The role of Ca2+ signalling and InsP3R in the pathogenesis of intrahepatic cholestasis of pregnancy.

BACKGROUND: In order to contribute new insights for future prevention and treatment of intrahepatic cholestasis of pregnancy (ICP), and to promote positive pregnancy outcomes, we evaluated serum Ca2+ levels and inositol 1,4,5-trisphosphate receptor (InsP3R) expression in the liver tissue of a rat ICP model. METHODS: After establishing the model by injection of oestradiol benzoate and progesterone into pregnant rats, animals were divided into normal control (n = 5) and ICP model groups (n = 5). The expression of InsP3R protein in the liver, and serum levels of Ca2+, glycocholic acid and bile acid were detected. RESULTS: InsP3R mRNA and protein were significantly lower in the ICP model group compared to the normal group, as determined by qPCR and immunohistochemistry, respectively. Serum enzyme-linked immunosorbent assay results revealed significantly higher levels of glycocholic acid and bile acid in the ICP model group compared to the normal group, while Ca2+ levels were significantly lower. The levers of Ca2+ were significantly and negatively correlated with the levels of glycocholic acid. The observed decrease in Ca2+ was associated with an increase in total bile acids, but there was no significant correlation. CONCLUSIONS: Our results revealed that the expression of InsP3R and serum Ca2+ levels was significantly decreased in the liver tissue of ICP model rats. Additionally, Ca2+ levels were found to be negatively correlated with the level of glycocholic acid.

This study investigated the relationship between serum Ca²⁺ levels, inositol 1,4,5-trisphosphate receptor (InsP3R) expression and intrahepatic cholestasis of pregnancy (ICP) in a rat model. The results indicated a significant decrease in InsP3R expression and Ca²⁺ in the disease group compared to the control group, alongside elevated levels of glycocholic acid and bile acid. The levels of Ca²⁺ exhibited a negative correlation with the levels of glycocholic acid. These findings indicated that the decrease of InsP3R expression and Ca²⁺ levels may be related to the pathogenesis of ICP. The study provides further insight into the treatment of this disease.

DRP1 inhibition-mediated mitochondrial elongation abolishes cancer stemness, enhances glutaminolysis, and drives ferroptosis in oral squamous cell carcinoma.

BACKGROUND: Mitochondrial dynamics play a fundamental role in determining stem cell fate. However, the underlying mechanisms of mitochondrial dynamics in the stemness acquisition of cancer cells are incompletely understood. METHODS: Metabolomic profiling of cells were analyzed by MS/MS. The genomic distribution of H3K27me3 was measured by CUT&Tag. Oral squamous cell carcinoma (OSCC) cells depended on glucose or glutamine fueling TCA cycle were monitored by 13C-isotope tracing. Organoids and tumors from patients and mice were treated with DRP1 inhibitors mdivi-1, ferroptosis inducer erastin, or combination with mdivi-1 and erastin to evaluate treatment effects. RESULTS: Mitochondria of OSCC stem cells own fragment mitochondrial network and DRP1 is required for maintenance of their globular morphology. Imbalanced mitochondrial dynamics induced by DRP1 knockdown suppressed stemness of OSCC cells. Elongated mitochondria increased α-ketoglutarate levels and enhanced glutaminolysis to fuel the TCA cycle by increasing glutamine transporter ASCT2 expression. α-KG promoted the demethylation of histone H3K27me3, resulting in downregulation of SNAI2 associated with stemness and EMT. Significantly, suppressing DRP1 enhanced the anticancer effects of ferroptosis. CONCLUSION: Our study reveals a novel mechanism underlying mitochondrial dynamics mediated cancer stemness acquisition and highlights the therapeutic potential of mitochondria elongation to increase the susceptibility of cancer cells to ferroptosis.

FedDUS: Lung tumor segmentation on CT images through federated semi-supervised with dynamic update strategy.

