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Summary: The recombinase RAD51 plays a core role in DNA repair by homologous recombination (HR). The assembly and disassembly of RAD51 filament need to be orderly regulated by mediators such as BRCA2 and anti-recombinases. To screen for potential regulators of RAD51, we perform RAD51 proximity proteomics and identify factor C1orf112. We further find that C1orf112 complexed with FIGNL1 facilitates RAD51 filament disassembly in the HR step of Fanconi anemia (FA) pathway. Specifically, C1orf112 physically interacts with FIGNL1 and enhances its protein stability. Meanwhile, the RAD51 filament disassembly activity of FIGNL1 is directly stimulated by C1orf112. BRCA2 directly interacts with C1orf112-FIGNL1 complex and functions upstream of this complex to protect RAD51 filament from premature disassembly. C1orf112- and FIGNL1-deficient cells are primarily sensitive to DNA interstrand cross-link (ICL) agents. Thus, these findings suggest an important function of C1orf112 in RAD51 regulation in the HR step of ICL repair by FA pathway.

Using deep learning and machine learning techniques for network intrusion detection is of great significance for enhancing the defense capability of network security systems. Given the characteristics of generative adversarial networks, such as the approximate consistency of generated samples with the input data distribution but with a random distribution within a certain bounded interval, and in response to the problem of insufficient classification performance and detection omission caused by the imbalance of different degrees of data categories and quantities in network intrusion traffic, and in light of the fact that the effectiveness of existing classification algorithms based on unbalanced traffic data still has some room for improvement, this paper proposes a network intrusion detection strategy based on auxiliary classifier generative adversarial networks. The data expansion experiments are conducted with the intrusion detection dataset NSL-KDD. The data are classified into twenty-three categories before and after the expansion by binary classification validation. The results show that the expansion of the generated samples for unbalanced network traffic data improve the subsequent recognition effect significantly. Finally, five classification performance index verification experiments are conducted. The results prove that the strategy of this paper performs better in accuracy, precision, recall rate and F-value indexes, and is capable of obtaining a large number of features from limited samples and inferring complete data distribution based on fewer features. The model as a whole has stronger generalization ability and defense effect.

The underlying causes of biodiversity disparities among geographic regions have long been a fundamental theme in ecology and evolution. However, the patterns of phylogenetic diversity (PD) and phylogenetic beta diversity (PBD) of congeners that are disjunctly distributed between eastern Asia–eastern North America (EA−ENA disjuncts) and their associated factors remain unknown. Here we investigated the standardized effect size of PD (SES-PD), PBD, and potentially associated factors in 11 natural mixed forest sites (five in EA and six in ENA) where abundant EA−ENA disjuncts occur. We found that the disjuncts in ENA possessed higher SES-PD than those in EA at the continental scale (1.96 vs −1.12), even though the number of disjunct species in ENA is much lower than in EA (128 vs 263). SES-PD of the EA−ENA disjuncts tended to decrease with increasing latitude in 11 sites. The latitudinal diversity gradient of SES-PD was stronger in EA sites than in ENA sites. Based on the unweighted unique fraction metric (UniFrac) distance and the phylogenetic community dissimilarity, PBD showed that the two northern sites in EA were more similar to the six-site ENA group than to the remaining southern EA sites. Based on the standardized effect size of mean pairwise distances (SES-MPD), nine of eleven studied sites showed a neutral community structure (−1.96 ≤ SES-MPD ≤ 1.96). Both Pearson's r and structural equation modeling suggested that SES-PD of the EA–ENA disjuncts was mostly associated with mean divergence time. Moreover, SES-PD of the EA–ENA disjuncts was positively correlated with temperature-related climatic factors, although negatively correlated with mean diversification rate and community structure. By applying approaches from phylogenetics and community ecology, our work sheds light on historical patterns of the EA−ENA disjunction and paves the way for further research.

