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Automatic first‐break picking is a basic step in seismic data processing, so much so that the quality of the picking largely determines the effect of subsequent processing. To a certain extent, artificial intelligence technology has solved the shortcomings of traditional first‐break picking algorithms, such as poor applicability and low efficiency. However, some problems still remain for seismic data, with a low signal‐to‐noise ratio and large first‐break change leading to inaccurate picking and poor generalization of the network. In order to improve the accuracy of the automatic first‐break picking results of the above seismic data, we propose a multi‐view automatic first‐break picking method driven by multi‐network. First, we analysed the single‐trace boundary characteristics and the two‐dimensional boundary characteristics of the first break. Based on these two characteristics of the first break, we used the Long Short‐Term Memory and the ResNet attention gate UNet (resudual attention gate UNet) networks to extract the characteristics of the first arrival and its location from the seismic data, respectively. Then, we introduced the idea of multi‐network learning in the first‐break picking work and designed a feature fusion network. Finally, the multi‐view first‐break features extracted by the Long Short‐Term Memory and resudual attention gate UNet networks are fused, which effectively improves the picking accuracy. The results obtained after applying the method to field seismic data show that the accuracy of the first break detected by a feature fusion network is higher than that given by the above two networks alone and has good applicability and resistance to noise. [ABSTRACT FROM AUTHOR]

Climate change is always an immense challenge for conservation biologists in the development and implementation of effective conservation strategies. The expected loss of biodiversity due to climate change weakens the delivery of ecosystem functioning and services, which can lead to a global environmental crisis. This study aims to conduct a comprehensive review of literature on recent progress in climate change and biodiversity conservation research and identifies the leading countries, institutions and researchers in this research area. We also aim to explore the current research trends, and existing scientific knowledge as well as to provide perspectives on the topic. A scientometric analysis approach included co-occurrence analysis of countries, institutions, and authors for research productivity and academic development; co-occurrence of keywords for identification of research hotspots; co-citation analysis for prominent articles and journals; and keyword burst for detection of global research trends, was applied by using CiteSpace based on 1965 articles retrieved from the Web of Science Core Collection for the period 2000–2021. We found an increasing research production over time on climate change and biodiversity conservation research. Although climate change and biodiversity conservation research have been studied across the globe (particularly in developed countries such as the USA) and institutions (such as the University of Queensland, Australia), several more countries, regions and institutions are underrepresented across the globe. The current research hot topics we found are mainly “management”, “impact”, “diversity” and “land use”, whereas the research trends are “richness”, “scenario”, “perception” and “REDD”. Thus, further research is needed to cover the huge knowledge gap related to humans, climate change, biodiversity, and ecosystem functioning across the globe (particularly in unexplored countries and regions) through several interdisciplinary approaches and collaborations.

Seismic analysis and interpretation are sensitive to data resolution. High-density acquisition, deconvolution, and inverse $Q$ filtering are traditional methods for resolution improvement. These methods have drawbacks such as strict assumptions and complex parameter solving processes. In this letter, we propose a channel attention U-Net and physical convolution combination (CAUC) algorithm to overcome these limitations. First, we design a channel attention U-Net (CAU) to establish a sophisticated nonlinear relationship between low-frequency data and coarse reflection coefficients. Specifically, we use a channel attention block after each downsampling convolution block to extract important local features of seismic data. Second, we convolve the coarse reflection coefficients with the wavelets to obtain high-resolution data. This physical convolution operation has a solid theoretical foundation. Therefore, our algorithm benefits not only from the learning ability of the neural network but also from the explainability of the physical operation. Both synthetic and field data are employed to verify the validity of the new algorithm. The traditional fast iterative shrinkage-thresholding algorithm (FISTA) and deep convolutional neural network (CNN) are used for comparison. The results show the superiority of the proposed method, especially in enhancing details such as thin layers and continuity. [ABSTRACT FROM AUTHOR]

