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The Tibetan Plateau (TP) is an important component of the global climate system, while the characteristics of its climate is poorly represented in most regional climate models at coarse resolutions. In this study, a 20-year (2000-2019) dynamical downscaling simulation at the gray-zone resolution (9 km) using the WRF model driven by the ERA5 reanalysis is conducted over the TP. Based on comparison against in-situ observations and the Integrated Multi-satellite Retrievals for GPM (IMERG) version 6 satellite precipitation product, the assessment of basic climate variables, such as near-surface air temperature (T2m) and precipitation, is performed to evaluate model’s performance and understand its added value better. Results show that both WRF and ERA5 can successfully reproduce the spatial patterns of annual mean and seasonal mean surface air temperature. However, significant cold and wet biases are found especially over the southeastern TP in ERA5, which are greatly improved in WRF with reduced RMSEs. Not only the climatological characteristics, but also the inter-annual variability and seasonal variation of T2m and precipitation are well captured by WRF which reduces the cold and wet biases especially in winter and summer compared to ERA5, respectively. Besides, at daily scale, the overestimation of precipitation in WRF and ERA5 is mainly caused by the overestimated precipitation frequency when precipitation intensity changed slightly. Furthermore, WRF outperforms ERA5 in capturing the diurnal variation of precipitation with more realistic peak time in all sub-regions over the TP. Further investigation into the mechanism of model bias reveals that less simulated snow cover fraction plays a crucial role in increasing the surface net energy by affecting surface albedo over the southeastern TP in WRF, leading to higher T2m. In addition, less water vapor transport from the southern boundary of TP leads to reduced wet bias in WRF, indicating that the added value in dynamical downscaling at gray-zone resolution is obtained by representing water vapor transport more realistically.

Background Epilepsy was defined as an abnormal brain network model disease in the latest definition. From a microscopic perspective, it is also particularly important to observe the Mutual Information (MI) of the whole brain network based on different lead positions. Methods In this study, we selected EEG data from representative temporal lobe and frontal lobe epilepsy patients. Based on Phase Space Reconstruction and the calculation of MI indicator, we used Complex Network technology to construct a dynamic brain network function model of epilepsy seizure. At the same time, about the analysis of our network, we described the index changes and propagation paths of epilepsy discharge in different periods, and spatially monitors the seizure change process based on the analysis of the parameter characteristics of the complex network. Results Our model portrayed the functional synergy between the various regions of the brain and the state transition during the seizure process. We also characterized the EEG synchronous propagation path and core nodes during seizures. The results shown the full node change path and the distribution of important indicators during the seizure process, which makes the state change of the seizure process more clearly. Conclusion In this study, we have demonstrated that synchronization-based brain networks change with time and space. The EEG synchronous propagation path and core nodes during epileptic seizures can provide a reference for finding the focus area.

Background Epilepsy is one of the diseases of the nervous system, which has a large population in the world. Traditional diagnosis methods mostly depended on the professional neurologists’ reading of the electroencephalogram (EEG), which was time-consuming, inefficient, and subjective. In recent years, automatic epilepsy diagnosis of EEG by deep learning had attracted more and more attention. But the potential of deep neural networks in seizure detection had not been fully developed. Methods In this article, we used a one-dimensional convolutional neural network (1-D CNN) to replace the residual network architecture’s traditional convolutional neural network (CNN). Moreover, we combined the Independent recurrent neural network (indRNN) and CNN to form a new residual network architecture-independent convolutional recurrent neural network (RCNN). Our model can achieve an automatic diagnosis of epilepsy EEG. Firstly, the important features of EEG were learned by using the residual network architecture of 1-D CNN. Then the relationship between the sequences were learned by using the recurrent neural network. Finally, the model outputted the classification results. Results On the small sample data sets of Bonn University, our method was superior to the baseline methods and achieved 100% classification accuracy, 100% classification specificity. For the noisy real-world data, our method also exhibited powerful performance. Conclusion The model we proposed can quickly and accurately identify the different periods of EEG in an ideal condition and the real-world condition. The model can provide automatic detection capabilities for clinical epilepsy EEG detection. We hoped to provide a positive significance for the prediction of epileptic seizures EEG.

