Changes in grassland soil types lead to different characteristics of bacterial and fungal communities in Northwest Liaoning, China

IntroductionSoil microbial communities are critical in regulating grassland biogeochemical cycles and ecosystem functions, but the mechanisms of how environmental factors affect changes in the structural composition and diversity of soil microbial communities in different grassland soil types is not fully understood in northwest Liaoning, China.MethodsWe investigated the characteristics and drivers of bacterial and fungal communities in 4 grassland soil types with 11 sites across this region using high-throughput Illumina sequencing.Results and DiscussionActinobacteria and Ascomycota were the dominant phyla of bacterial and fungal communities, respectively, but their relative abundances were not significantly different among different grassland soil types. The abundance, number of OTUs, number of species and diversity of both bacterial and fungal communities in warm and temperate ecotone soil were the highest, while the warm-temperate shrub soil had the lowest microbial diversity. Besides, environmental factors were not significantly correlated with soil bacterial Alpha diversity index. However, there was a highly significant negative correlation between soil pH and Shannon index of fungal communities, and a highly significant positive correlation between plant cover and Chao1 index as well as Observed species of fungal communities. Analysis of similarities showed that the structural composition of microbial communities differed significantly among different grassland soil types. Meanwhile, the microbial community structure of temperate steppe-sandy soil was significantly different from that of other grassland soil types. Redundancy analysis revealed that soil total nitrogen content, pH and conductivity were important influencing factors causing changes in soil bacterial communities, while soil organic carbon, total nitrogen content and conductivity mainly drove the differentiation of soil fungal communities. In addition, the degree of connection in the soil bacterial network of grassland was much higher than that in the fungal network and soil bacterial and fungal communities were inconsistently limited by environmental factors. Our results showed that the microbial community structure, composition and diversity of different grassland soil types in northwest Liaoning differed significantly and were significantly influenced by environmental factors. Microbial community structure and the observation of soil total nitrogen and organic carbon content can predict the health changes of grassland ecosystems to a certain extent

Nociceptin Receptor Is Overexpressed in Non-small Cell Lung Cancer and Predicts Poor Prognosis

Classic opioid receptors, mu (μ), delta (δ), and kappa (κ), have been reported to be expressed in non-small cell lung cancer (NSCLC) cell lines and tumor tissues and to play a role in tumor prognosis. However, the expression and role of the non-classic opioid receptor, nociceptin receptor (NOP) in cancer are unclear. Our hypothesis was that NOP was also highly expressed in NSCLC tumor tissues and this could be correlated with patients' prognostic characters. Expression of NOP was examined in archived cancer tissues from 129 enrolled NSCLC patients by immunohistochemistry and was further analyzed with the patients' outcomes. NOP expression in NSCLC cell lines was also detected. The dataset from Kaplan-Meier Plotter was used to explore the correlation between the levels of NOP mRNA in cancerous tissue and the prognosis of NSCLC patients. Cell functional assays were performed to detect the effect of NOP activation on tumor aggressive furthers. Results showed NOP expression was highly expressed in cancer tissues and human cancer cell lines. NOP expression was not associated with patients' opioid requirement but closely with some clinicopathological indicators which reflected the malignancy. Moreover, NOP staining level was the independent poor prognostic factor for NSCLC patients receiving lobectomy, which was further verified by determining the mRNA expression levels through the online dataset. In vitro experiments revealed that NOP activation promotes the proliferation and invasion of A549 cells via PI3K/Akt signaling pathway. We conclude that NOP is overexpressed in NSCLC and is inversely correlated with patient's postoperative survival

PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features

Speech-driven 3D facial animation has improved a lot recently while most related works only utilize acoustic modality and neglect the influence of visual and textual cues, leading to unsatisfactory results in terms of precision and coherence. We argue that visual and textual cues are not trivial information. Therefore, we present a novel framework, namely PMMTalk, using complementary Pseudo Multi-Modal features for improving the accuracy of facial animation. The framework entails three modules: PMMTalk encoder, cross-modal alignment module, and PMMTalk decoder. Specifically, the PMMTalk encoder employs the off-the-shelf talking head generation architecture and speech recognition technology to extract visual and textual information from speech, respectively. Subsequently, the cross-modal alignment module aligns the audio-image-text features at temporal and semantic levels. Then PMMTalk decoder is employed to predict lip-syncing facial blendshape coefficients. Contrary to prior methods, PMMTalk only requires an additional random reference face image but yields more accurate results. Additionally, it is artist-friendly as it seamlessly integrates into standard animation production workflows by introducing facial blendshape coefficients. Finally, given the scarcity of 3D talking face datasets, we introduce a large-scale 3D Chinese Audio-Visual Facial Animation (3D-CAVFA) dataset. Extensive experiments and user studies show that our approach outperforms the state of the art. We recommend watching the supplementary video

