Prediction of Subsequent Vertebral Fracture After Acute Osteoporotic Fractures from Clinical and Paraspinal Muscle Features.

To construct a nomogram based on clinical factors and paraspinal muscle features to predict vertebral fractures occurring after acute osteoporotic vertebral compression fracture (OVCF). We retrospectively enrolled 307 patients with acute OVCF between January 2013 and August 2022, and performed magnetic resonance imaging of the L3/4 and L4/5 intervertebral discs (IVDs) to estimate the cross-sectional area (CSA) and degree of fatty infiltration (FI) of the paraspinal muscles. We also collected clinical and radiographic data. We used univariable and multivariable Cox proportional hazards models to identify factors that should be included in the predictive nomogram. Post-OVCF vertebral fracture occurred within 3, 12, and 24 months in 33, 69, and 98 out of the 307 patients (10.8%, 22.5%, and 31.9%, respectively). Multivariate analysis revealed that this event was associated with percutaneous vertebroplasty treatment, higher FI at the L3/4 IVD levels of the psoas muscle, and lower relative CSA of functional muscle at the L4/5 IVD levels of the multifidus muscle. Area under the curve values for subsequent vertebral fracture at 3, 12, and 24 months were 0.711, 0.724, and 0.737, respectively, indicating remarkable accuracy of the nomogram. We developed a model for predicting post-OVCF vertebral fracture from diagnostic information about prescribed treatment, FI at the L3/4 IVD levels of the psoas muscle, and relative CSA of functional muscle at the L4/5 IVD levels of the multifidus muscle. This model could facilitate personalized predictions and preventive strategies.

Fatty Infiltration of Multifidus Muscles: An Easily Overlooked Risk Factor for the Severity of Osteoporotic Vertebral Fractures.

OBJECTIVES: Osteoporotic vertebral fractures (OVFs) are a critical public health concern requiring urgent attention, and severe OVFs impose substantial health and economic burdens on patients and society. Analysis of the risk factors for severe OVF is imperative to actively prevent the occurrence of this degenerative disorder. This study aimed to investigate the risk factors associated with the severity of OVF, with a specific focus on changes in the paraspinal muscles. METHODS: A total of 281 patients with a first-time single-level acute OVF between January 2016 and January 2023 were enrolled in the study. Clinical and radiological data were collected and analyzed. The cross-sectional area (CSA) and degree of fatty infiltration (FI) of the paraspinal muscles, including the multifidus muscles (MFMs), erector spinae muscles (ESMs), and psoas major muscles (PSMs), were measured by magnetic resonance imaging (MRI) of the L4/5 intervertebral discs. According to the classification system of osteoporotic fractures (OF classification) and recommended treatment plan, OVFs were divided into a low-grade OF group and a high-grade OF group. Univariate and multivariate logistic regression analyse s were performed to identify risk factors associated with the severity of OVF. RESULTS: Ninety-eight patients were included in the low-grade OF group, and 183 patients were included in the high-grade OF group. Univariate analysis revealed a significantly higher incidence of a high degree of FI of MFMs (OR = 1.71, p = 0.002) and ESMs (OR = 1.56, p = 0.021) in the high-grade OF group. Further multivariate logistic regression analysis demonstrated that a high degree of FI of the MFMs (OR = 1.71, p = 0.002) is an independent risk factor for the severity of OVF. CONCLUSION: A high degree of FI of the MFMs was identified as an independent risk factor for the severity of OVF. Decreasing the degree of FI in the MFMs might lower the incidence of the severity of OVF, potentially reducing the necessity for surgical intervention in OVF patients.

Lycorine eliminates B-cell acute lymphoblastic leukemia cells by targeting PSAT1 through the serine/glycine metabolic pathway.

B-cell acute lymphoblastic leukemia (B-ALL) has been confirmed as the most common malignant hematologic neoplasm among children. A novel antitumor mechanism of lycorine was elucidated in this study. As revealed by the result of this study, lycorine significantly inhibited the growth and proliferation of REH and NALM-6 and induced their apoptosis. The result of the RNA-seq analysis suggested that lycorine targeted PSAT1 of serine/glycine metabolism in B-ALL cells. As indicated by the result of the GSEA analysis, the genes enriched in the amino acid metabolic pathways were down-regulated by lycorine. As revealed by the results of ectopic expression, shRNA knockdown assays, and further liquid-phase tandem mass spectrometry (LC-MS) analysis, lycorine reduced serine/glycine metabolites by down-regulating PSAT1, further disrupting carbon metabolism and eliminating B-ALL cells. Furthermore, lycorine showed a synergistic effect with cytarabine in ALL treatments. Lastly, lycorine significantly down-regulated leukemia progression in the cell line-derived xenograft (CDX) model. In brief, this study has suggested for the first time that lycorine is a promising anti-ALL drug, and a novel amino acid metabolism-associated property of lycorine was identified.