Epilepsy is one of the world’s most common neurological diseases. Reliable early prediction and warning of seizures can provide timely treatment for patients with epilepsy, and improve their quality of life. Compared with most hand-designed prediction methods, an automatic prediction model that can process the original electroencephalogram (EEG) signals directly and take into account the leads optimization problem is needed. In this paper, we proposed an end-to-end automatic seizure prediction model based on the Batch Normalization Long Short Term Memory networks (BNLSTM) and Channel and Spatial attention (CASA). Firstly, raw EEG signals without any preprocessing are used as the input to the system, which can reduce the computation amount. Secondly, BNLSTM and CASA retained the time and spatial information of the raw EEG data respectively. Channel attention (CA) achieved the automatic optimization of EEG full-lead data and improved the prediction accuracy. Spatial attention (SA) achieved the adaptive learning of feature parameters. Finally, a fully connected layer is applied to predict the seizures. The performance of the seizure prediction model we proposed is evaluated on the data of 14 patients with Area Under the Curve (AUC) of 0.986, accuracy (Acc) of 0.956, specificity (Spe) of 0.968, and sensitivity (Sen) of 0.942. In addition, the proposed method provided an accurate prediction for all 50 seizures of the other 5 patients in the generalization dataset. Experimental results show that the proposed model has a certain generalization performance, which can provide a reliable basis for early warning of epileptic seizures.

The Tibetan Plateau (TP) is often referred to as ‘the Third Pole’ and plays an essential role in influencing the global climate. However, it remains challenging for most global and regional models to realistically simulate the characteristics of long-period climate over the TP. In this study, two Weather Research and Forecasting model (WRF) experiments using the regional climate simulation method of spectral nudging with gray-zone (GZ9) and convection-permitting (CP3) resolution are conducted for summer from 2009 to 2018. The surface air temperature (T2m) and precipitation from the two simulations and the global reanalysis ERA5 are evaluated against in-situ observations. The results show that ERA5 has a general cold bias over southern TP, especially in maximum T2m (Tmax), and wet bias over whole TP. Both experiments can successfully capture the spatial pattern and daily variation of T2m and precipitation, though cold bias for temperature and dry bias for precipitation exist especially over the regions south of 35°N. Compared with ERA5, the added value of the two WRF experiments is mainly reflected in the reduced cold bias especially for Tmax with more improvement found in CP3 and the reduced wet bias. However, the ability of WRF experiments in significantly improving the simulation of precipitation seems limited, which may be related to physical parameterization and lack of representativeness of station observation. Further investigation into surface radiation budget reveals that the underestimation of surface net radiation contributes a lot to the cold bias of T2m over the eastern TP in GZ9 while is improved in CP3 due to more downward solar radiation. Compared with GZ9, CP3 shows larger specific humidity at low-level (mid-high level) coexists with more precipitation (clouds) over the southern TP. This improvement is achieved by better depiction of topographic details and stronger northward water vapor transport (WVT) in CP3, providing more water vapor for precipitation at surface and much wetter condition in the mid-high level.

Most land plant species have the ability to establish a symbiosis with arbuscular mycorrhizal (AM) fungi. These fungi penetrate into root cortical cells and form branched structures (known as arbuscules) for nutrient exchange. We cloned the MdIAA24 from apple (Malus domestica) following its up-regulation during AM symbiosis. Results demonstrate the positive impact of the overexpression (OE) of MdIAA24 in apple on AM colonization. We observed the strigolactone (SL) synthesis genes, including MdD27, MdCCD7, MdCCD8a, MdCCD8b and MdMAXa, to be up-regulated in the OE lines. Thus, the OE lines exhibited both a higher SL content and colonization rate. Furthermore, we observed that the OE lines were able to maintain better growth parameters under AM inoculation conditions. Under drought stress with the AM inoculation, the OE lines were less damaged, which was demonstrated by a higher relative water content, a lower relative electrolytic leakage, a greater osmotic adjustment, a higher reactive oxygen species scavenging ability, an improved gas exchange capacity and an increased chlorophyll fluorescence performance. Our findings demonstrate that the OE of MdIAA24 in apple positively regulates the synthesis of SL and the formation of arbuscules as a drought stress coping mechanism.