Visualization of Endolymphatic Hydrops in Patients With Unilateral Idiopathic Sudden Sensorineural Hearing Loss With Four Types According to Chinese Criterion

Objective: The aim of this study is to evaluate the possible value of endolymphatic hydrops (EH) in patients with unilateral idiopathic sudden sensorineural hearing loss (UISSNHL) with four types according to audiometry.Methods: Seventy-two patients (40 men and 32 women; age range, 28–78 years; mean age: 50.0 ± 12.9 years) with UISSNHL were admitted retrospectively into this study. Based on the pure tone audiometry before treatment, the hearing loss of all these patients were categorized into four types: low-frequency group (LF-G), high-frequency group (HF-G), flat group (F-G), and total deafness group (TD-G). The average time from symptom onset to the first examination was 6.9 ± 4.4 days (1–20 days). 3D-FLAIR MRI was performed 24 h after intratympanic injection of gadolinium (Gd) within 1 week after the UISSNHL onset. The incidence of EH in the affected ears based on four types of hearing loss were analyzed using the Chi-square test, and the possible relationship with vertigo and prognosis were also assessed.Results: Eleven of 21 patients (52.4%) in LF-G had the highest EH-positive rate, followed by 18.2% in HF-G, 11.8% in F-G, and 17.4% in TD-G. The significant difference was found in the four groups (P = 0.018). The EH rate of LF-G was statistically significantly higher than that of F-G and TD-G (P = 0.009, P =0.014), respectively. After being valued by the volume-referencing grading system (VR scores), the EH level was represented by the sum scores of EH. In LF-G, no statistically significant difference was found in the prognosis of ISSNHL patients between with the EH group and the no EH group (P = 0.586). The symptom “vertigo” did not correlate with EH and prognosis.Conclusions: EH was observed in UISSNHL patients by 3D-FLAIR MRI. EH may be responsible for the pathology of LF-G but not related to prognosis. It might be meaningless to assess EH in other hearing loss types, which might be more related to the blood-labyrinth dysfunction

Fungus Pichia kudriavzevii XTY1 and heterotrophic nitrifying bacterium Enterobacter asburiae GS2 cannot efficiently transform organic nitrogen via hydroxylamine and nitrite

Heterotrophic nitrification is a process of organic nitrogen degradation completed by the participation of heterotrophic nitrifying microorganisms, which can accelerate the nitrogen transformation process. However, the current research mainly focuses on heterotrophic nitrifying bacteria and their ammonium degradation capacities. And there is little accumulation of research on fungi, the main force of heterotrophic nitrification, and their capacities to transform organic nitrogen. In this study, novel heterotrophic nitrifying fungus (XTY1) and bacterium (GS2) were screened and isolated from upland soil, and the strains were identified and registered through GenBank comparison. After 24 h single nitrogen source tests and 15N labeling tests, we compared and preliminarily determined the heterotrophic nitrification capacities and pathways of the two strains. The results showed that XTY1 and GS2 had different transformation capacities to different nitrogen substrates and could efficiently transform organic nitrogen. However, the transformation capacity of XTY1 to ammonium was much lower than that of GS2. The two strains did not pass through NH2OH and NO2− during the heterotrophic nitrification of organic nitrogen, and mainly generated intracellular nitrogen and low N2O. Other novel organic nitrogen metabolism pathways may be existed, but they remain to be further validated

oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

With the rapid development of deep learning models and hardware support for dense computing, the deep learning workload characteristics changed significantly from a few hot spots on compute-intensive operations to a broad range of operations scattered across the models. Accelerating a few compute-intensive operations using the expert-tuned implementation of primitives does not fully exploit the performance potential of AI hardware. Various efforts have been made to compile a full deep neural network (DNN) graph. One of the biggest challenges is to achieve high-performance tensor compilation by generating expert level performance code for the dense compute-intensive operations and applying compilation optimization at the scope of DNN computation graph across multiple compute-intensive operations. We present oneDNN Graph Compiler, a tensor compiler that employs a hybrid approach of using techniques from both compiler optimization and expert-tuned kernels for high performance code generation of the deep neural network graph. oneDNN Graph Compiler addresses unique optimization challenges in the deep learning domain, such as low-precision computation, aggressive fusion of graph operations, optimization for static tensor shapes and memory layout, constant weight optimization, and memory buffer reuse. Experimental results demonstrate significant performance gains over existing tensor compiler and primitives library for performance-critical DNN computation graphs and end-to-end models on Intel Xeon Scalable Processors.Comment: 10 pages excluding reference, 9 figures, 1 tabl

Different responses of soil fungal and bacterial communities to nitrogen addition in a forest grassland ecotone