Marine debris significantly influences the environment and economics of marine ecosystems. Measures to ban illegally discarded materials using monitoring techniques are expected to mitigate marine debris mismanagement. For example, derelict oyster farming rafts along the southwestern coast of Taiwan have been a source of marine debris pollution since the 1980s. An efficient inspection system is an urgent requirement for monitoring oyster farming areas and, is expected to implement control and surveillance measures for litter discarded from coastal fisheries. To address this issue, this study examined combinations of radio frequency identification (RFID), drone archiving, and onshore receiving systems to ascertain the positions of oyster rafts and their owners with digitally tagged labels. The results showed that the two proposed monitoring systems are feasible for use in marine environments. The RFID signals archived by the drone reached 100% of the 200 tags with a spatial bias ranging from 2.38 to 59.99 m. RFID-GPS hybrid tag signals received by the onshore station covered 100% of the 20 tags with spatial bias ranging from 1.27 to 10.47 m. The RFID-GPS hybrid system was confirmed as a feasible approach for monitoring oyster rafts within 3 km of the coast. The real-time (1 h intervals) position and attributes of each raft detected by the system indicated that our designed techniques enhance responsible fishery surveillance and management of coastal aquaculture worldwide.

Material exchange between oceans and currents is crucial for biogeochemical processes in marginal seas, such as the Kuroshio intrusion in the Luzon Strait, which contributes to nutrient and phytoplankton growth in the adjacent water. Therefore, it is necessary to understand changes in major current systems and their possible effects on marine ecology. In this study, we applied an edge-detection method to satellite-derived sea-surface temperature (SST) images to identify the SST front as the index of Kuroshio intrusion during 1985–2017. Chlorophyll-a (Chl-a) concentrations and geostrophic currents (determined from satellite observations after 1993) were examined by comparing long-term variations related to the Kuroshio front using empirical-mode decomposition analysis. The Kuroshio intrusion into the Luzon Strait gradually decreased after the 1990s, as did the Chl-a concentrations and current speed in the Strait. In contrast, the speed of the Kuroshio Current in the eastern Philippine tended to increase, indicating that the northward Kuroshio Current from the eastern Philippines became stronger, curtailing the westward intrusion of the branch current into the Luzon Strait. The speed of the Kuroshio Current correlated with the bifurcation of the North Equatorial Current (NEC), which is upstream of the Kuroshio Current starting from the southeast Philippines. Therefore, the NEC bifurcation latitude may have shifted more southward, which strengthened the water mass and current speed of the Kuroshio, resulting in decreased westward motion of the Kuroshio through the Luzon Strait. Consequently, the weakening Kuroshio intrusion may have caused a decreasing trend of biogeochemical processes in the South China Sea.

Abstract The association between gut microbiome and chronic metabolic disease including polycystic ovary syndrome (PCOS), is well documented, however, the relationship between the gut microbiota and serum metabolites remains unknown. In this study, untargeted metabolomics together with a 16S rRNA gene sequencing tool was used to detect small molecule serum metabolites and the gut microbiome. We identified 15 differential metabolites between PCOS patients and the healthy control. Lysophosphatidylcholine (LPC) (18:2, 20:3, 18:1, P-16:0, 17:0, 15:0, 18:3, 20:4), phosphatidylcholine(PC), ganglioside GA2 (d18:1/16:0) and 1-linoleoylglycerophosphocholine were increased in the PCOS group, and the concentrations of phosphoniodidous acid, bilirubin, nicotinate beta-d-ribonucleotide and citric acid were decreased in the PCOS group, suggesting a lipid metabolism and energy metabolism disorder in the PCOS patients. The diversity of gut microbiota in PCOS group was lower than that in healthy controls. Escherichia/Shigella, Alistipes and an unnamed strain 0319_6G20 belonging to Proteobacteria were important distinguishing genera (LDA > 3.5) in PCOS. Prevotella_9 was positively correlated with phosphoniodidous acid, nicotinate beta-d-ribonucleotide and citric acid concentrations, and negatively correlated with the concentration of LPC (20:3) and 1-linoleoylglycerophosphocholine; Roseburia was negatively correlated with LPC concentration (20:4), while the characteristic genus 0319_6G20 of PCOS was positively correlated with LPC concentration (20:3) (COR > 0.45). SF-36 in the PCOS group was significantly lower than that in the healthy control (HC) group, which was associated with the presence of Escherichia-Shigella and Alistipes. Our finding demonstrated the correlation between the gut microbiota and serum metabolites in PCOS, and therefore characteristic gut microbiota and metabolites may play an important role in the insulin resistance and the mood changes of PCOS patients.