Driving technology factors of carbon emissions: Theoretical framework and its policy implications for China.

Empirical studies have widely examined the driving factors and methods to achieve a carbon peak; however, they seldom construct a theoretical framework and ignore the potential heterogeneity in technology. The most notable controversy is technology's different roles in carbon emissions. This study proposes an integrated theoretical framework considering the evolution of carbon emissions and presents the conditions for achieving a carbon peak. This framework shows that if the positive role of eco-friendly technology in decreasing carbon emissions is larger than the negative role of production-oriented technology in increasing carbon emissions; thus, carbon emissions do not increase (i.e. carbon peak). Additionally, this framework addresses the controversy concerning the effect of technology on carbon emissions. Our empirical results from a city-level panel dataset show that China is still moving towards achieving carbon emission reduction. Analysis of the driving mechanism reveals that production-oriented technology increases carbon emissions by increasing the production scale, consequently demanding more energy and emitting more carbon dioxide.

How the energy technology influences the total factor of energy efficiency?: evidence from China.

Technological progress is of great importance to total-factor energy efficiency (TFEE). However, previous research has not narrowed technological progress into the energy field, generating rough and ambiguous empirical evidence for policymakers. In addition, technological progress is often discussed from a conventional perspective as a whole, ignoring its heterogeneity and spillover effect between regions. This study applies the stock of energy patents to reflect the effect of technological progress in the energy field on TFEE at first. The dynamic models are then employed to investigate if and how technological progress influences TFEE from the conventional and spatial perspectives for China's over the period of 2000-2016. The conventional analysis shows that energy technology is of great importance to TFEE. However, the creation-type of technology coming from businesses specifically is shown to have more success in enhancing TFEE than other types of energy technology. Further evidence coming from the spatial econometrics demonstrates that technology spillovers across regions are rather common and have significant effects on TFEE.

[Construction of Nalm6-Cas9 Cell Line for Genome-Wide Translocation Sequencing].

OBJECTIVE: In order to conduct high-throughput genome-wide translocation sequencing based on CRISPR/Cas9, Nalm6-cas9 monoclonal cell line expressing Cas9 protein was constructed by lentivirus transduction. METHODS: Lentiviral vectors LentiCas9-Blast, pSPAX2, and pMD2.G were used to co-transfect HEK293T cells to obtain recombinant lentivirus. After Nalm6 cells were infected with the recombinant lentivirus, the cells were screened by Blasticidin, and multiple monoclonal cell lines expressing Cas9 protein were obtained by limited dilution. Western blot was used to detect the expression level of Cas9 protein in monoclonal cell lines, and cell count analysis was used to detect the proliferation activity of monoclonal cell lines. LentiCRISPRV2GFP-Δcas9, LentiCRISPRV2GFP-Δcas9-AF4, LentiCRISPRV2GFP-Δ cas9-MLL plasmids were constructed, and transfected with pSPAX2 and pMD2.G, respectively. T vector cloning was used to detect the function of Cas9 protein in Nalm6-Cas9 monoclonal cell line infected with virus. RESULTS: Western blot showed that Nalm6-Cas9_1-6 monoclonal cell line had high expression of Cas9 protein. Cell count analysis showed that high expression of Cas9 protein in Nalm6-Cas9_1-6 monoclonal cell line did not affect cell proliferation activity. The Nalm6-Cas9_1-6 monoclonal cell line had high cleavage activity, and the editing efficiency of AF4 and MLL genes was more than 90% which was determined by T vector cloning. CONCLUSION: Nalm6-Cas9_1-6 monoclonal cell line stably expressing highly active Cas9 protein was obtained, which provided a basis for exploring the translocation of MLL in therapy-related leukemias based on CRISPR/Cas9 genome-wide high-throughput genome-wide translocation sequencing.

The heterogeneous impacts of Sino-African trade relations on carbon intensity in Africa.

Studies on the environmental impacts of China-African trade relations are scarce. To fill the gap, this research examines the effects of Sino-African trade relations on carbon dioxide (CO2) emissions intensity in Africa, employing panel quantile regression for 39 African countries over the period of 1992-2015. The results indicate that imports have a negative and significant effect on CO2 emissions intensity across all quantile distributions, whereas exports have a positive and significant effect, except at the 25th and 35th quantiles. The findings also confirm the inverted U-shaped environmental Kuznets curve hypothesis, particularly for countries at higher emissions points. The study also demonstrates that urbanisation and energy intensity positively affect CO2 intensity, while the effect of foreign direct investment is negative and significant, confirming the pollution halo hypothesis. Finally, policy implications are presented based on the findings of the study.

