Toroidic phase transitions in a direct-kagome artificial spin ice.

Ferrotoroidicity-the fourth form of primary ferroic order-breaks both space and time-inversion symmetry. So far, direct observation of ferrotoroidicity in natural materials remains elusive, which impedes the exploration of ferrotoroidic phase transitions. Here we overcome the limitations of natural materials using an artificial nanomagnet system that can be characterized at the constituent level and at different effective temperatures. We design a nanomagnet array as to realize a direct-kagome spin ice. This artificial spin ice exhibits robust toroidal moments and a quasi-degenerate ground state with two distinct low-temperature toroidal phases: ferrotoroidicity and paratoroidicity. Using magnetic force microscopy and Monte Carlo simulation, we demonstrate a phase transition between ferrotoroidicity and paratoroidicity, along with a cross-over to a non-toroidal paramagnetic phase. Our quasi-degenerate artificial spin ice in a direct-kagome structure provides a model system for the investigation of magnetic states and phase transitions that are inaccessible in natural materials.

Unlocking the predictive potential of long non-coding RNAs: a machine learning approach for precise cancer patient prognosis.

The intricate web of cancer biology is governed by the active participation of long non-coding RNAs (lncRNAs), playing crucial roles in cancer cells' proliferation, migration, and drug resistance. Pioneering research driven by machine learning algorithms has unveiled the profound ability of specific combinations of lncRNAs to predict the prognosis of cancer patients. These findings highlight the transformative potential of lncRNAs as powerful therapeutic targets and prognostic markers. In this comprehensive review, we meticulously examined the landscape of lncRNAs in predicting the prognosis of the top five cancers and other malignancies, aiming to provide a compelling reference for future research endeavours. Leveraging the power of machine learning techniques, we explored the predictive capabilities of diverse lncRNA combinations, revealing their unprecedented potential to accurately determine patient outcomes.

lncRNAs play crucial roles in cancer biology, regulating proliferation, migration, and drug resistance.Emerging evidence suggests that machine learning can predict cancer prognosis using specific lncRNA combinations.Comprehensive information on the predictive abilities of lncRNA combinations in oncology concerning machine learning is lacking.This review offers up-to-date vital references on diverse lncRNA combinations pertinent to future research and clinical trials.

Soil Fungal Community Characteristics at Timberlines of Sejila Mountain in Southeast Tibet, China.

Soil fungal community characteristics of alpine timberlines are unclear. In this study, soil fungal communities in five vegetation zones across timberlines on the south and north slopes of Sejila Mountain in Tibet, China were investigated. The results show that the alpha diversity of soil fungi was not different between the north- and south-facing timberlines or among the five vegetation zones. Archaeorhizomyces (Ascomycota) was a dominant genus at the south-facing timberline, whereas the ectomycorrhizal genus Russula (Basidiomycota) decreased with decreasing Abies georgei coverage and density at the north-facing timberline. Saprotrophic soil fungi were dominant, but their relative abundance changed little among the vegetation zones at the south timberline, whereas ectomycorrhizal fungi decreased with tree hosts at the north timberline. Soil fungal community characteristics were related to coverage and density, soil pH and ammonium nitrogen at the north timberline, whereas they had no associations with the vegetation and soil factors at the south timberline. In conclusion, timberline and A. georgei presence exerted apparent influences on the soil fungal community structure and function in this study. The findings may enhance our understanding of the distribution of soil fungal communities at the timberlines of Sejila Mountain.

Visualization and Object Detection Based on Event Information.

A dynamic vision sensor is an optical sensor that focuses on dynamic changes and outputs event information containing only position, time, and polarity. It has the advantages of high temporal resolution, high dynamic range, low data volume, and low power consumption. However, a single event can only indicate that the increase or decrease in light exceeds the threshold at a certain pixel position and a certain moment. In order to further study the ability and characteristics of event information to represent targets, this paper proposes an event information visualization method with adaptive temporal resolution. Compared with methods with constant time intervals and a constant number of events, it can better convert event information into pseudo-frame images. Additionally, in order to explore whether the pseudo-frame image can efficiently complete the task of target detection according to its characteristics, this paper designs a target detection network named YOLOE. Compared with other algorithms, it has a more balanced detection effect. By constructing a dataset and conducting experimental verification, the detection accuracy of the image obtained by the event information visualization method with adaptive temporal resolution was 5.11% and 4.74% higher than that obtained using methods with a constant time interval and number of events, respectively. The average detection accuracy of pseudo-frame images in the YOLOE network designed in this paper is 85.11%, and the number of detection frames per second is 109. Therefore, the effectiveness of the proposed visualization method and the good performance of the designed detection network are verified.