BACKGROUND AND OBJECTIVE: Lung tumor annotation is a key upstream task for further diagnosis and prognosis. Although deep learning techniques have promoted automation of lung tumor segmentation, there remain challenges impeding its application in clinical practice, such as a lack of prior annotation for model training and data-sharing among centers. METHODS: In this paper, we use data from six centers to design a novel federated semi-supervised learning (FSSL) framework with dynamic model aggregation and improve segmentation performance for lung tumors. To be specific, we propose a dynamically updated algorithm to deal with model parameter aggregation in FSSL, which takes advantage of both the quality and quantity of client data. Moreover, to increase the accessibility of data in the federated learning (FL) network, we explore the FAIR data principle while the previous federated methods never involve. RESULT: The experimental results show that the segmentation performance of our model in six centers is 0.9348, 0.8436, 0.8328, 0.7776, 0.8870 and 0.8460 respectively, which is superior to traditional deep learning methods and recent federated semi-supervised learning methods. CONCLUSION: The experimental results demonstrate that our method is superior to the existing FSSL methods. In addition, our proposed dynamic update strategy effectively utilizes the quality and quantity information of client data and shows efficiency in lung tumor segmentation. The source code is released on (https://github.com/GDPHMediaLab/FedDUS).

MAD-Former: A Traceable Interpretability Model for Alzheimer's Disease Recognition Based on Multi-Patch Attention.

The integration of structural magnetic resonance imaging (sMRI) and deep learning techniques is one of the important research directions for the automatic diagnosis of Alzheimer's disease (AD). Despite the satisfactory performance achieved by existing voxel-based models based on convolutional neural networks (CNNs), such models only handle AD-related brain atrophy at a single spatial scale and lack spatial localization of abnormal brain regions based on model interpretability. To address the above limitations, we propose a traceable interpretability model for AD recognition based on multi-patch attention (MAD-Former). MAD-Former consists of two parts: recognition and interpretability. In the recognition part, we design a 3D brain feature extraction network to extract local features, followed by constructing a dual-branch attention structure with different patch sizes to achieve global feature extraction, forming a multi-scale spatial feature extraction framework. Meanwhile, we propose an important attention similarity position loss function to assist in model decision-making. The interpretability part proposes a traceable method that can obtain a 3D ROI space through attention-based selection and receptive field tracing. This space encompasses key brain tissues that influence model decisions. Experimental results reveal the significant role of brain tissues such as the Fusiform Gyrus (FuG) in AD recognition. MAD-Former achieves outstanding performance in different tasks on ADNI and OASIS datasets, demonstrating reliable model interpretability.

Multifidus lesions: A possible pathological component in patients with low back pain after posterior lumbar surgery.

There are few histological studies on multifidus after lumbar surgery, and it is not clear whether multifidus changes affect the clinical outcome after lumbar surgery. The aim of this study was to investigate the relationship between multifidus changes and clinical outcomes after lumbar surgery. Patients underwent internal fixation removal after lumbar posterior surgery were enrolled. Patients were divided into a low back pain (LBP) group (n = 15) and a non-low back pain (non-LBP) group (n = 10).The Oswestry disability index (ODI) and visual analog scale (VAS) were completed. 18 patients with lumbar fracture surgery were included as the control group. Multifidus morphological changes were observed by hematoxylin and eosin and Masson staining. The expression of TGF-ß1 was observed by immunohistochemistry, immunofluorescence and Western blot. The cross-sectional area (CSA) of the multifidus in the non-LBP group and the control group were greater than those in the LBP group. TGF-ß1 expression and gray value ratio in the non-LBP group and the control group were lower than those in the LBP group. The multifidus CSA and TGF-ß1 expression in multifidus were strongly correlated with ODI and VAS. Patients with LBP after posterior lumbar surgery suffered from atrophy and fibrosis lesions in the multifidus, and the degree of multifidus lesions was closely related to dysfunction and pain, which might be one of the causes of LBP after posterior lumbar surgery.

Acetyl-11-keto-beta-boswellic acid inhibits cell proliferation and growth of oral squamous cell carcinoma via RAB7B-mediated autophagy.