Deep learning has made substantial progress in remote sensing image segmentation tasks. It usually requires a large number of high-quality annotation maps (i.e., clean labels), which are labor-intensive. In this letter, we propose to use abundant electronic maps (i.e., noisy labels) to supplement a small number of clean labels to solve the problem of massive label production. In addition, we propose a multistage noise supervised framework to prevent noise from deteriorating the performance of deep model. Noise-supervised deep learning framework (NSDI) consists of clean training, weight initialization, and hybrid training stages. In the clean training stage, we train a segmentation model using a small amount of clean labels and remote sensing images to compute the confusion probability matrix. In the weight initialization stage, we use the confusion probability matrix and the prediction probability to calculate the label reliability of the electronic map. In the hybrid training stage, an adaptive weighted loss function based on cross-entropy is used to dynamically update the label reliability. Then we train the model further using electronic maps with the support of the adaptive weighted loss function and label reliability. Experiments were undertaken on 2656 images of 512 × 512 pixels. Ablation studies show that NSDI improves the model robustness and the segmentation quality. [ABSTRACT FROM AUTHOR]

The Sichuan Basin is a significant region for exploration and development of shale gas in China, and it is essential to clarify the impact of deep shale gas reservoir parameters on cost-effective development at scale to ensure national energy security. Rock physics modeling is a significant means of communicating the physical and elastic parameters of rocks. A rock physics modeling method applicable to fractured shale gas reservoirs is proposed for the current situation of complex fluid relationships in shale gas reservoirs and unclear characteristics of gas identification seismic response. In this paper, based on the Self Consistent Approximation (SCA) model and the differential effective medium (DEM) model, the anisotropic source of shale is used as a starting point to add bound water, kerogen, clay, and brittle minerals, the Schoenberg linear slip theory is used to add fracture disturbance effects, and then the Brown–Korringa model is used to perform fluid replacement under anisotropic conditions. Finally a rock physics model applicable to fractured shale gas reservoirs is obtained, and the established rock physics model is used for analysis of elastic parameters, Thomsen parameters, and fracture weakness parameters. Rock physics tests were performed on shale in southern Sichuan as an example. The experimental results show that the model established by the process can accurately invert the longitudinal and transverse wave velocities of the shale, which can provide a conceptual basis for the study of fractured shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Brittleness is an important factor that indicates shale properties, as well as fracturability, and it can be well-represented using the elasticity parameter Eρ. Seismic inversion allows direct access to the Eρ ofbrittleness parameters. Seismic inversion is a typical ill-posed problem that has an enormous multiplicity of solutions. In order to invert reservoir brittleness parameters more stably and reliably, a direct inversion method for determining brittleness parameters based on a reweighted Lp-norm is proposed, and the reweighted Lp method is introduced to brittleness parameter inversion for the first time. The alternating direction method of multipliers (ADMM) is used to establish the inversion structure and to optimize the objective function in blocks, which effectively improves the convergence speed. We first introduce a reweighted Lp method and establish a pre-stack inversion objective function based on the reweighted Lp method. Then, theoretical simulation data are applied to compare the inversion outcomes of the new method with those of the traditional method, and the effect of the method in this manuscript is verified. Finally, the feasibility of this method is further verified using actual data for experimental analysis. Through an analysis of the experimental results, we find that this method can be well-applied to seismic pre-stack inversion calculation and provides a new direct inversion method for the determination of brittleness parameters for exploration geophysics. [ABSTRACT FROM AUTHOR]

This paper presents a novel trans-critical CO2 heat pump cycle with expander (TCCE) for increasing COP in the warm period and the suction preheating in the cold period. This cycle has two main operation modes. One is TCCEA for warm period and the other is TCCEB for cold period. Theoretical simulations are conducted to study energy efficiency and exergy efficiency of this novel cycle as well as the basic cycle. The results show that in the warm period TCCEA has an excellent COP and exergy efficiency and at low discharge pressure, the COP of TCCEA is improved by up to 31.49% compared with the basic cycle. Additionally, in the cold period, using TCCEB is helpful to avoid liquid suction. Compared with the basic cycle, the heating capacity of TCCEB can be improved by up to 12%. Taking the heating capacity into account, TCCEB is the best system under the warm period. According to the simulation results, this novel cycle is better suited for warm or cold weather. [ABSTRACT FROM AUTHOR]