Blind Remote Sensing Image Deblurring Based on Overlapped Patches' Non-Linear Prior.

The remote sensing imaging environment is complex, in which many factors cause image blur. Thus, without prior knowledge, the restoration model established to obtain clear images can only rely on the observed blurry images. We still build the prior with extreme pixels but no longer traverse all pixels, such as the extreme channels. The features are extracted in units of patches, which are segmented from an image and partially overlap with each other. In this paper, we design a new prior, i.e., overlapped patches' non-linear (OPNL) prior, derived from the ratio of extreme pixels affected by blurring in patches. The analysis of more than 5000 remote sensing images confirms that OPNL prior prefers clear images rather than blurry images in the restoration process. The complexity of the optimization problem is increased due to the introduction of OPNL prior, which makes it impossible to solve it directly. A related solving algorithm is established based on the projected alternating minimization (PAM) algorithm combined with the half-quadratic splitting method, the fast iterative shrinkage-thresholding algorithm (FISTA), fast Fourier transform (FFT), etc. Numerous experiments prove that this algorithm has excellent stability and effectiveness and has obtained competitive processing results in restoring remote sensing images.

Evaluation of the anticarcinogenic potential of the endophyte, Streptomyces sp. LRE541 isolated from Lilium davidii var. unicolor (Hoog) Cotton.

BACKGROUND: Endophytic actinomycetes, as emerging sources of bioactive metabolites, have been paid great attention over the years. Recent reports demonstrated that endophytic streptomycetes could yield compounds with potent anticancer properties that may be developed as chemotherapeutic drugs. RESULTS: Here, a total of 15 actinomycete-like isolates were obtained from the root tissues of Lilium davidii var. unicolor (Hoog) Cotton based on their morphological appearance, mycelia coloration and diffusible pigments. The preliminary screening of antagonistic capabilities of the 15 isolates showed that isolate LRE541 displayed antimicrobial activities against all of the seven tested pathogenic microorganisms. Further in vitro cytotoxicity test of the LRE541 extract revealed that this isolate possesses potent anticancer activities with IC50 values of 0.021, 0.2904, 1.484, 4.861, 6.986, 8.106, 10.87, 12.98, and 16.94 µg/mL against cancer cell lines RKO, 7901, HepG2, CAL-27, MCF-7, K562, Hela, SW1990, and A549, respectively. LRE541 was characterized and identified as belonging to the genus Streptomyces based on the 16S rRNA gene sequence analysis. It produced extensively branched red substrate and vivid pink aerial hyphae that changed into amaranth, with elliptic spores sessile to the aerial mycelia. To further explore the mechanism underlying the decrease of cancer cell viability following the LRE541 extract treatment, cell apoptosis and cell cycle arrest assays were conducted in two cancer cell lines, RKO and 7901. The result demonstrated that LRE541 extract inhibited cell proliferation of RKO and 7901 by causing cell cycle arrest both at the S phase and inducing apoptosis in a dose-dependent manner. The chemical profile of LRE541 extract performed by the UHPLC-MS/MS analysis revealed the presence of thirty-nine antitumor compounds in the extract. Further chemical investigation of the LRE541 extract led to the discovery of one prenylated indole diketopiperazine (DKP) alkaloid, elucidated as neoechinulin A, a known antitumor agent firstly detected in Streptomyces; two anthraquinones 4-deoxy-ε-pyrromycinone (1) and epsilon-pyrromycinone (2) both displaying anticancer activities against RKO, SW1990, A549, and HepG2 with IC50 values of 14.96 ± 2.6 - 20.42 ± 4.24 µg/mL for (1); 12.9 ± 2.13, 19.3 ± 4.32, 16.8 ± 0.75, and 18.6 ± 3.03 µg/mL for (2), respectively. CONCLUSION: Our work evaluated the anticarcinogenic potential of the endophyte, Streptomyces sp. LRE541 and obtained one prenylated indole diketopiperazine alkaloid and two anthraquinones. Neoechinulin A, as a known antitumor agent, was identified for the first time in Streptomyces. Though previously found in Streptomyces, epsilon-pyrromycinone and 4-deoxy-ε-pyrromycinone were firstly shown to possess anticancer activities.

