Penghou, a new genus of flea beetles from China (Coleoptera: Chrysomelidae: Galerucinae: Alticini)

A new genus (Penghou) with a single new species (P. yulongshan) from Yunnan Province in China is described and illus- trated. It is compared to Hespera Weise, Hesperomorpha Ogloblin, Laotzeus Chen, Luperomorpha Weise, Mandarella Duvivier, Omeiana Chen, Stenoluperus Ogloblin and Taiwanohespera Kimoto

Penghou, a new genus of flea beetles from China (Coleoptera: Chrysomelidae: Galerucinae: Alticini)

A new genus (Penghou) with a single new species (P. yulongshan) from Yunnan Province in China is described and illus- trated. It is compared to Hespera Weise, Hesperomorpha Ogloblin, Laotzeus Chen, Luperomorpha Weise, Mandarella Duvivier, Omeiana Chen, Stenoluperus Ogloblin and Taiwanohespera Kimoto

Redundancy-Free Self-Supervised Relational Learning for Graph Clustering

Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable attention accompanied by graph neural networks in recent years. However, most existing methods overlook the inherent relational information among the non-independent and non-identically distributed nodes in a graph. Due to the lack of exploration of relational attributes, the semantic information of the graph-structured data fails to be fully exploited which leads to poor clustering performance. In this paper, we propose a novel self-supervised deep graph clustering method named Relational Redundancy-Free Graph Clustering (R$^2$FGC) to tackle the problem. It extracts the attribute- and structure-level relational information from both global and local views based on an autoencoder and a graph autoencoder. To obtain effective representations of the semantic information, we preserve the consistent relation among augmented nodes, whereas the redundant relation is further reduced for learning discriminative embeddings. In addition, a simple yet valid strategy is utilized to alleviate the over-smoothing issue. Extensive experiments are performed on widely used benchmark datasets to validate the superiority of our R$^2$FGC over state-of-the-art baselines. Our codes are available at https://github.com/yisiyu95/R2FGC.Comment: Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2024

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Recent advancements in Large Language Models (LLMs) have revolutionized decision-making by breaking down complex problems into more manageable language sequences referred to as ``thoughts''. An effective thought design should consider three key perspectives: performance, efficiency, and flexibility. However, existing thought can at most exhibit two of these attributes. To address these limitations, we introduce a novel thought prompting approach called ``Everything of Thoughts'' (XoT) to defy the law of ``Penrose triangle of existing thought paradigms. XoT leverages pretrained reinforcement learning and Monte Carlo Tree Search (MCTS) to incorporate external domain knowledge into thoughts, thereby enhancing LLMs' capabilities and enabling them to generalize to unseen problems efficiently. Through the utilization of the MCTS-LLM collaborative thought revision framework, this approach autonomously produces high-quality comprehensive cognitive mappings with minimal LLM interactions. Additionally, XoT empowers LLMs to engage in unconstrained thinking, allowing for flexible cognitive mappings for problems with multiple solutions. We evaluate XoT on several challenging multi-solution problem-solving tasks, including Game of 24, 8-Puzzle, and Pocket Cube. Our results demonstrate that XoT significantly outperforms existing approaches. Notably, XoT can yield multiple solutions with just one LLM call, showcasing its remarkable proficiency in addressing complex problems across diverse domains.Comment: 17 pages, 5 figure

A tough and mechanically stable adhesive hydrogel for non-invasive wound repair

Wound healing has been a great challenge throughout human history. Improper treatment for wounds is so easy to lead to infection and a series of serious symptoms, even death. Because of the ability of absorbing fluid and keeping a moist environment, the hydrogel with 3D networks is ideal candidate for wound dressing. More important, it has good biocompatibility. However, most of the hydrogel dressings reported have weak mechanical properties and adhesion properties, which greatly limit their clinical application. Herein, a tough adhesive hydrogel with good mechanical stability for non-invasive wound repair is reported. The hydrogel is composed of polyethylene glycol dimethacrylate (PEGDA), chitosan (CS) and chitin nano-whisker (CW). PEGDA and CS form interpenetrating network hydrogel through free radical polymerization reaction under the UV light. The introduction of CW further enhances the toughness of the hydrogel. The pH-sensitive CS can form adhesion to various materials through topological adhesion. As a wound closure repair material, PEGDA/CS/CW hydrogel not only has the characteristic of effectively closing the wound, defending against invading bacteria, and keeping the wound clean, but also has good tensile and mechanical stability, which is expected to realize the closure and repair of joints and other moving parts of the wound. This adhesive hydrogel is proven a promising material for wound closure repair