Natural products can overcome the limitations of conventional chemotherapy. Acetyl-11-keto-beta-boswellic acid (AKBA) as a natural product extracted from frankincense, exhibited chemotherapeutic activities in different cancers. However, whether AKBA exerts inhibiting effect of oral squamous cell carcinoma (OSCC) cells growth and the mechanism need to be explored. We attempted to investigate the therapeutic effects of AKBA against OSCC and explore the mechanism involved. Here we attempt to disclose the cell-killing effect of AKBA on OSCC cell lines and try to figure out the specifical pathway. The presence of increase autophagosome and the production of mitochondrial reactive oxygen species were confirmed after the application of AKBA on OSCC cells, and RAB7B inhibition enhanced autophagosome accumulation. Though the increase autophagosome was detected induced by AKBA, autophagic flux was inhibited as the failure fusion of autophagosome and lysosome. Cal27 xenografts were established to verify the role of anti-OSCC cells of AKBA in vivo. Based above findings, we speculate that natural product AKBA suppresses OSCC cells growth via RAB7B-mediated autophagy and may serve as a promising strategy for the therapy of OSCC.

The impact of chemical properties of the solid-liquid-adsorbate interfaces on the entropy-enthalpy compensation involved in adsorption.

Despite extensive studies on the thermodynamic mechanism governing molecular adsorption at the solid-water interface, a comprehensive understanding of the crucial role of interface properties in mediating the entropy-enthalpy compensation during adsorption is lacking, particularly at a quantitative level. Herein, we employed two types of surface models (hydroxyapatite and graphene) along with a series of amino acids to successfully elucidate how distinct interfacial features dictate the delicate balance between entropy and enthalpy variations. The adsorption of all amino acids on the hydroxyapatite surface is an enthalpy-dominated process, where the water-induced enthalpic component of the free energy and the surface-adsorbate electrostatic interaction term alternatively act as the driving force for adsorption in different regions of the surface. Although favorable interactions are observed between amino acids and the graphene surface, the entropy-enthalpy compensation exhibits dependence on the molecular size of the adsorbates. For small amino acids, favorable enthalpy changes predominantly determine their adsorption behavior; however, larger amino acids tend to bind more tightly with the graphene surface, which is thermodynamically dominated by the entropy variations despite the structural characteristics of amino acids. This study reveals specific entropy-enthalpy mechanisms underlying amino acid adsorption at the solid-liquid interface, providing guidance for surface design and synthesis of new biomolecules.

Luteal phase support of intramuscular progesterone associated with lower hypertensive disorders of pregnancy as compared to vaginal progesterone: A cohort study.

OBJECTIVE: To compare the hypertensive disorders of pregnancy (HDP) risk between vaginal and intramuscular (IM) progesterone in programmed frozen-thawed embryo transfer (FET) cycles. METHODS: This was a retrospective cohort study at a tertiary hospital, and only women who achieved ongoing pregnancy after programmed FET between January 2018 and June 2022 were included. Women with chronic hypertension before pregnancy or with history of gestational hypertension or pre-eclampsia in previous pregnancies were excluded. All women were divided into IM progesterone or vaginal progesterone groups according to the route of progesterone supplementation. Follow-up information on obstetric complications and neonatal outcomes were obtained by telephonic interviews. The primary outcome was HDP. Association between routes of progesterone supplementation and HDP was assessed by subgroup analysis and multivariable logistic regression. RESULTS: A total of 5891 programmed FET cycles (3196 IM progesterone cycles and 2695 vaginal progesterone cycles) were included in the analysis. The prevalence of HDP in the IM progesterone group was significantly lower than that of the vaginal progesterone group (6.54% vs 9.17%, P < 0.001). Therein, the prevalence of gestational hypertension (3.57% vs 4.94%, P = 0.009) and pre-eclampsia (2.97% vs 4.23%, P = 0.009) in the IM progesterone group were all significantly lower as compared to the vaginal progesterone group. According to subgroup analysis, IM progesterone was associated with lower HDP risk in all subgroups. The logistic regression analysis showed that the IM progesterone cycles were associated with lower risk of HDP compared to vaginal progesterone cycles (adjusted odds ratio 0.66, 95% CI: 0.54-0.80, P < 0.001). CONCLUSION: Among women undergoing programmed FET cycles, progesterone supplementation with IM progesterone was associated with reduced HDP risk compared to vaginal progesterone.

Physiological indices and liver gene expression related to glucose supply in Brandt's vole (Lasiopodomys brandtii) exhibit species- and oxygen concentration-specific responses to hypoxia.