Malware detection based on semi-supervised learning with malware visualization.

The traditional signature-based detection method requires detailed manual analysis to extract the signatures of malicious samples, and requires a large number of manual markers to maintain the signature library, which brings a great time and resource costs, and makes it difficult to adapt to the rapid generation and mutation of malware. Methods based on traditional machine learning often require a lot of time and resources in sample labeling, which results in a sufficient inventory of unlabeled samples but not directly usable. In view of these issues, this paper proposes an effective malware classification framework based on malware visualization and semi-supervised learning. This framework includes mainly three parts: malware visualization, feature extraction, and classification algorithm. Firstly, binary files are processed directly through visual methods, without assembly, decompression, and decryption; Then the global and local features of the gray image are extracted, and the visual image features extracted are fused on the whole by a special feature fusion method to eliminate the exclusion between different feature variables. Finally, an improved collaborative learning algorithm is proposed to continuously train and optimize the classifier by introducing features of inexpensive unlabeled samples. The proposed framework was evaluated over two extensively researched benchmark datasets, i.e., Malimg and Microsoft. The results show that compared with traditional machine learning algorithms, the improved collaborative learning algorithm can not only reduce the cost of sample labeling but also can continuously improve the model performance through the input of unlabeled samples, thereby achieving higher classification accuracy.

The Short-Term Impact of Animation on the Executive Function of Children Aged 4 to 7.

Research has shown that animation plays an important role in the development of children's executive function (EF), and the development of EF components, inhibitory control, working memory, and cognitive flexibility, is asynchronous. Thus, this study explores the developmental trajectories and animation features (fantasy and pacing) that influence each EF component, by examining 218 children aged 4-7. Pretest information, mainly the childhood EF inventory, was provided by parents: child's age, age of first exposure to animation, animation viewing time on weekdays and weekends, family income, and parents' education. The children in each age group were randomly divided into four groups to watch animations comprised of different animation features. After watching, their EF were measured by a day-night task, backward digit-span task, and flexible item-selection task. The results showed that the children's inhibitory control, working memory and cognitive flexibility levels all improved with age. Highly fantastical animations weakened children's performance on each subsequent EF task. Pacing had no effect on any of the components of children's EF. An interactive effect on inhibitory control was only found with fantasy in younger children; specifically, high-fantastical animations had a more pronounced short-lived weakening effect on inhibitory control in younger children (4-6 years) compared with low-fantastical animations. Future research should explore the long-term impact of content rather than the form of animation on younger children's EF.

An Automatic Exposure Method of Plane Array Remote Sensing Image Based on Two-Dimensional Entropy.

The improper setting of exposure time for the space camera will cause serious image quality degradation (overexposure or underexposure) in the imaging process. In order to solve the problem of insufficient utilization of the camera's dynamic range to obtain high-quality original images, an automatic exposure method for plane array remote sensing images based on two-dimensional entropy is proposed. First, a two-dimensional entropy-based image exposure quality evaluation model is proposed. The two-dimensional entropy matrix of the image is partitioned to distinguish the saturated areas (region of overexposure and underexposure) and the unsaturated areas (region of propitious exposure) from the original image. The ratio of the saturated area is used as an evaluating indicator of image exposure quality, which is more sensitive to the brightness, edges, information volume, and signal-to-noise ratio of the image. Then, the cubic spline interpolation method is applied to fit the exposure quality curve to efficiently improve the camera's exposure accuracy. A series of experiments have been carried out for different targets in different environments using the existing imaging system to verify the superiority and robustness of the proposed method. Compared with the conventional automatic exposure method, the signal-to-noise ratio of the image obtained by the proposed algorithm is increased by at least 1.6730 dB, and the number of saturated pixels is reduced to at least 2.568%. The method is significant to improve the on-orbit autonomous operating capability and on-orbit application efficiency of space camera.