Unconventional reservoirs usually have strong anisotropy. Generally, they can be regarded as transversely isotropic media with a vertical symmetry axis [(VTI) media] in the absence of fractures. Therefore, it is of great significance to develop high-accuracy inversion method for VTI media. The three elastic parameters and two Thomsen anisotropy parameters of VTI media are usually obtained by indirect calculation or inversion methods based on the approximate formulas. However, the cumulative errors caused by indirect calculation and low calculation accuracy of the approximate formulas limit the estimation accuracy of these parameters. In this article, we propose a new method based on the exact reflection coefficients equations (ERCEs) of VTI media to improve the inversion accuracy of these elastic and anisotropy parameters. The new method adopts the Bayesian deterministic inversion (BDI) strategy to solve the inversion problem, which becomes highly nonlinear when using the ERCEs. We analyze the feasibility of the new method using the residual function maps (RFMs) and eigenvalue analysis of Hessian matrix. The analysis results show that the BDI strategy can well solve a series of problems brought by the ERCEs for nonlinear inversion, such as strong nonlinearity and more target parameters need to invert. Both synthetic and field data examples show that the proposed method can accurately estimate the elastic and anisotropy parameters, which verifies the feasibility and effectiveness of the method. [ABSTRACT FROM AUTHOR]

In the absence of fracture, the strata with horizontal interbedding structure can be approximately equivalent to transversely isotropic media with vertical axis of symmetry (VTI) in the sedimentary basin. Accurate estimation of Young’s modulus, Poisson’s ratio, and weak anisotropy (WA) parameters can provide basic information for further prediction of shale reservoir rock brittleness and in situ stress. Based on the scattering theory and Born approximation, we derive the P-wave reflection coefficients involving Young’s modulus and Poisson’s ratio and WA parameters for an interface separating two elastic VTI media. Assuming in the case of shale, we modify this reflection coefficient to involve only three model parameters through a series of integration and simplification for stabler inversion. A Bayesian amplitude versus offset (AVO) inversion method is implemented to estimate the three attributes, which are then converted to calculate the brittleness-related and WA parameters. The numerical simulation results show that for AVO of III in the case of gas-bearing shale, the derived approximation has more accuracy than the Young’s modulus, Poisson’s ratio and density (YPD) equation, especially at large angle. Tests on synthetic and real seismic data verify that the established inversion strategy for VTI shale reservoirs is stable and accurate in the estimation of brittleness-related and WA parameters. [ABSTRACT FROM AUTHOR]

One of the typical anisotropic media is the monoclinic anisotropy (MA) medium, which is formed by embedding two sets of non-orthogonal fracture sets into an isotropic or vertical transverse isotropic (VTI) background medium. Weak anisotropy (WA) parameters and fracture density provide important in situ stress and high-porosity zone information. Estimation of WA parameters and fracture density of MA medium by prestack seismic amplitude inversion is important for shale reservoir characterisation. We derive the expression of generalised WA parameters in a basic reflection coefficients formula of MA medium by incorporating a stiffness matrix of VTI background and disturbance compliance matrix of asymmetric fracture. We then re-express the P-wave reflection coefficients in terms of WA parameters and fracture compliance tensors. To achieve the direct inversion of fracture density, we rewrite the linearised expression of P-wave reflection coefficients related to WA parameters and fracture density. Finally, under the Bayesian framework, the WA parameters and fracture density are estimated by using the amplitude versus offset and azimuth (AVOA) inversion parameters. We use a Monte Carlo simulation to test the effect of uncertainties in the priori information about fracture property parameters. The application of synthetic seismic gathers show that the proposed inversion strategy is reliable within moderate noise. Compared with the results obtained by using inversion based on a rotationally invariant fracture, the test indicates that a fracture model with a simplified shape or wrong assumption will increase calculation error and reduce the inversion accuracy. [ABSTRACT FROM AUTHOR]

In shale gas development, fracture density is an important lithologic parameter to properly characterize reservoir reconstruction, establish a fracturing scheme, and calculate porosity and permeability. The traditional methods usually assume that the fracture reservoir is one set of aligned vertical fractures, embedded in an isotropic background, and estimate some alternative parameters associated with fracture density. Thus, the low accuracy caused by this simplified model, and the intrinsic errors caused by the indirect substitution, affect the estimation of fracture density. In this paper, the fractured rock of monoclinic symmetry assumes two non-orthogonal vertical fracture sets, embedded in a transversely isotropic background. Firstly, assuming that the fracture radius, width, and orientation are known, a new form of P-wave reflection coefficient, in terms of weak anisotropy (WA) parameters and fracture density, was obtained by substituting the stiffness coefficients of vertical transverse isotropic (VTI) background, normal, and tangential fracture compliances. Then, a linear amplitude versus offset and azimuth (AVOA) inversion method, of WA parameters and fracture density, was constructed by using Bayesian theory. Tests on synthetic data showed that WA parameters, and fracture density, are stably estimated in the case of seismic data containing a moderate noise, which can provide a reliable tool in fracture prediction. [ABSTRACT FROM AUTHOR]