MTA1-mediated RNA m6 A modification regulates autophagy and is required for infection of the rice blast fungus.

In eukaryotes, N6 -methyladenosine (m6 A) is abundant on mRNA, and plays key roles in the regulation of RNA function. However, the roles and regulatory mechanisms of m6 A in phytopathogenic fungi are still largely unknown. Combined with biochemical analysis, MeRIP-seq and RNA-seq methods, as well as biological analysis, we showed that Magnaporthe oryzae MTA1 gene is an orthologue of human METTL4, which is involved in m6 A modification and plays a critical role in autophagy for fungal infection. The Δmta1 mutant showed reduced virulence due to blockage of appressorial penetration and invasive growth. Moreover, the autophagy process was severely disordered in the mutant. MeRIP-seq identified 659 hypomethylated m6 A peaks covering 595 mRNAs in Δmta1 appressoria, 114 m6 A peaks was negatively related to mRNA abundance, including several ATG gene transcripts. Typically, the mRNA abundance of MoATG8 was also increased in the single m6 A site mutant ∆atg8/MoATG8A982C , leading to an autophagy disorder. Our findings reveal the functional importance of the m6 A methylation in infection of M. oryzae and provide novel insight into the regulatory mechanisms of plant pathogenic fungi.

Endocytic protein Pal1 regulates appressorium formation and is required for full virulence of Magnaporthe oryzae.

Endocytosis plays key roles during infection of plant-pathogenic fungi, but its regulatory mechanisms are still largely unknown. Here, we identified a putative endocytosis-related gene, PAL1, which was highly expressed in appressorium of Magnaporthe oryzae, and was found to be important for appressorium formation and maturation. Deletion of PAL1 significantly reduced the virulence of M. oryzae due to defects in appressorial penetration and invasive growth in host cells. The Pal1 protein interacted and colocalized with the endocytosis protein Sla1, suggesting it is involved in endocytosis. The Δpal1 mutant was significantly reduced in appressorium formation, which was recovered by adding exogenous cAMP and 3-isobutyl-1-methylxanthine (IBMX). Moreover, the phosphorylation level of Pmk1 in Δpal1 was also reduced, suggesting Pal1 functions upstream of both the cAMP and Pmk1 signalling pathways. As a consequence, the utilization of glycogen and lipid, appressorial autophagy, actin ring formation, localization of septin proteins, as well as turgor accumulation were all affected in the Δpal1 mutant. Taken together, Pal1 regulates cAMP and the Pmk1 signalling pathway for appressorium formation and maturation to facilitate infection of M. oryzae.

Green research and development activities and SO2 intensity: an analysis for China.

Carrying out domestic research and development (R&D) activities can improve environmental performance. However, extant studies have not conclusively indicated that R&D activities in all energy fields lead to a reduction in the SO2 intensity. SO2 intensity is defined as the ratio of SO2 emissions to the GDP. Hence, green R&D activities are required. However, the strong heterogeneity between green R&D activities could have distinctive economic consequences. Thus, it is imperative to study the heterogeneity of green R&D activities on SO2 intensity. Moreover, previous studies have ignored regional differences. Although overlooked in the literature, a technology's adsorptive ability could be a key determinant of the effects of green R&D activities on SO2 intensity. Based on a linear analysis of China's provincial data over 2000-2016, we show that green R&D activities are instrumental in reducing SO2 intensity. Different green R&D activities have distinct goals and contrasting statistical effects on SO2 intensity. The empirical results show that the impact of green R&D activities on SO2 intensity differs by region. Lastly, it is proposed that green R&D activity effects on SO2 intensity are nonlinear by analysing a technology's adsorptive ability.

Impact of energy technology and structural change on energy demand in China.

Facing significant pressure from growing energy demand, China needs to identify specific, effective, and targeted policies that can effectively control this demand. In the past, both technological progress and structural change have been shown to reduce energy demand. However, extant studies on this lack sufficient evidence to support effective policies as these look broadly at technological progress and do not narrow this to the energy field alone. Moreover, heterogeneity in energy technology along with internal changes in specific industries have been overlooked. To address these gaps, this study investigates the effects of energy technologies and structural change on China's energy demand. Using a provincial panel dataset from 2000 to 2016, the results show that although energy technological progress is effective in controlling demand, different technologies offer significantly different results: utilitarian energy technologies, focused on energy conversation, are more effective than technologies aimed at energy substitutions. In addition, technologies developed by enterprises show a significant and positive effect on energy demand, while those developed by higher education institutions and individuals do not. Analysis of the regions indicates some significant regional differences as well. The implication is that China should design energy policies that support funding for enterprises developing utility-focused energy technologies.