Analysis on acupoint selection rules for impotence treated with acupuncture and moxibustion in ancient based on data mining technology / 中国针灸

Based on the data mining technology, the rules of acupoint selection and prescription were analyzed for impotence treated with acupuncture and moxibustion in ancient recorded in

Nitrate reductase-dependent nitric oxide plays a key role on MeJA-induced ganoderic acid biosynthesis in Ganoderma lucidum.

Ganoderma lucidum, which contains numerous biologically active compounds, is known worldwide as a medicinal basidiomycete. Because of its application for the prevention and treatment of various diseases, most of artificially cultivated G. lucidum is output to many countries as food, tea, and dietary supplements for further processing. Methyl jasmonate (MeJA) has been reported as a compound that can induce ganoderic acid (GA) biosynthesis, an important secondary metabolite of G. lucidum. Herein, MeJA was found to increase the intracellular level of nitric oxide (NO). In addition, upregulation of GA biosynthesis in the presence of MeJA was abolished when NO was depleted from the culture. This result demonstrated that MeJA-regulated GA biosynthesis might occur via NO signaling. To elucidate the underlying mechanism, we used gene-silenced strains of nitrate reductase (NR) and the inhibitor of NR to illustrate the role of NO in MeJA induction. The results indicated that the increase in GA biosynthesis induced by MeJA was activated by NR-generated NO. Furthermore, the findings indicated that the reduction of NO could induce GA levels in the control group, but NO could also activate GA biosynthesis upon MeJA treatment. Further results indicated that NR silencing reversed the increased enzymatic activity of NOX to generate ROS due to MeJA induction. Importantly, our results highlight the NR-generated NO functions in signaling crosstalk between reactive oxygen species and MeJA. These results provide a good opportunity to determine the potential pathway linking NO to the ROS signaling pathway in fungi treated with MeJA. KEY POINTS: • MeJA increased the intracellular level of nitric oxide (NO) in G. lucidum. • The increase in GA biosynthesis induced by MeJA is activated by NR-generated NO. • NO acts as a signaling molecule between reactive oxygen species (ROS) and MeJA.

Relationship between volatile compounds of Picea likiangensis var. linzhiensis cone and host selection of Dioryctria abietella.

This study aimed to determine the relationship between volatile compounds of Picea likiangensis var. linzhiensis cone and host selection of Dioryctria abietella. During the infestation of P. likiangensis var. linzhiensis by D. abietella, their cones and branches emitted volatile compounds, which were extracted using CH2 Cl2 extraction and XAD2 adsorption methods, and were analyzed using gas chromatography-mass spectrometry. Before and after overwintering, D. abietella larva preferred annually infested cones and their extracts, and adult D. abietella preferred to lay eggs on annually infested cones and healthy cones of the year, and the oviposition rate of adult D. abietella was 72% on branches with healthy cones of the year, and no egg was laid on branches with annually healthy cones or branches without cones. The volatile compounds after infestation, α- and ß-pinene, were significantly higher in cones than those in other tissues; however, myrcene in cones was significantly lower than those in other tissues. The annually infested cones produced ß-caryophyllene and (1S)-(-)-ß-pinene, while the annually healthy cones and branches produced myrcene and 3-carene. The annually infested cones and their extracts attracted D. abietella larvae, while that of healthy cones and annually infested cones attracted the adults, indicating that the terpene compounds: α-pinene, ß-pinene, (1S)-(-)-ß-pinene, limonene, and ß-caryophyllene are attractive to D. abietella, and the terpene compounds-myrcene and 3-carene-from the branch tissues may be repulsive to D. abietella.

Seed bank characteristics in a Pinus densata forest and its relationship with vegetation diversity in Southeast Tibet, China.