Brandt's vole (Lasiopodomys brandtii) is a species with hypoxia tolerance, and glucose serves as the primary energy substrate under hypoxia. However, the glucose supply in Brandt's voles under hypoxia has not been studied. This study aimed to investigate characteristics in physiological indices and liver gene expression associated with glucose supply in Brandt's voles under hypoxia. Serum glucose of Brandt's voles remained stable under 10% O2, increased under 7.5% O2, and decreased under 5% O2. Serum lactate increased under 10% O2, decreased under 7.5% O2, increased at 6 h and decreased at 12 h under 5% O2. Liver glycogen increased under 10% O2, remained constant under 7.5% O2, and reduced under 5% O2. Pepck and G6pase expression associated with gluconeogenesis decreased under 10% O2, while Pepck expression decreased and G6pase expression increased under 7.5% and 5% O2. Regarding genes related to glycogen metabolism, Gys expression decreased at all oxygen concentrations, Phk expression increased under 5% O2, and Gp expression increased under 7.5% and 5% O2. The alterations in glucose, lactate, liver glycogen, and gene expression related to glycogenolysis in Kunming mice (Mus musculus, control species) are similar to discovery of Brandt's voles under 7.5% O2, but gene expression involved in gluconeogenesis and glycogen synthesis increased. The findings suggest that Brandt's voles are more tolerant to hypoxia than Kunming mice, and their physiological indices and liver gene expression related to glucose supply exhibit species- and oxygen concentration-specific responses to hypoxia. This research offers novel insights for studying hypoxia tolerance of Brandt's voles.

Emerging roles of circular RNAs in the invasion and metastasis of head and neck cancer: Possible functions and mechanisms.

Head and neck cancer (HNC) is the seventh most prevalent malignancy worldwide in 2020. Cancer metastasis is the main cause of poor prognosis in HNC patients. Recently, circular RNAs (circRNAs), initially thought to have no biological function, are attracting increasing attention, and their crucial roles in mediating HNC metastasis are being extensively investigated. Existing studies have shown that circRNAs primarily function through miRNA sponges, transcriptional regulation, interacting with RNA-binding proteins (RBPs) and as translation templates. Among these functions, the function of miRNA sponge is the most prominent. In this review, we summarized the reported circRNAs involved in HNC metastasis, aiming to elucidate the regulatory relationship between circRNAs and HNC metastasis. Furthermore, we summarized the latest advances in the epidemiological information of HNC metastasis and the tumor metastasis theories, the biogenesis, characterization and functional mechanisms of circRNAs, and their potential clinical applications. Although the research on circRNAs is still in its infancy, circRNAs are expected to serve as prognostic markers and effective therapeutic targets to inhibit HNC metastasis and significantly improve the prognosis of HNC patients.

[Alzheimer's disease classification based on nonlinear high-order features and hypergraph convolutional neural network].

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that damages patients' memory and cognitive abilities. Therefore, the diagnosis of AD holds significant importance. The interactions between regions of interest (ROIs) in the brain often involve multiple areas collaborating in a nonlinear manner. Leveraging these nonlinear higher-order interaction features to their fullest potential contributes to enhancing the accuracy of AD diagnosis. To address this, a framework combining nonlinear higher-order feature extraction and three-dimensional (3D) hypergraph neural networks is proposed for computer-assisted diagnosis of AD. First, a support vector machine regression model based on the radial basis function kernel was trained on ROI data to obtain a base estimator. Then, a recursive feature elimination algorithm based on the base estimator was applied to extract nonlinear higher-order features from functional magnetic resonance imaging (fMRI) data. These features were subsequently constructed into a hypergraph, leveraging the complex interactions captured in the data. Finally, a four-dimensional (4D) spatiotemporal hypergraph convolutional neural network model was constructed based on the fMRI data for classification. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database demonstrated that the proposed framework outperformed the Hyper Graph Convolutional Network (HyperGCN) framework by 8% and traditional two-dimensional (2D) linear feature extraction methods by 12% in the AD/normal control (NC) classification task. In conclusion, this framework demonstrates an improvement in AD classification compared to mainstream deep learning methods, providing valuable evidence for computer-assisted diagnosis of AD.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

Background: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented. Methods: After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism. Results: The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism. Conclusion: This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.

ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images.