Abstract Background The correct establishment of the barcode classification system for fish can facilitate biotaxonomists to distinguish fish species, and it can help the government to verify the authenticity of the ingredients of fish products or identify unknown fish related samples. The Cytochrome c oxidation I (COI) gene sequence in the mitochondria of each species possesses unique characteristics, which has been widely used as barcodes in identifying species in recent years. Instead of using COI gene sequences for primer design, flanking tRNA segments of COI genes from 2618 complete fish mitochondrial genomes were analyzed to discover suitable primers for fish classification at taxonomic family level. The minimal number of primer sets is designed to effectively distinguish various clustered groups of fish species for identification applications. Sequence alignment analysis and cross tRNA segment comparisons were applied to check and ensure the primers for each cluster group are exclusive. Results Two approaches were applied to improve primer design and re-cluster fish species. The results have shown that exclusive primers for 2618 fish species were successfully discovered through in silico analysis. In addition, we applied sequence alignment analysis to confirm that each pair of primers can successfully identify all collected fish species at the taxonomic family levels. Conclusions This study provided a practical strategy to discover unique primers for each fishery species and a comprehensive list of exclusive primers for extracting COI barcode sequences of all known fishery species. Various applications of verification of fish products or identification of unknown fish species could be effectively achieved.

A modularized output formation tracking control for mixed-order multi-agent systems is investigated. The multi-agent systems are composed of first-order and second-order integrators. The stability and formation tracking performance are analysed theoretically by the mathematical induction method. Finally, the effectiveness of the proposed modularized output control protocol is verified by simulation examples.

Emamectin benzoate (EMB) is one of the high-efficacious pesticide commonly used to control the ferocious economic crop pest S. exigua in the field. The results of S. exigua life table treated with three lethal doses of EMB (LC5, LC20 and LC50) indicated that three lethal doses of EMB could all inhibited the proliferation of S. exigua population effectively by long-lasting inhibit the survival of the S. exigua larvae and per female fecundity significantly (p

Abstract Background Maxillofacial fractures can lead to massive oronasal bleeding; however, surgical hemostasis and packing procedures can be challenging owing to complex facial anatomy. Only a few studies investigated maxillofacial fractures with massive oronasal hemorrhage. However, thus far, no studies have reported a protocolized management approach for maxillofacial trauma from a single center. This study aimed to evaluate the effectiveness of protocolized management for maxillofacial fractures with oronasal bleeding. Methods Patients were identified from the National Cheng University Hospital trauma registry from 2010 to 2020. We included patients with a face Abbreviated Injury Scale (AIS) score of > 3 and active oronasal bleeding. Patients’ characteristics were compared between the angiography and non-angiography groups and between survivors and nonsurvivors. Results Forty-nine patients were included. Among them, 34 (69%) underwent angiography, of whom 21 received arterial embolization. Forty-seven patients (96%) successfully achieved hemostasis by adhering to the treatment protocol at our institution. Compared with the non-angiography group, the angiography group had significantly more patients requiring oral intubation (97% vs. 53%, P 3 (65% vs. 13%, P = 0.001), higher Injury Severity Score (ISS; 43 [33–50] vs. 22 [18–27], P 3 (92% vs. 33%; P