Recently, the seismic illumination analysis has progressed considerably in methodology which has been developed not only from one-way wave equation-based illumination to full-wave equation-based illumination but also from conventional illumination analysis to directional illumination analysis with local plane-wave decomposition. Because of the inherent defects of the one-way wave equation, the full-wave equation-based seismic illumination methods have increasingly attracted more attention. However, full-wave equation-based wavefield includes both downgoing and upgoing waves, such as transmissive, turning, and reflected waves. This hybrid wavefield can mislead us in seismic illumination analysis. For the sake of a preferable seismic illumination analysis method, we separated upgoing and downgoing wavefields in the time domain using Poynting vector and defined the incident and reflected illumination analysis functions based on the separated wavefields. Furthermore, we applied these two new illumination functions in seismic illumination analysis with the Sigsbee2a model. Multiple-shot illumination results show that the full-wave illumination and incident illumination maps are consistent with the seismic migration image. Because of no interference caused by the interactions between upgoing and downgoing waves, the incident illumination is superior for illumination analysis. Successful application of the full-wave equation-based incident and reflected illumination functions in the actual acquisition direction design of marine seismic geometry verifies their applicability and reveals their excellent prospects. [ABSTRACT FROM AUTHOR]

Transient effective flow and force areas of reed valve in a rotary compressor are studied by two three-dimensional fluid–structure interaction (FSI) models. One is the full FSI model, the other one is the simplified FSI model, in which the discharge port is not covered. It is apparent that two effects have to be considered in the one-dimensional valve model: partly covered discharge port by the cylinder and the roller, and unsteady flow. In an attempt to describe the first effect, comparison of the transient effective flow and force areas between the full FSI model and the simplified FSI model is presented. For the second effect, unsteady flow and force equations are developed and analyzed, and the steady effective flow and force areas are compared with that of the transient. It is found that if these two effects are negligible, the impact velocity of the valve reed impacting on the retainer will be overestimated. [ABSTRACT FROM PUBLISHER]

Conventional sparse spike deconvolution algorithms that are based on the iterative shrinkage-thresholding algorithm (ISTA) are widely used. The aim of this type of algorithm is to obtain accurate seismic wavelets. When this is not fulfilled, the processing stops being optimum. Using a recurrent neural network (RNN) as deep learning method and applying backpropagation to ISTA, we have developed an RNN-like ISTA as an alternative sparse spike deconvolution algorithm. The algorithm is tested with both synthetic and real seismic data. The algorithm first builds a training dataset from existing well-logs seismic data and then extracts wavelets from those seismic data for further processing. Based on the extracted wavelets, the new method uses ISTA to calculate the reflection coefficients. Next, inspired by the backpropagation through time (BPTT) algorithm, backward error correction is performed on the wavelets while using the errors between the calculated reflection coefficients and the reflection coefficients corresponding to the training dataset. Finally, after performing backward correction over multiple iterations, a set of acceptable seismic wavelets is obtained, which is then used to deduce the sequence of reflection coefficients of the real data. The new algorithm improves the accuracy of the deconvolution results by reducing the effect of wrong seismic wavelets that are given by conventional ISTA. In this study, we account for the mechanism and the derivation of the proposed algorithm, and verify its effectiveness through experimentation using theoretical and real data. [ABSTRACT FROM AUTHOR]