IntroductionContinuous nitrogen deposition increases the nitrogen content of terrestrial ecosystem and affects the geochemical cycle of soil nitrogen. Forest-grassland ecotone is the interface area of forest and grassland and is sensitive to global climate change. However, the structure composition and diversity of soil microbial communities and their relationship with soil environmental factors at increasing nitrogen deposition have not been sufficiently studied in forest-grassland ecotone.MethodsIn this study, experiments were carried out with four nitrogen addition treatments (0 kgN·hm−2·a−1, 10 kgN·hm−2·a−1, 20 kgN·hm−2·a−1 and 40 kgN·hm−2·a−1) to simulate nitrogen deposition in a forest-grassland ecotone in northwest Liaoning Province, China. High-throughput sequencing and qPCR technologies were used to analyze the composition, structure, and diversity characteristics of the soil microbial communities under different levels of nitrogen addition.Results and discussionThe results showed that soil pH decreased significantly at increasing nitrogen concentrations, and the total nitrogen and ammonium nitrogen contents first increased and then decreased, which were significantly higher in the N10 treatment than in other treatments (N:0.32 ~ 0.48 g/kg; NH4+-N: 11.54 ~ 13 mg/kg). With the increase in nitrogen concentration, the net nitrogen mineralization, nitrification, and ammoniation rates decreased. The addition of nitrogen had no significant effect on the diversity and structure of the fungal community, while the diversity of the bacterial community decreased significantly at increasing nitrogen concentrations. Ascomycetes and Actinomycetes were the dominant fungal and bacterial phyla, respectively. The relative abundance of Ascomycetes was negatively correlated with total nitrogen content, while that of Actinomycetes was positively correlated with soil pH. The fungal community diversity was significantly negatively correlated with nitrate nitrogen, while the diversity of the bacterial community was significantly positively correlated with soil pH. No significant differences in the abundance of functional genes related to soil nitrogen transformations under the different treatments were observed. Overall, the distribution pattern and driving factors were different in soil microbial communities in a forest-grassland ecotone in northwest Liaoning. Our study enriches research content related to factors that affect the forest-grassland ecotone

FGF22 deletion causes hidden hearing loss by affecting the function of inner hair cell ribbon synapses

Ribbon synapses are important structures in transmitting auditory signals from the inner hair cells (IHCs) to their corresponding spiral ganglion neurons (SGNs). Over the last few decades, deafness has been primarily attributed to the deterioration of cochlear hair cells rather than ribbon synapses. Hearing dysfunction that cannot be detected by the hearing threshold is defined as hidden hearing loss (HHL). The relationship between ribbon synapses and FGF22 deletion remains unknown. In this study, we used a 6-week-old FGF22 knockout mice model (Fgf22–/–) and mainly focused on alteration in ribbon synapses by applying the auditory brainstem response (ABR) test, the immunofluorescence staining, the patch-clamp recording, and quantitative real-time PCR. In Fgf22–/– mice, we found the decreased amplitude of ABR wave I, the reduced vesicles of ribbon synapses, and the decreased efficiency of exocytosis, which was suggested by a decrease in the capacitance change. Quantitative real-time PCR revealed that Fgf22–/– led to dysfunction in ribbon synapses by downregulating SNAP-25 and Gipc3 and upregulating MEF2D expression, which was important for the maintenance of ribbon synapses’ function. Our research concluded that FGF22 deletion caused HHL by affecting the function of IHC ribbon synapses and may offer a novel therapeutic target to meet an ever-growing demand for deafness treatment

Cartilage oligomeric matrix protein is a novel notch ligand driving embryonic stem cell differentiation towards the smooth muscle lineage

Cartilage oligomeric matrix protein (COMP), a protective component of vascular extracellular matrix (ECM), maintains the homeostasis of mature vascular smooth muscle cells (VSMCs). However, whether COMP modulates the differentiation of stem cells towards the smooth muscle lineage is still elusive. Firstly, purified mouse COMP directly induced mouse embryonic stem cell (ESC) differentiation into VSMCs both in vitro and in vivo, while the silencing of endogenous COMP markedly inhibited ESC-VSMC differentiation. RNA-Sequencing revealed that Notch signaling was significantly activated by COMP during ESC-VSMC differentiation, whereas the inhibition of Notch signaling attenuated COMP-directed ESC-VSMC differentiation. Furthermore, COMP deficiency inhibited Notch activation and VSMC differentiation in mice. Through silencing distinct Notch receptors, we identified that Notch1 mainly mediated COMP-initiated ESC-VSMC differentiation. Mechanistically, COMP N-terminus directly interacted with the EGF11-12 domain of Notch1 and activated Notch1 signaling, as evidenced by co-immunoprecipitation and mammalian two-hybrid assay. In conclusion, COMP served as a potential ligand of Notch1, thereby driving ESC-VSMC differentiation