Abstract Delayed bleeding is a major issue in patients with high-grade splenic injuries who receive non-operative management (NOM). While only few studies addressed the clinical manifestations of delayed bleeding in these patients. We reviewed the patients with high-grade splenic injuries presented with delayed bleeding, defined as the need for salvage procedures following NOM. There were 138 patients received NOM in study period. Fourteen of 107 patients in the SAE group and 3 of 31 patients in the non-embolization group had delayed bleeding. Among the 17 delayed bleeding episodes, 6 and 11 patients were salvaged by splenectomy and SAE, respectively. Ten (58.9%, 10/17) patients experienced bleeding episodes in the intensive care unit (ICU), whereas seven (41.1%, 7/17) experienced those in the ward or at home. The clinical manifestations of delayed bleeding were a decline in haemoglobin levels (47.1%, 8/17), hypotension (35.3%, 6/17), tachycardia (47.1%, 8/17), new abdominal pain (29.4%, 5/17), and worsening abdominal pain (17.6%, 3/17). For the bleeding episodes detected in the ICU, a decline in haemoglobin (60%, 6/10) was the main manifestation. New abdominal pain (71.43%, 5/7) was the main presentation when the patients left the ICU. In conclusion, abdominal pain was the main early clinical presentation of delayed bleeding following discharge from the ICU or hospital.

Profile soil moisture (PSM), the soil water content in the whole soil layer, directly controls the major processes related to biological interaction, vegetation growth, and runoff generation. Its spatial heterogeneity, which refers to the uneven distribution and complexity in space, influences refined spatial management and decision-making in ecological, agricultural, and hydrological systems. Satellite instruments and hydrological models are two important sources of spatial information on PSM, but there is still a gap in understanding their potential mechanisms that affect spatial heterogeneity. This study is designed to identify the spatial heterogeneity and the driving factors of two PSM datasets; one is preprocessed from a satellite product (European Space Agency Climate Change Initiative, ESA CCI), and the other is simulated from a distributed hydrological model (the DEM-based distributed rainfall-runoff model, DDRM). Three catchments with different climate conditions were chosen as the study area. By considering the scale dependence of spatial heterogeneity, the profile saturation degree (PSD) datasets from different sources (shown as ESA CCI PSD and DDRM PSD, respectively) during 2017 that are matched in terms of spatial scale and physical properties were acquired first based on the calibration data from 2014–2016, and then the spatial heterogeneity of the PSD from different sources was identified by using spatial statistical analysis and the semi-variogram method, followed by the geographic detector method, to investigate the driving factors. The results indicate that (1) ESA CCI and DDRM PSD are similar for seasonal changes and are overall consistent and locally different in terms of the spatial variations in catchment with different climate conditions; (2) based on spatial statistical analysis, the spatial heterogeneity of PSD reduces after spatial rescaling; at the same spatial scale, DDRM PSD shows higher spatial heterogeneity than ESA CCI PSD, and the low-flow period shows higher spatial heterogeneity than the high-flow period; (3) based on the semi-variogram method, both ESA CCI and DDRM PSD show strong spatial heterogeneity in most cases, in which the proportion of C/(C0 + C) is higher than 0.75, and the spatial data in the low-flow period mostly show larger spatial heterogeneity, in which the proportion is higher than 0.9; the spatial heterogeneity of PSD is higher in the semi-arid catchment; (4) the first three driving factors of the spatial heterogeneity of both ESA CCI and DDRM PSD are DEM, precipitation, and soil type in most cases, contributing more than 50% to spatial heterogeneity; (5) precipitation contributes most to ESA CCI PSD in the low-flow period, and there is no obvious high contribution of precipitation to DDRM PSD. The research provides insights into the spatial heterogeneity of PSM, which helps develop refined modeling and spatial management strategies for soil moisture in ecological, agricultural, and hydrological fields.