Cardiovascular disease (CVD) accounts for about half of non-communicable diseases. Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed tomography angiography (CTA) is one of the widely used noninvasive imaging modalities in coronary artery diagnosis due to its superior image resolution. Clinically, segmentation of coronary arteries is essential for the diagnosis and quantification of coronary artery disease. Recently, a variety of works have been proposed to address this problem. However, on one hand, most works rely on in-house datasets, and only a few works published their datasets to the public which only contain tens of images. On the other hand, their source code have not been published, and most follow-up works have not made comparison with existing works, which makes it difficult to judge the effectiveness of the methods and hinders the further exploration of this challenging yet critical problem in the community. In this paper, we propose a large-scale dataset for coronary artery segmentation on CTA images. In addition, we have implemented a benchmark in which we have tried our best to implement several typical existing methods. Furthermore, we propose a strong baseline method which combines multi-scale patch fusion and two-stage processing to extract the details of vessels. Comprehensive experiments show that the proposed method achieves better performance than existing works on the proposed large-scale dataset. The benchmark and the dataset are published at https://github.com/XiaoweiXu/ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-CT.

Effect of place-based policy on regional economic growth: A quasi-natural experiment from China's Old Revolutionary Development Program.

Triggering economic growth is a requirement to promote human welfare and realize sustainable development in many developing countries. However, place-based policies' impact on economic growth is debatable, and its underlying mechanism is unknown. China's Old Revolutionary Development Program (ORDP) is a large-scale and novel type of place-based policy targeted at undeveloped regions in China. We evaluate the effect of ORDP on economic growth by employing a time-varying difference-in-differences model and further explore the potential mechanisms and heterogeneity effects. VIIRS/DNB nightlight data is used to measure economic growth. We find that ORDP can significantly promote economic growth by 4.0% and the result is still robust after several tests. Mechanism analysis shows that ORDP can improve economic growth through government intervention, industrial structure optimization, and information infrastructure construction. Heterogeneity analysis indicates that the ORDP performs better on economic growth in central Chinese cities and high-economy cities. At the same time, our paper provides three practical suggestions for stimulating economic growth in ORDP, which can be enlightening for other developing countries.

The role of place-based policies on carbon emission: A quasi-natural experiment from China's old revolutionary development program.

The effectiveness of place-based policies on carbon emission is controversial, and particularly the mechanism behind its effectiveness is unknown. We treat China's Old Revolutionary Development Program (ORDP)- a large-scale and novel type of place-based policy targeted at undeveloped regions, as a natural experiment to estimate ORDP's impact on carbon emission. Employing the panel data of 110 prefecture-level cities in China from 2010 to 2019, we perform a time-varying difference-in-differences (DID) study and discover that ORDP leads to an average of 26.7% increase in carbon emission and this effect takes a period to emerge and is not sustainable in the long term. Three mechanisms that may result in such impact are that ORDP improves economic development, changes industrial structure, and decreases technological progress. Further heterogeneity analysis indicates that ORDP results in a greater increased impact on carbon emission in old revolutionary cities that are located in western China compared to those located in central and eastern China.

The origin and evolution of emerged swine acute diarrhea syndrome coronavirus with zoonotic potential.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered alphacoronavirus with zoonotic potential that causes diarrhea and vomiting mainly in piglets. Having emerged suddenly in 2017, the prevailing opinion is that the virus originated from HKU2, an alphacoronavirus whose primary host is bats, and at some unknown point achieved interspecies transmission via some intermediate. Here, we further explore the evolutionary history and possible cross-species transmission event for SADS-CoV. Coevolutionary analysis demonstrated that HKU2 may have achieved host switch via SADS-related (SADSr)-CoV, which was isolated from the genus Rhinolophus in 2017. SADS-CoV, HKU2, and SADSr-CoV share similar codon usage patterns and showed a lower tendency to use CpG, which may reflect a method of immune escape. The analyses of virus-host coevolution and recombination support SADSr-CoV is the direct source of SADS-CoV that may have undergone recombination events during its formation. Structure-based spike glycoprotein variance analysis revealed a more nuanced evolutionary pathway to receptor recognition for host switch. We did not find a possible positive selection site, and the dN/dS of the S gene was only 0.29, which indicates that the current SADS-CoV is slowly evolving. These results provide new insights that may help predict future cross-species transmission, and possibly surveil future zoonotic outbreaks and associated public health emergencies.