The Tibetan Plateau (TP) is often referred to as ‘the Third Pole’ and plays an essential role in influencing the global climate. However, it remains challenging for most global and regional models to realistically simulate the characteristics of long-period climate over the TP. In this study, two Weather Research and Forecasting model (WRF) experiments using the regional climate simulation method of spectral nudging with gray-zone (GZ9) and convection-permitting (CP3) resolution are conducted for summer from 2009 to 2019. The surface air temperature (T2m) and precipitation are evaluated against in-situ observations and the Global Satellite Mapping of Precipitation (GSMaP) dataset. The results show that both experiments can successfully capture the spatial pattern and daily variation of T2m and precipitation, though cold bias for temperature and dry bias for precipitation exist especially over the regions south of 35ºN. Compared to GZ9, CP3 reduces the cold and dry bias over the southern TP. In addition, analysis of the diurnal variation of precipitation shows that both experiments simulate the advanced occurrence time of maximum precipitation by about 3 hours over the eastern TP but postpone the occurrence time of maximum precipitation over the central and western TP. Both experiments simulate a bimodal structure of the diurnal cycle of precipitation amount (PA). Further investigation reveals that GZ9 has more low-level clouds and prevents shortwave radiation from reaching the surface during daytime, leading to lower maximum surface air temperature (Tmax) in GZ9, while CP3 has more low-level clouds over the southeastern TP and preventing the outgoing longwave radiation and compensating the heat loss during nighttime, resulting in higher minimum surface air temperature (Tmin) in CP3. Besides, more water vapor over the southeastern TP results in more precipitation and thus reduced dry bias in CP3 over the southeastern TP. Moreover, the current study also indicates that gray-zone scale simulations can perform as good as convection-permitting simulations by carefully choosing the right parameterization schemes.

Ovarian granulosa cells (GC) play an essential role in the development and atresia of follicles. Emerging studies suggest that non-coding RNAs are involved in the regulation of GC apoptosis. Here, we aimed to analyze the function of ssc-circINHA-001, coded by the first exon of the inhibin subunit α gene (INHA), in resisting GC apoptosis and follicular atresia by enhancing the expression of the inhibin subunit β A (INHBA) through a cluster of miRNAs. A higher expression of ssc-circINHA-001 in healthy follicles compared to early atretic follicles was detected by qRT-PCR. Its circular structure was confirmed by RNase R treatment and reversed PCR. The function of ssc-circINHA-001 in GC resistance to apoptosis was detected by in vitro transfection of its si-RNA. Furthermore, the dual-luciferase reporter assay suggested that ssc-circINHA-001 adsorbed three miRNAs, termed miR-214-5p, miR-7144-3p, and miR-9830-5p, which share the common target INHBA. A low expression of ssc-circINHA-001 increased the levels of the free miRNAs, inhibited INHBA expression, and thus raised GCs apoptosis through a shift from the secretion of activin to that of inhibin. Our study demonstrated the existence of a circRNA–microRNAs–INHBA regulatory axis in follicular GC apoptosis and provides insight into the relationship between circRNA function and its coding gene in inhibin/activin balance and ovarian physiological functions.

Two regional climate simulation experiments (spectral nudging and re-initialization) at convection-permitting scale are conducted using the WRF model driven by the 4th generation Global Reanalysis data (ERA5) from European Centre for Medium-Range Weather Forecasts over the Tibetan Plateau (TP). The surface air temperature (T2m) and the precipitation in summer during 2016–2018 are evaluated against the in-situ station observations and the Global Satellite Mapping of Precipitation (GSMaP) dataset. The results show that both experiments as well as ERA5 can successfully capture the spatial distribution and the daily variation of T2m and precipitation, with reasonable cold bias for temperature and dry bias for precipitation when compared with the station observations. In addition, the diurnal cycle of precipitation is investigated, indicating that both experiments tend to simulate the afternoon precipitation peak in advance and postpone the night precipitation peak. The precipitation bias is reduced by using the spectral nudging technique, especially at night and early morning. Both WRF experiments outperform ERA5 in reproducing the diurnal cycle of precipitation amount. Possible causes for the differences between the two experiments are also analyzed. In the re-initialization experiment, the daytime net shortwave radiation contributes a lot to the cold biases of Tmax, and the stronger vertically integrated moisture flux convergence leads to more precipitation compared with the spectral nudging experiment over the central and southeastern TP. These results can provide valuable guidance for further fine-scale simulation studies over the TP.

Drought leads to reductions in plant growth and crop yields. Arbuscular mycorrhizal fungi (AMF), which form symbioses with the roots of the most important crop species, alleviate drought stress in plants. In the present work, we identified 14 GH3 genes in apple (Malus domestica) and provided evidence that MdGH3-2 and MdGH3-12 play important roles during AM symbiosis. The expression of both MdGH3-2 and MdGH3-12 was upregulated during mycorrhization, and the silencing of MdGH3-2/12 had a negative impact on AM colonization. MdGH3-2/12 silencing resulted in the downregulation of five genes involved in strigolactone synthesis, and there was a corresponding change in root strigolactone content. Furthermore, we observed lower root dry weights in RNAi lines under AM inoculation conditions. Mycorrhizal transgenic plants showed greater sensitivity to drought stress than WT, as indicated by their higher relative electrolytic leakage and lower relative water contents, osmotic adjustment ability, ROS scavenging ability, photosynthetic capacity, chlorophyll fluorescence values, and abscisic acid contents. Taken together, these data demonstrate that MdGH3-2/12 plays an important role in AM symbiosis and drought stress tolerance in apple.