OBJECTIVE: We aimed to understand the basic characteristics of the underground seed bank of Pinus densata forest and its relationship with aboveground vegetation, to provide a theoretical basis for vegetation restoration. METHODS: The study sites were Dongjiu Bridge (DJ), Linji Bridge (LZ), and Birishen Mountain Scenic Spot (RB) in Gongbu Nature Reserve, Southeast Tibet, China. Species composition and distribution pattern of the underground seed bank in P. densata forest were analyzed. Germination data and field investigations were used to examine the similarities between aboveground vegetation and underground seed banks, and their responses to the environment. RESULTS: There were 47 species belonging to 27 families in the underground seed bank of the P. densata forest. Asteraceae, Rosaceae, Labiatae, and Poaceae were dominant, accounting for 40.4% of the total number of families. Underground seed density was 2,114, 1,952, and 1,141 seeds/m2 in DJ, LZ, and BR, respectively. The percentage of different life-forms in each sampling location was shown to be perennial herbs > shrubs > annual herbs > trees > subshrubs. The Shannon-Wiener diversity index, Margalef richness index, and Simpson's dominance index of each sample showed that species decreased with higher elevation, while the Pielou evenness index showed the opposite trend. Elevation, slope position, slope aspect, and slope were positively correlated with the Pielou evenness index and negatively correlated with the Shannon-Wiener diversity index, Margalef richness index, and Simpson's dominance index. The Sørensen index, comparing the similarity between the underground seed bank and aboveground vegetation of DJ, LZ, and BR was 0.46, 0.35, and 0.31, respectively. CONCLUSION: The underground seed bank of P. densata forest has high seed density and high species richness, but there was little similarity between aboveground vegetation and underground seed bank. Elevation and slope position had a great influence on the uniformity of species distribution.

Label propagation algorithm based on Roll-back detection and credibility assessment.

The traditional label propagation algorithm (LPA) iteratively propagates labels from a small number of labeled samples to many unlabeled ones based on the sample similarities. However, due to the randomness of label propagations, and LPA's weak ability to deal with uncertain points, the label error may be continuously expanded during the propagation process. In this paper, the algorithm label propagation based on roll-back detection and credibility assessment (LPRC) is proposed. A credit evaluation of the unlabeled samples is carried out before the selection of samples in each round of label propagation, which makes sure that the samples with more certainty can be labeled first. Furthermore, a roll-back detection mechanism is introduced in the iterative process to improve the label propagation accuracy. At last, our method is compared with 9 algorithms based on UCI datasets, and the results demonstrated that our method can achieve better classification performance, especially when the number of labeled samples is small. When the labeled samples only account for 1% of the total sample number of each synthetic dataset, the classification accuracy of LPRC improved by at least 26.31% in dataset circles, and more than 13.99%, 15.22% than most of the algorithms compared in dataset moons and varied, respectively. When the labeled samples account for 2% of the total sample number of each dataset in UCI datasets, the accuracy (take the average value of 50 experiments) of LPRC improved in an average value of 23.20% in dataset wine, 20.82% in dataset iris, 4.25% in dataset australian, and 6.75% in dataset breast. And the accuracy increases with the number of labeled samples.

Comparative and Functional Analyses of Two Sequenced Paenibacillus polymyxa Genomes Provides Insights Into Their Potential Genes Related to Plant Growth-Promoting Features and Biocontrol Mechanisms.

Many bacteria belonging to Paenibacillus polymyxa are plant growth-promoting rhizobacteria (PGPR) with the potential to promote plant growth and suppress phytopathogens and have been used as biological control agents (BCAs). However, the growth promotion and biocontrol mechanisms of P. polymyxa have not been thoroughly elucidated thus far. In this investigation, the genome sequences of two P. polymyxa strains, ZF129 and ZF197, with broad anti-pathogen activities and potential for growth promotion were comparatively studied. Comparative and functional analyses of the two sequenced P. polymyxa genomes showed that the ZF129 genome consists of one 5,703,931 bp circular chromosome and two 79,020 bp and 37,602 bp plasmids, designated pAP1 and pAP2, respectively. The complete genome sequence of ZF197 consists of one 5,507,169 bp circular chromosome and one 32,065 bp plasmid, designated pAP197. Phylogenetic analysis revealed that ZF129 is highly similar to two P. polymyxa strains, HY96-2 and SQR-21, while ZF197 is highly similar to P. polymyxa strain J. The genes responsible for secondary metabolite synthesis, plant growth-promoting traits, and systemic resistance inducer production were compared between strains ZF129 and ZF197 as well as other P. polymyxa strains. The results indicated that the variation of the corresponding genes or gene clusters between strains ZF129 and ZF197 may lead to different antagonistic activities of their volatiles or cell-free supernatants against Fusarium oxysporum. This work indicates that plant growth promotion by P. polymyxa is largely mediated by phytohormone production, increased nutrient availability and biocontrol mechanisms. This study provides an in-depth understanding of the genome architecture of P. polymyxa, revealing great potential for the application of this bacterium in the fields of agriculture and horticulture as a PGPR.