Perinatal asphyxia often results in neonatal cerebral hypoxia-ischemia (HI), which is associated with high mortality and severe long-term neurological deficits in newborns. Currently, there are no effective drugs to mitigate the functional impairments post-HI. Previous studies have shown that fibroblast growth factor 21 (FGF21) has a potential neuroprotective effect against brain injury. However, the effect of FGF21 on neonatal HI brain injury is unclear. In the present study, both in vivo and in vitro models were used to assess whether recombinant human FGF21 (rhFGF21) could exert a neuroprotective effect after HI and explore the associated mechanism. The results showed that the rhFGF21 treatment remarkably reduced the infarct volume, ameliorated the body weight and improved the tissue structure after HI in neonatal rats. In addition, the rhFGF21 treatment lengthened the running endurance times in the rotarod test and decreased the mean escape latencies and increased the number of platform crossings in the Morris water maze test at 21 d post-HI insult. In contrast, the FGFR1 inhibitor PD173074 and PI3K inhibitor LY294002 partially reversed these therapeutic effects. In isolated primary cortical neurons, the rhFGF21 treatment protected primary neurons from oxygen-glucose deprivation (OGD) insult by inhibiting neuronal apoptosis and promoting neuronal survival. Both our in vivo and in vitro results reveal that rhFGF21 could inhibit neuronal apoptosis by activating the PI3K/Akt signaling pathway via FGF21/FGFR1/β-klotho complex formation. Therefore, rhFGF21 may be a promising therapeutic agent for promoting functional recovery after HI-induced neonatal brain injury. • rhFGF21 reduces the brain infarct volume and ameliorates the histological structure. • rhFGF21 improves motor and learning disabilities in rats after hypoxia-ischemia. • rhFGF21 activates the PI3K/Akt pathway via FGFR1/β-klotho post hypoxia-ischemia. • rhFGF21 attenuates OGD-induced primary cortical neuronal death. • rhFGF21 protects neurons against OGD injury by inhibiting neuronal apoptosis. [ABSTRACT FROM AUTHOR]

Melatonin has neuroprotective effects in many diseases, including neonatal hypoxic-ischaemic (HI) brain injury. The purpose of this study was to evaluate the neuroprotective effects of melatonin both in vivo and in vitro and associated molecular mechanisms behind these effects. Postnatal day 7 male and female rat pups were subjected to unilateral HI, melatonin was injected intraperitoneally 1 h before HI and an additional six doses were administered at 24 h intervals. The pups were sacrificed at 24 h and 7 d after HI. Pre-treatment with melatonin significantly reduced brain damage at 7 d after HI, with 15 mg/kg melatonin achieving over 30% recovery in tissue loss compared to vehicle-treated animals. Autophagy and apoptotic cell death as indicated by autophagy associated proteins, cleaved caspase 3 and Tunel staining, was significantly inhibited after melatonin treatment in vivo as well as in PC12 cells. Melatonin treatment also significantly increased the GAP43 in the cortex. In conclusion, melatonin treatment reduced neonatal rat brain injury after HI, and this appeared to be related to inhibiting autophagy as well as reducing apoptotic cell death. [ABSTRACT FROM AUTHOR]

• NBP treatment reduces the brain infarct volume and brain tissue loss. • NBP treatment enhances neuronal rehabilitation, promotes neurite growth and remyelination. • NBP treatment improves long-term neurobehavioral development and prognosis after hypoxia-ischemia. • NBP treatment inhibits endoplasmic reticulum stress-induced cell apoptosis. • NBP treatment alleviates blood-brain barrier disruption. Dl-3-n-butylphthalide (NBP) has been demonstrated to exert neuroprotective effects in experimental models and human patients. This study was performed to assess the therapeutic effects and the underlying molecular mechanisms of NBP in a neonatal hypoxic-ischemic rat model. The results showed that NBP treatment significantly reduced the infarct volume, improved histological recovery, decreased neuronal cell loss, enhanced neuronal cell rehabilitation, promoted neurite growth and decreased white matter injury. In addition, NBP treatment effectively improved long-term neurobehavioral development and prognosis after HI injury. We further demonstrated an inhibitory effect of NBP on endoplasmic reticulum (ER) stress-induced apoptosis, evidenced by reduction in ER stress-related protein expressions (GRP78, XBP-1, PDI and CHOP), decrease in TUNEL-positive cells, down-regulation in pro-apoptosis protein (Bax and cleaved caspase-3), up-regulation in anti-apoptosis protein (Bcl-2). Moreover, NBP exerted a protective effect in blood-brain barrier disruption, which ameliorated brain edema and reduced the degeneration of the tight junction proteins (Occludin and Claudin-5) and adherens junction proteins (P120-Catenin, VE-Cadherin and β-Catenin). Overall, our findings demonstrated that NBP treatment attenuated HI brain injury through inhibiting ER stress-induced apoptosis and alleviating blood-brain barrier disruption in newborn rats. This work provides an effective therapeutic strategy to reduce brain damage and enhance recovery after neonatal HI brain injury. [ABSTRACT FROM AUTHOR]