Background: Follicular atresia is an inevitable degenerative process of ovarian follicles in mammals. The molecular events involved in atresia, particularly in granulosa cell apoptosis, have always attracted researchers’ attention. It is known that VEGFA isdownregulated during follicular atresia in pig ovaries and serves as an apoptosis inhibitor of granulosa cells. Besides, the TGF-β signalling has been considered as a central trigger in granulosa cell apoptosis. However, the link between TGF-β signalling and VEGFA is missing.Results:We proved that miR-361-5p significantly up-regulated during the atresia process andenhances GC apoptosis by direct targeting to VEGFA 3’UTR. In addition,we revealed that miR-361-5p coding geneMIR361was significant downregulation bySMAD4, the central intracellular mediator of TGF-β signalling,through promoter binding.Conclusions: Our findingsenriched the knowledge of VEGFA post-transcriptional regulation and completed the TGF-β/miR-361-5p/VEGFAregulatory networkin ovarian granulosa cell apoptosis. It offereduseful references for follicular atresia and ovarian physiological function studies.

Arbuscular mycorrhizal fungi (AMF) can form a symbiotic relationship with most terrestrial plant roots, promote plant growth, and heavy metal (HM) tolerance and thus plays a crucial role in phytoremediation. However, research on the relationship between colonization level and HM tolerance is limited. In this study, apple (Malus domestica) Gretchen Hagen3 genes MdGH3-2/12 silencing plants were treated with four AMF and Cd combination treatments to determine AMF colonization levels, biomass, Cd accumulation, photosynthesis, fluorescence, reactive oxygen species (ROS) and antioxidant substance accumulation, and Cd uptake, transport and detoxification gene expression levels. Results indicate the greater sensitivity of transgenic plants under AMF inoculation and Cd treatment compared with wild type (WT) via lower AMF colonization levels, biomass accumulation, photosynthetic parameters, and the accumulation and clearance homeostasis of ROS, as well as lower detoxification expression levels and higher Cd uptake and transport expression levels. Our study essentially demonstrates that MdGH3-2/12 plays an important role in Cd stress tolerance by regulating AM colonization in apple.

Follicular atresia is an inevitable degenerative process that occurs in mammalian ovarian follicles. The molecular events involved in atresia, particularly granulosa cell apoptosis, have long attracted researchers&rsquo, attention. Vascular endothelial growth factor A (VEGFA) is downregulated during follicular atresia in porcine ovaries and serves as an inhibitor of apoptosis in granulosa cells. In addition, transforming growth factor (TGF)-&beta, signaling has been considered a central trigger in granulosa cell apoptosis. However, the link between TGF-&beta, signaling and VEGFA is unknown. We proved that miR-361-5p is significantly upregulated during the atresia process and that it promotes GC apoptosis by directly targeting the VEGFA 3&prime, UTR. In addition, we revealed that the miR-361-5p coding gene MIR361 was significantly downregulated by SMAD4, the central intracellular mediator of TGF-&beta, signaling, that bound to the MIR361 promoter. In conclusion, our findings expanded what is known about VEGFA posttranscriptional regulation and revealed a complete SMAD4/miR-361-5p/VEGFA regulatory network in ovarian granulosa cell apoptosis. These data provide useful references for follicular atresia and ovarian physiological function studies.

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Titanium dioxide nanoparticles (TiO2 NPs) have the potential to produce reactive oxygen species and can be transferred from the mother to the fetal brain. The central nervous system exhibits remarkable plasticity in early life and can be altered significantly by environmental stressors encountered during fetal period. Additionally, prenatal stressors are involved with emotional problems in adulthood. The purpose of the current study is to evaluate whether prenatal exposure to TiO2 NPs could induce oxidative damage in the offspring brain and eventually affect the emotional behaviors in adulthood. The results showed that prenatal exposure to TiO2 NPs impaired the antioxidant status, caused a significant oxidative damage to nucleic acids and lipids in the brain of newborn pups, and enhanced the depressive-like behaviors during adulthood in the force swimming test and the sucrose preference test. These results suggest that the stress during fetal life induced by prenatal exposure to TiO2 NPs could be implicated in depressive-like behaviors in adulthood.