Majorana corner modes in an s-wave second order topological superfluid.

In sharp contrast to conventional topological superfluids, higher order (order r > 1) topological superfluids in n dimensions do not host n - 1 dimensional Majorana boundary states, instead host n - r dimensional Majorana excitations. In this paper, we propose Majorana corner modes can emerge in a second order superfluid with s-wave pairing, instead of unconventional pairings such as d-wave and [Formula: see text]-wave pairings in most of previous proposals. There are three key ingredients in this scheme consisting of a topological insulator, an in-plane Zeeman field, and an s-wave pairing. Based on the low energy theory for edge states, where the effective Dirac mass sign changes at the corner, we unveil the emergence of Majorana corner modes. Our proposal provides a promising platform for implementing 2D second order topological superfluids and Majorana corner modes.

Application of special acupoints for chronic gastritis in ancient literature of acupuncture and moxibustion / 中国针灸

The application of special acupoints for different primary symptoms of chronic gastritis in ancient literature of acupuncture and moxibustion was analyzed and summarized. With keywords, electronic and manual retrieval of ancient literature being performed to establish a database, the association rules were performed with SPSS Modeler 18. As a result, ① among all the 2243 items included, 109 items mentioned special acupoints (excluding those only mentioned crossing acupoint). The frequency of special acupoints was 2554 (71.7%), and the special acupoints on the spleen meridian, the stomach meridian, the conception vessel were frequently used. The frequency of five- point was highest, followed by front- points. ② The special acupoints for four main primary symptoms of chronic gastritis, "stomachache" "vomiting and regurgitation" "belching and acid regurgitation" and "epigastric fullness", included Zusanli (ST 36), Neiguan (PC 6), Zhongwan (CV 12), Gongsun (SP 4), Taibai (SP 3). In addition, the back- points were also selected to treat the primary symptoms other than "epigastric fullness". Zhangmen (LR 13) was added to treat "belching and acid regurgitation". The combination of Neiguan (PC 6) and Gongsun (SP 4) showed the strongest correlation; due to different primary symptoms, the combination had different emphasis.

[The functions of yhcZ gene during Bacillus thuringiensis growth].

yhcZ and yhcY genes constitute a two-component system in Bacillus subtilis and B. cereus that regulates bacterial growth. However, the exact biological function of yhcZ gene in B. thuringiensis has not been fully elucidated. In this study, we proved that HD73_5824 is an yhcZ gene in B. thuringiensis subsp. kurstaki HD73 strain by combining gene functional annotation, analysis of upstream and downstream genes arrangement, and amino acid sequence alignment. This yhcZ gene may co-regulate bacterial growth with HD73_5825 gene (yhcY gene) by constituting a two-component system. Homologous recombination technology was employed to knock out yhcZ gene of HD73, resulting in a mutant strain HD (ΔyhcZ). The HD (ΔyhcZ) strain grew slower than wild-type strain HD73 in both LB and SSM medium. Re-introduction of yhcZ gene in HD (ΔyhcZ) strain can partially restore the growth, indicating that the deletion of yhcZ gene impacts the cell growth of HD73 strain. HD (ΔyhcZ) strain grew faster than HD73 strain in M9 medium with 0.4% glucose as the sole carbon source, implying that the yhcZ gene plays an important role in glucose utilization by HD73 strain. The results of biolog assay showed that HD (ΔyhcZ) exhibits a lower average well color development compared to HD73. HD(ΔyhcZ) cells also demonstrated a decreased capacity for absorbing and utilizing D/L-serine, formic acid, D-gluconic acid, L-histamine, D-methyl lactate, and citric acid, indicating that yhcZ gene could dramatically influence carbon source utilization of HD73 strains. Additionally, HD (ΔyhcZ) was less resistant to 8% NaCl, suggesting that yhcZ gene may be involved in the expression and regulation of genes related to high-salt stress response in bacterial cells. The results above show that the yhcZ gene significantly promotes glucose and other carbon sources utilization of HD73 strain during growth. Our findings will lay a foundation not only for analyzing the regulatory mechanisms of glucose and carbon sources utilization by yhcZ gene, but also providing a reference for the further research on bacterial growth and fermentation.

