Simulating the effect of climate change on soil microbial community in an Abies georgei var. smithii forest

Qinghai–Tibet Plateau is considered a region vulnerable to the effects of climate change. Studying the effects of climate change on the structure and function of soil microbial communities will provide insight into the carbon cycle under climate change. However, to date, changes in the successional dynamics and stability of microbial communities under the combined effects of climate change (warming or cooling) remain unknown, which limits our ability to predict the consequences of future climate change. In this study, in situ soil columns of an Abies georgei var. smithii forest at 4,300 and 3,500 m elevation in the Sygera Mountains were incubated in pairs for 1 year using the PVC tube method to simulate climate warming and cooling, corresponding to a temperature change of ±4.7°C. Illumina HiSeq sequencing was applied to study alterations in soil bacterial and fungal communities of different soil layers. Results showed that warming did not significantly affect the fungal and bacterial diversity of the 0–10 cm soil layer, but the fungal and bacterial diversity of the 20–30 cm soil layer increased significantly after warming. Warming changed the structure of fungal and bacterial communities in all soil layers (0–10 cm, 10–20 cm, and 20–30 cm), and the effect increased with the increase of soil layers. Cooling had almost no significant effect on fungal and bacterial diversity in all soil layers. Cooling changed the structure of fungal communities in all soil layers, but it showed no significant effect on the structure of bacterial communities in all soil layers because fungi are more adapted than bacteria to environments with high soil water content (SWC) and low temperatures. Redundancy analysis (RDA) and hierarchical analysis showed that changes in soil bacterial community structure were primarily related to soil physical and chemical properties, whereas changes in soil fungal community structure primarily affected SWC and soil temperature (Soil Temp). The specialization ratio of fungi and bacteria increased with soil depth, and fungi were significantly higher than bacteria, indicating that climate change has a greater impact on microorganisms in deeper soil layers, and fungi are more sensitive to climate change. Furthermore, a warmer climate could create more ecological niches for microbial species to coexist and increase the strength of microbial interactions, whereas a cooler climate could have the opposite effect. However, we found differences in the intensity of microbial interactions in response to climate change in different soil layers. This study provides new insights to understand and predict future effects of climate change on soil microbes in alpine forest ecosystems

Biologically inspired structure learning with reverse knowledge distillation for spiking neural networks

Spiking neural networks (SNNs) have superb characteristics in sensory information recognition tasks due to their biological plausibility. However, the performance of some current spiking-based models is limited by their structures which means either fully connected or too-deep structures bring too much redundancy. This redundancy from both connection and neurons is one of the key factors hindering the practical application of SNNs. Although Some pruning methods were proposed to tackle this problem, they normally ignored the fact the neural topology in the human brain could be adjusted dynamically. Inspired by this, this paper proposed an evolutionary-based structure construction method for constructing more reasonable SNNs. By integrating the knowledge distillation and connection pruning method, the synaptic connections in SNNs can be optimized dynamically to reach an optimal state. As a result, the structure of SNNs could not only absorb knowledge from the teacher model but also search for deep but sparse network topology. Experimental results on CIFAR100 and DVS-Gesture show that the proposed structure learning method can get pretty well performance while reducing the connection redundancy. The proposed method explores a novel dynamical way for structure learning from scratch in SNNs which could build a bridge to close the gap between deep learning and bio-inspired neural dynamics

Benefits of laboratory personalized antiplatelet therapy in patients undergoing percutaneous coronary intervention: A meta-analysis of randomized controlled trials

   Background: The preventive effects of laboratory personalized antiplatelet therapy (PAPT) strategy in­cluding genetic detection and platelet function testing (PFT) on major adverse cardiac events (MACEs) and bleeding events in coronary artery disease (CAD) patients undergoing stenting has been extensively studied. Despite that, no clear conclusion can be drawn. In this study, a meta-analysis was performed to explore a more precise estimation of the benefits of laboratory PAPT. Methods: Randomized controlled trials were identified by the use of search databases such as PubMed, Embase, and Cochrane Controlled Trials Register up to May 2017, and the estimates were pooled. Results: Fourteen studies including 9497 patients met the inclusion criteria. The laboratory PAPT reduced MACEs risk (risk ratio [RR] 0.58, 95% confidence interval [CI] 0.42–0.80, p = 0.001), stent thrombosis (RR 0.60, 95% CI 0.41–0.87, p = 0.008) and myocardial infarctions (RR 0.43, 95% CI 0.21–0.88, p = 0.02) compared to the non-PAPT group. No statistically significant difference was observed between the two groups regarding cardiovascular death (RR 0.77, 95% CI 0.51–1.16, p = 0.21), bleeding events (RR 0.96, 95% CI 0.81–1.13, p = 0.59) and ischemic stroke (RR 0.81; 95% CI 0.39–1.66, p = 0.57). The preventive effect on MACEs was more significant in patients with high on-treatment platelet reactivity (RR 0.46; 95% CI 0.27–0.80, p = 0.006). Conclusions: Coronary artery disease patients after stenting could obtain benefits from laboratory PAPT. (Cardiol J 2018; 25, 1: 128–141

The research and development and application of minimal-oil igniting pulverized-coal burners

Paper presented at the 6th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 30 June - 2 July, 2008.It is very important for China to reduce the consumption of petroleum under the pressure of hers fundamental realities of lean-oil--rich-coal and the consistently increasing price of international crude oil. For this reason, we developed series of minimal-oil igniting burners applied on the boilers in power stations to reduce the oil consumption for ignition. The most significant characteristic of the burners is the average ignitingoil reduction by over 95%. This superior performance can be assured by some built-in igniting oil guns and by some novel designs for the minimal-oil burners. Up to now, the technology has achieved remarkable success on over 30 power units in China.vk201