Decreasing China's carbon intensity through research and development activities.

Research and development (R&D) activities are frequently undertaken as a powerful means to improve a country's environmental performance. However, previous studies examine R&D activities as a whole, and thus do not provide detailed information, such as the carbon intensity reduction of individual actors or stages. In addition, factors that affect regional capacity for absorbing technology (absorptive capacity) are important to influence the role of R&D in carbon intensity, but they have largely been ignored in the literature. In this study, we investigate the impacts of domestic R&D on carbon intensity by classifying R&D into three stages and three actors. The results derived from a Chinese provincial panel dataset from 2000 to 2016 indicate that domestic R&D is effective for improving carbon intensity. R&D at different stages and involving different actors have statistically different impacts on carbon intensity. Further analysis using the panel threshold model provides new evidence that the nexus between carbon intensity and domestic R&D is nonlinear. Technology absorptive capacity, which is denoted by the full-time equivalent of R&D personnel, can alleviate the negative role of R&D in increasing carbon intensity and strengthen the positive effect of R&D on decreasing carbon intensity. According to the empirical evidence, some insightful policy implications for China to decrease the carbon intensity are presented.

Effect of technological progress on carbon emissions: New evidence from a decomposition and spatiotemporal perspective in China.

The continuously increasing carbon emissions have become a significant hurdle for global sustainable development. Technological progress is considered essential for controlling carbon emissions. However, previous literature has analyzed technological progress as a whole, largely ignoring its spatial spillovers. Therefore, our understanding of how technological progress influences carbon emissions is still limited. To fill this gap, we conduct an in-depth analysis of the effect of technological progress regarding carbon emissions by introducing a new framework that combines the slacks-based measure of the Malmquist-Luenberger index and the spatial dynamic model. Employing a Chinese provincial panel dataset for 2000-2016 as a case study, the conventional analysis indicates that both technological progress and its components have not played a significant role in decreasing carbon emissions. A further analysis using the spatial dynamic model suggests that the technological progress of neighbouring regions plays a significant role in reducing carbon emissions. Moreover, the effect of efficiency change is stronger than that of technical change, which provides new evidence on how technological progress influences carbon emissions.

Determining the factors driving China's industrial energy intensity: Evidence from technological innovation sources and structural change.

The question of how to reduce energy intensity has been a hot issue of social concern. However, there is lack of detailed information from the perspective of technological innovation sources and structural change for policy consideration. To better understand the influence of different technological innovation sources and structural change on industrial energy intensity, this paper applies both linear and non-linear methods of empirical analysis. The conventional linear regression analysis suggests that indigenous research and development (R&D) exerts the most control on energy intensity reduction. Technology acquisitions, both domestically and internationally, have a significant impact on industrial energy intensity. Increases in the proportion of state-owned enterprises within industry and the expansion of the industrial sectors both have a negative effect on energy intensity reduction, but improving the entry level of foreign enterprises can reduce energy intensity. Further, a dynamic panel threshold model indicates that effects of different technological innovation sources and structural change on industrial energy intensity are nonlinear. These findings indicate that increasing R&D inputs and promoting coordinated development between different R&D activities, in addition to adjusting ownership structure, are of great significance for controlling industrial energy intensity.

GPI7-mediated glycosylphosphatidylinositol anchoring regulates appressorial penetration and immune evasion during infection of Magnaporthe oryzae.

Glycosylphosphatidylinositol (GPI) anchoring plays key roles in many biological processes by targeting proteins to the cell wall; however, its roles are largely unknown in plant pathogenic fungi. Here, we reveal the roles of the GPI anchoring in Magnaporthe oryzae during plant infection. The GPI-anchored proteins were found to highly accumulate in appressoria and invasive hyphae. Disruption of GPI7, a GPI anchor-pathway gene, led to a significant reduction in virulence. The Δgpi7 mutant showed significant defects in penetration and invasive growth. This mutant also displayed defects of the cell wall architecture, suggesting GPI7 is required for cell wall biogenesis. Removal of GPI-anchored proteins in the wild-type strain by hydrofluoric acid (HF) pyridine treatment exposed both the chitin and ß-1,3-glucans to the host immune system. Exposure of the chitin and ß-1,3-glucans was also observed in the Δgpi7 mutant, indicating GPI-anchored proteins are required for immune evasion. The GPI anchoring can regulate subcellular localization of the Gel proteins in the cell wall for appressorial penetration and abundance of which for invasive growth. Our results indicate the GPI anchoring facilitates the penetration of M. oryzae into host cells by affecting the cell wall integrity and the evasion of host immune recognition.