Hormone replacement treatment regimen is associated with a higher risk of hypertensive disorders of pregnancy in women undergoing frozen-thawed embryo transfer.

Introduction: In frozen-thawed embryo transfer (FET) cycles, hormone replacement treatment (HRT) was associated with a higher risk of hypertensive disorders of pregnancy (HDP) compared with natural cycles (NC). Multiple pregnancy was a risk factor for HDP and several studies did not conduct subgroup analysis of singleton pregnancy and multiple pregnancy. Objective: To investigate whether HRT regimen could be a risk factor for HDP in women undergoing FET cycles in singleton and twin pregnancies. Methods: A retrospective cohort study at a tertiary hospital, including a total of 9120 women who underwent FET and achieved ongoing pregnancy; 7590 patients underwent HRT-FET and 1530 NC-FET. The main outcome was HDP. HDP were analyzed for singleton and twin pregnancies, respectively. Results: In the singleton pregnancy, the risk of HDP in the HRT-FET group was significantly higher than that in the NC-FET group (6.21% vs. 4.09%; P=0.003). After adjusting for female age oocyte pick up, female age at FET and body mass index (BMI), HRT was found as a risk factor for HDP (adjusted odds ration [aOR]: 1.43; 95% confidence interval [CI]: 1.07 to 1.91; P=0.017). In the multiple pregnancy, the risk of HDP in the HRT-FET and NC-FET groups was similar. Conclusion: HRT was associated with a higher risk of HDP in women who underwent FET and achieved singleton pregnancy.

Changes in gene expression and enzyme activity related to glucose metabolism in the livers of Brandt's voles (Lasiopodomys brandtii) exposed to hypoxia.

Brandt's vole (Lasiopodomys brandtii) is a hypoxia-tolerant species, and the metabolic characteristics of hypoxia-tolerant species have become a focus of recent research. However, insights into the anaerobic and aerobic metabolism of the livers of Brandt's voles under hypoxia remain limited. In this study, Brandt's voles and hypoxia-intolerant Kunming mice (Mus musculus, control species) were exposed to hypoxia conditions (Brandt's voles, 10% and 7.5% O2; Kunming mice, 10% O2) for 24 h, and changes in gene expression and enzyme activity related to anaerobic and aerobic metabolism in the livers were evaluated. Phosphofructokinase 1 (PFK1), phosphofructokinase 2 (PFK2), pyruvate kinase muscle (PKM), hexokinase 2 (HK2), and lactate dehydrogenase (LDH) related to anaerobic metabolism in the livers of Brandt's voles were increased under 7.5% O2. Regarding gene expression and enzyme activity for aerobic metabolism in Brandt's voles under 7.5% and 10% O2, pyruvate dehydrogenase kinase 1 (PDK1) expression was up-regulated, and succinate dehydrogenase (SDH) activity was decreased. In the livers of Kunming mice, gene expression related to anaerobic and aerobic metabolism was increased at the late stage of 10% O2, and SDH activity was enhanced at 6 h and reduced at 18 h. In addition, PFK1,PKM, PDK1 expression and SDH activity in Brandt's voles were significantly correlated with HIF-1a expression. PFK1, PKM, LDHand PDK1 expression in Kunming mice were significantly correlated with HIF-1a expression. These findings indicate that the livers of Brandt's voles have a certain tolerance to hypoxia, and metabolic changes play important roles in hypoxia tolerance.

Quantifying the Effectiveness of Environmental Regulations on Green Total Factor Productivity: Evidence Based on China's Environmental Protection Interview Program.

The effectiveness of environmental regulations on green total factor productivity (GTFP) is controversial, and the mechanisms of the relationship between environmental regulation and GTFP are unknown. In this article, we take advantage of the Environmental Protection Interview (EPI) program-the harshest environmental monitoring program in Chinese history-to carry out a natural experiment to estimate the effect of environmental regulation on GTFP. Applying a time-varying difference-in-differences model based on city panel data from 2003 to 2018 in China, we determined that the EPI can lead to an average GTFP promotion of 35.6%, but the effect of the EPI is not consistent in the long term. A heterogeneity analysis documented that the effect of the EPI on GTFP is more significant in cities with low initial GTFP levels and low economic levels. A mechanism analysis showed that the EPI increases GTFP, basically, through technical creativity and industrial structure upgrading.