Neonatal hypoxic-ischemic (HI) brain injury remains a devastating clinical disease associated with high mortality and lifetime disability. Neonatal HI injury damages the architecture of neurovascular unit (NVU), thus, therapy targeting the NVU may provide effective neuroprotection against HI. This study was designed to investigate whether fibroblast growth factor 10 (FGF10) protected the NVU against HI and afforded observable neuroprotection in a rat model of neonatal HI brain injury. The results showed that FGF10 treatment significantly reduced brain damage post HI, characterized by reduction in brain infarct volume and tissue loss. Further interesting findings showed that FGF10 treatment exerted neuroprotective effects on HI brain injury in neonate rats through protecting the NVU against HI, evidenced by inhibition of neuronal cell apoptosis, suppression of gliosis, and amelioration of blood-brain barrier disruption. Collectively, our study indicates that FGF10 treatment exhibits great potential for protecting NVU against HI and attenuates neonatal brain injury, suggesting a potential novel therapeutic agent to this disease. • FGF10 decreases neuronal death via inhibiting neuronal apoptosis • FGF10 attenuates the activation of microglia and astrocytes through modulating TLR4/NF-κB signaling pathway • FGF10 ameliorates blood-brain barrier disruption via reducing tight junction and adherens junction proteins degradation and pericytes loss • FGF10 exerts protective effects on the neurovascular unit in a rat model of neonatal HI brain injury. [ABSTRACT FROM AUTHOR]

Background: To describe the incidence of outborns among very preterm infants (VPIs, <32 weeks of gestation) in Chinese perinatal centers and to examine the association of outborn status with adverse outcomes., Methods: A cohort study enrolling all VPIs admitted to 18 perinatal centers in China from May 1st, 2015 to April 30th, 2018. Neonatal outcomes including rates of discharge against medical advice (DAMA), in-hospital mortality, overall mortality, severe intraventricular hemorrhage (IVH) or periventricular leukomalacia (PVL), sepsis, bronchopulmonary dysplasia (BPD), necrotizing enterocolitis (NEC) and severe retinopathy of prematurity (ROP) were compared between outborn and inborn infants. A multivariate logistic regression model was used to estimate the independent association of outborn status with neonatal outcomes., Results: Among 12,014 VPIs, 1,991 (16.6%) infants were outborn. Outborn infants had lower Apgar scores and higher illness severity score on admission. Mothers of outborn infants were less likely to receive antenatal steroids, prenatal care and caesarean section. The incidence of DAMA (18.0% vs. 12.5%, P<0.001), overall mortality (19.9% vs. 15.8%, P<0.001) and severe brain injury (10.8% vs. 9.1%, P=0.024) of outborn infants were significantly higher than inborn infants. Outborn status was independently associated with increased risks of DAMA (aOR, 1.6; 95% CI: 1.4-1.8), overall-hospital mortality (aOR, 1.3; 95% CI: 1.1-1.5) and severe IVH/PVL (aOR, 1.2; 95% CI: 1.0-1.5)., Conclusions: The incidence of outborn VPIs was high in China. Outborn infants were more likely to be delivered in an uncontrolled situation and were at significantly higher risk of neonatal mortality and severe brain injury compared with inborn infants. Quality improvement efforts are needed to facilitate in-utero transfer of high-risk pregnancies to tertiary centers., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tp-20-232). Dr. Shoo K. Lee serves as an unpaid editorial board member of Translational Pediatrics from Feb 2013 to Jan 2021. The other authors have no conflicts of interest to declare., (2021 Translational Pediatrics. All rights reserved.)

Neonatal hypoxic-ischemic (HI) brain injury is a devastating disease that often leads to death and detrimental neurological deficits. The present study was designed to evaluate the ability of metformin to provide neuroprotection in a model of neonatal hypoxic-ischemic brain injury and to study the associated molecular mechanisms behind these protective effects. Here, we found that metformin treatment remarkably attenuated brain infarct volumes and brain edema at 24 h after HI injury, and the neuroprotection of metformin was associated with inhibition of neuronal apoptosis, suppression of the neuroinflammation and amelioration of the blood brain barrier breakdown. Additionally, metformin treatment conferred long-term protective against brain damage at 7 d after HI injury. Our study indicates that metformin treatment protects against neonatal hypoxic-ischemic brain injury and thus has potential as a therapy for this disease., Competing Interests: CONFLICTS OF INTEREST The authors declare no conflicts of interest.