The influences of openness on China's industrial CO2 intensity.

As a main cause of global warming, carbon emissions have received growing concerns of Chinese government. As the main sources of carbon emissions, industrial sectors account for approximately 70% of China's total emissions. In this study, the effect of openness involving foreign direct investment, together with import and export on the industrial CO2 intensity, is comprehensively analyzed from the technology spillover perspective. Employing a panel dataset of 34 industrial sectors for the period of 2000-2010, linear regression analysis by fixed effects, the feasible generalized least squares estimator, and the Driscoll-Kraay estimator are employed. The estimation results indicate that the openness is conducive to low-carbon development except export. A further investigation conducted by employing the panel threshold model suggests that the influences of openness on the industrial CO2 intensity are dependent on the specific characteristics of the industrial sectors, such as the domestic innovation and the level of foreign investment entering in China's industrial sectors. These findings allow the relevant policy makers to carry out insightful policies aimed at pursuing low-CO2 intensity by considering the characteristics and situations of the local absorptive ability.

The role of domestic R&D activities played in carbon intensity: Evidence from China.

Most of the existing empirical studies exploring the role of domestic research and development (R&D) played in carbon intensity has confirmed that domestic R&D activities can effectively reduce carbon intensity. Unfortunately, the heterogeneity of R&D activities was ignored and the effect of domestic R&D on carbon intensity was discussed homogenously, that is, as a whole. Since R&D activities can be distinguished from stages and actors, we cannot obtain additional details such as the stages of R&D activities influencing carbon intensity. Additionally, regional differences were neglected. With these gaps in mind, the roles of R&D activities played in carbon intensity are deeply investigated by classifying them into different stages and actors. The empirical results based on a unique panel dataset from 2000 to 2016 imply that R&D can reduce carbon intensity and that carbon intensity is affected by R&D activities depending on its different stages and actors. The major positive role of R&D activities played in decreasing carbon intensity is generated through the activities at the experimental and developmental stages and industrial enterprises. Further analysis of China's regional carbon intensity also suggests that policymakers should consider regional characteristics.

Determining the factors driving energy demand in the Sichuan-Chongqing region: an examination based on DEA-Malmquist approach and spatial characteristics.

Since the "China Western Development" plan was initiated in 2000, the Sichuan-Chongqing region has experienced rapid economic growth, especially in the energy segment. However, energy shortage and environmental degradation currently pose a significant hurdle for sustainable development in this region. In the existing literature on factors driving the energy demand, the effect of technological progress on energy demand is discussed as a whole, but few papers have investigated the effect of technological progress from the perspective of its components. Additionally, existing studies have neglected the temporal and spatial aspect of energy demand, thereby generating biased and unreasonable results. Correspondingly, in the current study, the factors driving the per capita energy demand in the Sichuan-Chongqing region over the 2005-2016 period were, to the best of our knowledge, explored for the first time by employing the data envelopment analysis-Malmquist method and spatial dynamic panel model concurrently. The empirical results suggest that an improvement in total factor productivity (TFP) plays a positive but insignificant role in decreasing energy demand. Additionally, there is clear evidence that the effect of TFP on energy demand primarily emerges through spatial spillover effects and their components.

The effects of indigenous R&D activities on China's energy intensity: A regional perspective.

One of the most efficient and effective ways to cut energy intensity is through an increase in indigenous R&D activities. In the existing literature on the nexus of indigenous R&D and energy intensity, indigenous R&D activities are discussed as a whole, because they are assumed to be simple and homogeneous. Consequently, no detailed information on how indigenous R&D influences energy intensity can be obtained. In addition, regional imbalances are basically ignored. That may yield generalized results and policy implications for the whole of China but lack relevance for China's different regions. In this paper, the effects of indigenous R&D activities on energy intensity are analyzed by dividing R&D activities into three stages with three performers. The empirical results based on China's provincial data set covering the period 2000-2016 suggest that indigenous R&D is a major tool for cutting energy intensity; however, energy intensity is subject to statistically different effects from R&D activities in different stages and by different performers. The R&D activities in the experiment and development stage play a more important role in decreasing energy intensity, compared to the other two stages. In addition, R&D activities carried out by industrial enterprises contribute more to cutting energy intensity than those of independent R&D institutions and higher education. In a regional comparison, there is also clear evidence that the regional difference should not be omitted, suggesting that policy makers should pay more attention to coordinating the energy policies of different regions to maximize the policies' impacts.