Towards a global One Health index: a potential assessment tool for One Health performance

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8–65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI—subject to rigorous validation—would represent the world’s first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-022-00979-9

Radiofrequency Catheter Ablation of Supraventricular Tachycardia in Patients With Pulmonary Hypertension: Feasibility and Long-Term Outcome

BackgroundSupraventricular tachycardia (SVT) occurs commonly and is strongly correlated with clinical deterioration in patients with pulmonary hypertension (PH). This study aimed to investigate the feasibility and long-term outcome of radiofrequency catheter ablation (RFCA) in PH patients with SVT.Materials and MethodsConsecutive PH patients with SVT who were scheduled to undergo electrophysiological study and RFCA between September 2010 and July 2019 were included. The acute results and long-term success of RFCA were assessed after the procedure.ResultsIn total, 71 PH patients with 76 episodes of SVT were analyzed. Cavotricuspid isthmus-dependent atrial flutter (n = 33, 43.5%) was the most common SVT type, followed by atrioventricular nodal reentrant tachycardia (n = 16, 21.1%). Of the 71 patients, 60 (84.5%) underwent successful electrophysiological study and were subsequently treated by RFCA. Among them, acute sinus rhythm was restored in 54 (90.0%) patients, and procedure-related complications were observed in 4 (6.7%) patients. Univariate logistic regression analysis showed that cavotricuspid isthmus-independent atrial flutter [odds ratio (OR) 25.00, 95% confidence interval (CI) 3.45–180.98, p = 0.001] and wider pulmonary artery diameter (OR 1.19, 95% CI 1.03–1.38; p = 0.016) were associated with RFCA failure. During a median follow-up of 36 (range, 3–108) months, 7 patients with atrial flutter experienced recurrence, yielding a 78.3% 3-year success rate for RFCA treatment.ConclusionThe findings suggest that RFCA of SVT in PH patients is feasible and has a good long-term success rate. Cavotricuspid isthmus-independent atrial flutter and a wider PAD could increase the risk for ablation failure

Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing

BACKGROUND: Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing accessions, which represent wild, domesticated landrace, and Chinese elite soybean populations were analyzed. RESULTS: A total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions were identified. Among the SNPs detected, 25.5% were not described previously. We found that artificial selection during domestication led to more pronounced reduction in the genetic diversity of soybean than the switch from landraces to elite cultivars. Only a small proportion (2.99%) of the whole genomic regions appear to be affected by artificial selection for preferred agricultural traits. The selection regions were not distributed randomly or uniformly throughout the genome. Instead, clusters of selection hotspots in certain genomic regions were observed. Moreover, a set of candidate genes (4.38% of the total annotated genes) significantly affected by selection underlying soybean domestication and genetic improvement were identified. CONCLUSIONS: Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes/loci underlying agronomically important traits

Modeling Rett Syndrome Using TALEN-Edited MECP2 Mutant Cynomolgus Monkeys

Gene-editing technologies have made it feasible to create nonhuman primate models for human genetic disorders. Here, we report detailed genotypes and phenotypes of TALEN-edited MECP2 mutant cynomolgus monkeys serving as a model for a neurodevelopmental disorder, Rett syndrome (RTT), which is caused by loss-of-function mutations in the human MECP2 gene. Male mutant monkeys were embryonic lethal, reiterating that RTT is a disease of females. Through a battery of behavioral analyses, including primate-unique eye-tracking tests, in combination with brain imaging via MRI, we found a series of physiological, behavioral, and structural abnormalities resembling clinical manifestations of RTT. Moreover, blood transcriptome profiling revealed that mutant monkeys resembled RTT patients in immune gene dysregulation. Taken together, the stark similarity in phenotype and/or endophenotype between monkeys and patients suggested that gene-edited RTT founder monkeys would be of value for disease mechanistic studies as well as development of potential therapeutic interventions for RTT