cold-adapted Igs, convergent mechanisms to dampen antibody function, provision of mucosal defense, and many more. The purpose here is not to provide an encyclopedic examination of antibody evolution, but rather to hit the high points and entice readers to appreciate how things \"came to be.\"

Complex-valued convolutional neural networks (CVCNNs) have been demonstrated effectiveness in classifying complex signals and synthetic aperture radar (SAR) images. However, due to the introduction of complex-valued parameters, CVCNNs tend to become redundant with heavy floating-point operations. Model sparsity is emerged as an efficient method of removing the redundancy without much loss of performance. Currently, there are few studies on the sparsity problem of CVCNNs. Therefore, a complex-valued soft-log threshold reweighting (CV-SLTR) algorithm is proposed for the design of sparse CVCNN to reduce the number of weight parameters and simplify the structure of CVCNN. On one hand, considering the difference between complex and real numbers, we redefine and derive the complex-valued log-sum threshold method. On the other hand, by considering the distinctive characteristics of complex-valued convolutional (CConv) layers and complex-valued fully connected (CFC) layers of CVCNNs, the complex-valued soft and log-sum threshold methods are respectively developed to prune the weights of different layers during the forward propagation, and the sparsity thresholds are optimized during the backward propagation by inducing a sparsity budget. Furthermore, different optimizers can be integrated with CV-SLTR. When stochastic gradient descent (SGD) is used, the convergence of CV-SLTR is proved if Lipschitzian continuity is satisfied. Experiments on the RadioML 2016.10A and S1SLC-CVDL datasets show that the proposed algorithm is efficient for the sparsity of CVCNNs. It is worth noting that the proposed algorithm has fast sparsity speed while maintaining high classification accuracy. These demonstrate the feasibility and potential of the CV-SLTR algorithm.

BACKGROUND: The aim of the study was to investigate the association of parameters related to accommodation and convergence and axial elongation in basic intermittent exotropia (IXT) patients and the potential clinical predictors of axial length (AL) growth.
METHODS: A total of 140 basic IXT patients were recruited in this study. The medians of AL growth in different age brackets were chosen to divide the subjects into group A (slower axial elongation group, n = 69) and group B (faster axial elongation group, n = 71). Parameters of dominant and nondominant eyes were compared and analyzed during the 12-month follow-up period. The parameters, including baseline refraction, angle of deviation, Newcastle control score (NCS), accommodative amplitude (AMP), accommodative facility (AMF), accommodative response, positive or negative relative accommodation (PRA/NRA), and near point of convergence (NPC), were analyzed via univariate and multivariate regression.
RESULTS: Subjects in the faster axial elongation group tended to have more myopic spherical equivalents (t = 3.956, p < 0.001), greater AMPs of dominant eyes (t = -2.238, p = 0.027), and fewer near points of convergence (t = 2.347, p = 0.020) than in the slower axial elongation group. For dominant eyes, logistic and linear regression analysis revealed that more negative spherical equivalents (OR = 0.603, p < 0.001; β = -0.045, p < 0.001), greater AMPs (OR = 1.201, p = 0.027; β = 0.023, p = 0.010), and less near points of convergence (OR = 0.883, p = 0.021; β = -0.012, p = 0.019) were correlated with the faster axial elongation. For nondominant eyes, a more myopic spherical equivalent (OR = 0.682; p = 0.001; β = -0.029, p = 0.005) was the only parameter correlated with faster axial elongation through regression analysis.
CONCLUSIONS: In children with basic IXT, faster axial elongation in the dominant eyes was associated with more myopic spherical equivalents, greater AMPs, and lower NPCs. These accommodative parameters can serve as potential clinical indicators for monitoring myopia progression in addition to AL.

We introduce an analytical methodological framework that links knowledge generation efficiency with economic efficiency and the corresponding environmental impact for 199 European Regions during 2000-2018, using a benchmarking approach and especially a chain network DEA technique. A clear trade-off between knowledge generation efficiency and productive performance emerges. European regions which exhibit high innovation efficiency enjoy higher overall performance compared to their counterparts. In a second stage, we investigate the convergence patterns of the examined regions with respect to all the three facets of the estimated efficiency where the coexistence of multi-type convergence clubs is revealed.

A neural network model is constructed to solve convex quadratic multi-objective programming problem (CQMPP). The CQMPP is first converted into an equivalent single-objective convex quadratic programming problem by the mean of the weighted sum method, where the Pareto optimal solution (POS) are given by diversifying values of weights. Then, for given various values weights, multiple projection neural networks are employded to search for Pareto optimal solutions. Based on employing Lyapunov theory, the proposed neural network approach is established to be stable in the sense of Lyapunov and it is globally convergent to an exact optimal solution of the single-objective problem. The simulation results also show that the presented model is feasible and efficient.

The shift of agricultural labor force to non-agricultural sectors has paralleled China\'s economic development, leading to a substantial rise in labor costs relative to capital. Consequently, the agricultural production has witnessed a shift towards capital-intensive practices. The capital deepening coincides with the significant increase in China\'s grain output while the main cause of capital deepening in China\'s grain production is poorly understood. This study examines the effect of increasing in various capital investments on the grain yield growth and growth convergence in China\'s main production areas, based on the data collected from the data set of the Compilation of Cost-Benefit Data of Agricultural Products (CCBDAP). Results show that the increases of chemical fertilizer, pesticide and machinery input have played key roles in the increase of grain yield. For early indica rice, japonica rice, wheat and maize, the average land output bears a β convergence. These findings suggest that more capital investments are supposed to accelerate the growth of grain yield per unit of land, take the opportunity of practicing the cross-provincial balance system of occupation and compensation of cultivated land. Moreover, strategic adjustments to the spatial distribution of grain cultivation are recommended to maximize the utilization of limited arable land resources while upholding national food security objectives.

Spider webs that serve as snares are one of the most fascinating and abundant type of animal architectures. In many cases they include an adhesive coating of silk lines-so-called viscid silk-for prey capture. The evolutionary switch from silk secretions forming solid fibres to soft aqueous adhesives remains an open question in the understanding of spider silk evolution. Here we functionally and chemically characterized the secretions of two types of silk glands and their behavioural use in the cellar spider, Pholcus phalangioides. Both being derived from the same ancestral gland type that produces fibres with a solidifying glue coat, the two types produce respectively a quickly solidifying glue applied in thread anchorages and prey wraps, or a permanently tacky glue deployed in snares. We found that the latter is characterized by a high concentration of organic salts and reduced spidroin content, showing up a possible pathway for the evolution of viscid properties by hygroscopic-salt-mediated hydration of solidifying adhesives. Understanding the underlying molecular basis for such radical switches in material properties not only helps to better understand the evolutionary origins and versatility of ecologically impactful spider web architectures, but also informs the bioengineering of spider silk-based products with tailored properties.

Eurypterids-Palaeozoic marine and freshwater arthropods commonly known as sea scorpions-repeatedly evolved to remarkable sizes (over 0.5 m in length) and colonized continental aquatic habitats multiple times. We compiled data on the majority of eurypterid species and explored several previously proposed explanations for the evolution of giant size in the group, including the potential role of habitat, sea surface temperature and dissolved sea surface oxygen levels, using a phylogenetic comparative approach with a new tip-dated tree. There is no compelling evidence that the evolution of giant size was driven by temperature or oxygen levels, nor that it was coupled with the invasion of continental aquatic environments, latitude or local faunal diversity. Eurypterid body size evolution is best characterized by rapid bursts of change that occurred independently of habitat or environmental conditions. Intrinsic factors played a major role in determining the convergent origin of gigantism in eurypterids.