Cross Talk between Calcium and Reactive Oxygen Species Regulates Hyphal Branching and Ganoderic Acid Biosynthesis in Ganoderma lucidum under Copper Stress.

Ganoderma lucidum is among the best known medicinal basidiomycetes due to its production of many pharmacologically active compounds. To study the regulatory networks involved in its growth and development, we analyzed the relationship between reactive oxygen species (ROS) and Ca2+ signaling in the regulation of hyphal branching and ganoderic acid (GA) biosynthesis after Cu2+ treatment. Our results revealed that Cu2+ treatment decreased the distance between hyphal branches and increased the GA content and the intracellular levels of ROS and Ca2+ Further research revealed that the Cu2+-induced changes in hyphal branch distance, GA content, and cytosolic Ca2+ level were dependent on increases in cytosolic ROS. Our results also showed that increased cytosolic Ca2+ could reduce cytosolic ROS by activating antioxidases and modulating Cu2+ accumulation, resulting in feedback to adjust hyphal growth and GA biosynthesis. These results indicated that cytosolic ROS and Ca2+ levels exert important cross talk in the regulation of hyphal growth and GA biosynthesis induced by Cu2+ Taken together, our results provide a reference for analyzing the interactions among different signal transduction pathways with regard to the regulation of growth and development in other filamentous fungi.IMPORTANCEGanoderma lucidum, which is known as an important medicinal basidiomycete, is gradually becoming a model organism for studying environmental regulation and metabolism. In this study, we analyzed the relationship between reactive oxygen species (ROS) and Ca2+ signaling in the regulation of hyphal branching and ganoderic acid (GA) biosynthesis under Cu2+ stress. The results revealed that the Cu2+-induced changes in the hyphal branch distance, GA content, and cytosolic Ca2+ level were dependent on increases in cytosolic ROS. Furthermore, the results indicated that increased cytosolic Ca2+ could reduce cytosolic ROS levels by activating antioxidases and modulating Cu2+ accumulation. The results in this paper indicate that there was important cross talk between cytosolic ROS and Ca2+ levels in the regulation of hyphal growth and GA biosynthesis induced by Cu2.

UDP-glucose pyrophosphorylase influences polysaccharide synthesis, cell wall components, and hyphal branching in Ganoderma lucidum via regulation of the balance between glucose-1-phosphate and UDP-glucose.

UDP-glucose pyrophosphorylase (UGP) is a key enzyme involved in carbohydrate metabolism, but there are few studies on the functions of this enzyme in fungi. The ugp gene of Ganoderma lucidum was cloned, and enzyme kinetic parameters of the UGP recombinant protein were determined in vitro, revealing that this protein was functional and catalyzed the reversible conversion between Glc-1-P and UDP-Glc. ugp silencing by RNA interference resulted in changes in the levels of the intermediate metabolites Glc-1-P and UDP-Glc. The compounds and structure of the cell wall in the silenced strains were also altered compared with those in the wild-type strains. Moreover, the number of hyphal branches was also changed in the silenced strains. To verify the role of UGP in hyphal branching, a ugp-overexpressing strain was constructed. The results showed that the number of hyphal branches was influenced by UGP. The mechanism underlying hyphal branching was further investigated by adding exogenous Glc-1-P. Our results showed that hyphal branching was regulated by a change in the cytosolic Ca(2+) concentration, which was affected by the level of the intermediate metabolite Glc-1-P, in G. lucidum. Our findings indicate the existence of an interaction between carbon metabolism and Ca(2+) signaling in this fungus.