Hypoxic-ischemic and inflammatory (HII) induces the disruption of blood-brain barrier (BBB) which leads to inflammatory responses and neuronal cell death, resulting in brain secondary damage. Previous studies showed that melatonin produced potent neuroprotective effects in neonatal hypoxic-ischaemic models. However, the relationship between BBB disruption and melatonin in HII was still unclear. The present study therefore investigated the beneficial effects of melatonin on BBB after HII and the underlying mechanisms. HII animal model was conducted by receiving lipopolysaccharide followed by 90 min hypoxia-ischaemia in postnatal day 2 Sprague-Dawley rat pups. Melatonin was injected intraperitoneally 1 h before lipopolysaccharide injection and then once a day for 1 week to evaluate the long-term effects. In this study, we demonstrated that melatonin administration inhibited the disruption of BBB permeability and improved the white matter recovery in HII model rats. Melatonin significantly attenuated the degradation of junction proteins and the neuroprotective role was related to the inhibition of microglial toll-like receptor 4/ nuclear factor-kappa B signaling pathway both in vivo and in vitro. Taken together, our data demonstrated that therapeutic strategies targeting inflammation might be suitable for the therapy of preserving BBB integrity after HII.

Acidic fibroblast growth factor (aFGF) has been shown to exert neuroprotective effects in experimental models and human patients. In this study, we investigated whether aFGF intranasal-treatment protected against neonatal hypoxic-ischaemic brain injury and evaluated the role of endoplasmic reticulum stress. The Rice-Vannucci model of neonatal hypoxic-ischaemic brain injury was used in 7-day-old rats, which were subjected to unilateral carotid artery ligation followed by 2.5 h of hypoxia. Intranasal aFGF or vehicle was administered immediately after hypoxic-ischaemic injury (100 ng/g) and then twice a day for 1 week to evaluate the long-term effects. Here we reported that intranasal-treatment with aFGF significantly reduced hypoxic-ischaemic brain infarct volumes and the protective effects were at least partially via inhibiting endoplasmic reticulum stress. In addition, aFGF exerted long-term neuroprotective effects against brain atrophy and neuron loss at 7-day after injury. Our data indicate that therapeutic strategies targeting endoplasmic reticulum stress may be promising to the treatment of neonatal hypoxic-ischaemic brain injury., Competing Interests: CONFLICTS OF INTEREST The authors declare that they have no competing interests.

Brain injury secondary to birth asphyxia is the major cause of death and long-term disability in newborns. Intranasal drug administration enables agents to bypass the blood-brain barrier (BBB) and enter the brain directly. In this study, we determined whether intranasal basic fibroblast growth factor (bFGF) could exert neuroprotective effects in neonatal rats after hypoxic-ischaemic (HI) brain injury and assessed whether attenuation of endoplasmic reticulum (ER) stress was associated with these neuroprotective effects. Rats were subjected to HI brain injury via unilateral carotid artery ligation followed by 2.5 h of hypoxia and then treated with intranasal bFGF or vehicle immediately after HI injury. We found that the unfolded protein response (UPR) was strongly activated after HI injury and that bFGF significantly reduced the levels of the ER stress signalling proteins GRP78 and PDI. bFGF also decreased brain infarction volumes and conferred long-term neuroprotective effects against brain atrophy and neuron loss after HI brain injury. Taken together, our results suggest that intranasal bFGF provides neuroprotection function partly by inhibiting HI injury-induced ER stress. bFGF may have potential as a therapy for human neonates after birth asphyxia.

Neonatal hypoxic-ischemic brain injury is a devastating disease with limited treatment options. Preventive treatment with resveratrol has indicated to be well tolerated and has lower toxicity in both experimental models and human patients. However, whether resveratrol administration post-hypoxic-ischemic protects against neonatal hypoxic-ischemic injury is not known. Here we reported that post-treatment with resveratrol significantly reduced brain damage at 7-day after the injury. We found that resveratrol reduced the expression levels of key inflammatory factors at the mRNA and protein levels, and at least partially via inhibiting microglia activation. Moreover, resveratrol exerted an anti-apoptotic effect, as assessed by TUNEL staining, and altered the expression of the apoptosis-related genes Bax, Bcl-2 and caspase3. Our data indicate that post-treatment with resveratrol protects against neonatal hypoxic-ischemic brain injury and suggest a promising therapeutic strategy to this disease.