Interferon-Gamma Release Assays for the Diagnosis of Active Tuberculosis in HIV-Infected Patients: A Systematic Review and Meta-Analysis

BACKGROUND: Interferon-gamma release assays (IGRAs) have provided a new method for the diagnosis of Mycobacterium tuberculosis infection. However, the role of IGRAs for the diagnosis of active tuberculosis (TB), especially in HIV-infected patients remains unclear. METHODS: We searched PubMed, EMBASE and Cochrane databases to identify studies published in January 2001-July 2011 that evaluated the evidence of using QuantiFERON-TB Gold in-tube (QFT-GIT) and T-SPOT.TB (T-SPOT) on blood for the diagnosis of active TB in HIV-infected patients. RESULTS: The search identified 16 eligible studies that included 2801 HIV-infected individuals (637 culture confirmed TB cases). The pooled sensitivity for the diagnosis of active TB was 76.7% (95%CI, 71.6-80.5%) and 77.4% (95%CI, 71.4-82.6%) for QFT-GIT and T-SPOT, respectively, while the specificity was 76.1% (95%CI, 74.0-78.0%) and 63.1% (95%CI, 57.6-68.3%) after excluding the indeterminate results. Studies conducted in low/middle income countries showed slightly lower sensitivity and specificity when compared to that in high-income countries. The proportion of indeterminate results was as high as 10% (95%CI, 8.8-11.3%) and 13.2% (95%CI, 10.6-16.0%) for QFT-GIT and T-SPOT, respectively. CONCLUSION: IGRAs in their current formulations have limited accuracy in diagnosing active TB in HIV-infected patients, and should not be used alone to rule out or rule in active TB cases in HIV-infected patients. Further modification is needed to improve their accuracy

Efficient Structure Slimming for Spiking Neural Networks

Spiking neural networks (SNNs) are deeply inspired by biological neural information systems. Compared to convolutional neural networks (CNNs), SNNs are low power consumption because of their spike based information processing mechanism. However, most of the current structures of SNNs are fully-connected or converted from deep CNNs which poses redundancy connections. While the structure and topology in human brain systems are sparse and efficient. This paper aims at taking full advantage of sparse structure and low power consumption which lie in human brain and proposed efficient structure slimming methods. Inspired by the development of biological neural network structures, this paper designed types of structure slimming methods including neuron pruning and channel pruning. In addition to pruning, this paper also considers the growth and development of the nervous system. Through iterative application of the proposed neural pruning and rewiring algorithms, experimental evaluations on CIFAR-10, CIFAR-100, and DVS-Gesture datasets demonstrate the effectiveness of the structure slimming methods. When the parameter count is reduced to only about 10% of the original, the performance decreases by less than 1%

Interplay between Defects and Short-Range Disorder Manipulating the Oxygen Evolution Reaction on a Layered Double Hydroxide Electrocatalyst

Improving the efficiency of the oxygen evolution reaction (OER) is crucial for advancing sustainable and environmentally friendly hydrogen energy. Layered double hydroxides (LDHs) have emerged as promising electrocatalysts for the OER. However, a thorough understanding of the impact of structural disorder and defects on the catalytic activity of LDHs remains limited. In this work, a series of NiAl-LDH models are systematically constructed, and their OER performance is rigorously screened through theoretical density functional theory. The acquired results unequivocally reveal that the energy increase induced by structural disorder is effectively counteracted at the defect surface, indicating the coexistence of defects and disorder. Notably, it is ascertained that the simultaneous presence of defects and disorder synergistically augments the catalytic activity of LDHs in the context of the OER. These theoretical findings offer valuable insights into the design of highly efficient OER catalysts while also shedding light on the efficacy of LDH electrocatalysts

Litchi Flavonoids: Isolation, Identification and Biological Activity

The current status of the isolation, identification, biological activity, utilization and development prospects of flavonoids found in litchi fruit pericarp (LFP) tissues is reviewed. LFP tissues account for approximately 15% by weight of the whole fresh fruit and are comprised of significant amount of flavonoids. The major flavonoids in ripe LFP include flavonols and anthocyanins. The major flavanols in the LFP are reported to be procyanidin B4, procyanidin B2 and epicatechin, while cyanindin-3-rutinside, cyanidin-3-glucoside, quercetin-3-rutinosde and quercetin-3-glucoside are identified as the important anthocyanins. Litchi flavanols and anthocyanins exhibit good potential antioxidant activity. The hydroxyl radical and superoxide anion scavenging activities of procyanidin B2 are greater than those of procyanidin B4 and epicatechin, while epicatechin has the highest α,α-diphenyl-β-picrylhydrazyl radical (DPPH·) scavenging activity. In addition to the antioxidant activity, LFP extract displays a dose- and time-dependent inhibitory effect on human breast cancer, which could be attributed, in part, to its inhibition of proliferation and induction of apoptosis in cancer cells through upregulation and down-regulation of multiple genes. Furthermore, various anticancer activities are observed for epicatechin, procyanidin B2, procyanidin B4 and the ethyl acetate fraction of LFP tissue extracts. Procyanidin B4 and the ethyl acetate fraction show a stronger inhibitory effect on HELF than MCF-7 proliferation, while epicatechin and procyanidin B2 have lower cytotoxicities towards MCF-7 and HELF than paclitaxel. It is therefore suggested that flavonoids from LFP might be potentially useful components for functional foods and/or anti-breast cancer drugs