ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein-DNA Interaction Hotspots.

Protein-DNA interactions are pivotal to various cellular processes. Precise identification of the hotspot residues for protein-DNA interactions holds great significance for revealing the intricate mechanisms in protein-DNA recognition and for providing essential guidance for protein engineering. Aiming at protein-DNA interaction hotspots, this work introduces an effective prediction method, ESPDHot based on a stacked ensemble machine learning framework. Here, the interface residue whose mutation leads to a binding free energy change (ΔΔG) exceeding 2 kcal/mol is defined as a hotspot. To tackle the imbalanced data set issue, the adaptive synthetic sampling (ADASYN), an oversampling technique, is adopted to synthetically generate new minority samples, thereby rectifying data imbalance. As for molecular characteristics, besides traditional features, we introduce three new characteristic types including residue interface preference proposed by us, residue fluctuation dynamics characteristics, and coevolutionary features. Combining the Boruta method with our previously developed Random Grouping strategy, we obtained an optimal set of features. Finally, a stacking classifier is constructed to output prediction results, which integrates three classical predictors, Support Vector Machine (SVM), XGBoost, and Artificial Neural Network (ANN) as the first layer, and Logistic Regression (LR) algorithm as the second one. Notably, ESPDHot outperforms the current state-of-the-art predictors, achieving superior performance on the independent test data set, with F1, MCC, and AUC reaching 0.571, 0.516, and 0.870, respectively.

PMSPcnn: Predicting protein stability changes upon single point mutations with convolutional neural network.

Protein missense mutations and resulting protein stability changes are important causes for many human genetic diseases. However, the accurate prediction of stability changes due to mutations remains a challenging problem. To address this problem, we have developed an unbiased effective model: PMSPcnn that is based on a convolutional neural network. We have included an anti-symmetry property to build a balanced training dataset, which improves the prediction, in particular for stabilizing mutations. Persistent homology, which is an effective approach for characterizing protein structures, is used to obtain topological features. Additionally, a regression stratification cross-validation scheme has been proposed to improve the prediction for mutations with extreme ΔΔG. For three test datasets: Ssym, p53, and myoglobin, PMSPcnn achieves a better performance than currently existing predictors. PMSPcnn also outperforms currently available methods for membrane proteins. Overall, PMSPcnn is a promising method for the prediction of protein stability changes caused by single point mutations.

Identification of MYCN non-amplified neuroblastoma subgroups points towards molecular signatures for precision prognosis and therapy stratification.

BACKGROUND: Despite the extensive study of MYCN-amplified neuroblastomas, there is a significant unmet clinical need in MYCN non-amplified cases. In particular, the extent of heterogeneity within the MYCN non-amplified population is unknown. METHODS: A total of 1566 samples from 16 datasets were identified in Gene Expression Omnibus (GEO) and ArrayExpress. Characterisation of the subtypes was analysed by ConsensusClusterPlus. Independent predictors for subgrouping were constructed from the single sample predictor based on the multiclassPairs package. Findings were verified using immunohistochemistry and CIBERSORTx analysis. RESULTS: We demonstrate that MYCN non-amplified neuroblastomas are heterogeneous and can be classified into 3 subgroups based on their transcriptional signatures. Within these groups, subgroup_2 has the worst prognosis and this group shows a 'MYCN' signature that is potentially induced by the overexpression of Aurora Kinase A (AURKA); whilst subgroup_3 is characterised by an 'inflamed' gene signature. The clinical implications of this subtype classification are significant, as each subtype demonstrates a unique prognosis and vulnerability to investigational therapies. A total of 420 genes were identified as independent subgroup predictors with average balanced accuracy of 0.93 and 0.84 for train and test datasets, respectively. CONCLUSION: We propose that transcriptional subtyping may enhance precision prognosis and therapy stratification for patients with MYCN non-amplified neuroblastomas.

Kisspeptin-10 binding to Gpr54 in osteoclasts prevents bone loss by activating Dusp18-mediated dephosphorylation of Src.

Osteoclasts are over-activated as we age, which results in bone loss. Src deficiency in mice leads to severe osteopetrosis due to a functional defect in osteoclasts, indicating that Src function is essential in osteoclasts. G-protein-coupled receptors (GPCRs) are the targets for ∼35% of approved drugs but it is still unclear how GPCRs regulate Src kinase activity. Here, we reveal that GPR54 activation by its natural ligand Kisspeptin-10 (Kp-10) causes Dusp18 to dephosphorylate Src at Tyr 416. Mechanistically, Gpr54 recruits both active Src and the Dusp18 phosphatase at its proline/arginine-rich motif in its C terminus. We show that Kp-10 binding to Gpr54 leads to the up-regulation of Dusp18. Kiss1, Gpr54 and Dusp18 knockout mice all exhibit osteoclast hyperactivation and bone loss, and Kp-10 abrogated bone loss by suppressing osteoclast activity in vivo. Therefore, Kp-10/Gpr54 is a promising therapeutic target to abrogate bone resorption by Dusp18-mediated Src dephosphorylation.

Complement components regulates ferroptosis in CVB3 viral myocarditis by interatction with TFRC.

BACKGROUND: Dysregulated cell death machinery and an excessive inflammatory response in Coxsackievirus B3(CVB3)-infected myocarditis are hallmarks of an abnormal host response. Complement C4 and C3 are considered the central components of the classical activation pathway and often participate in the response process in the early stages of virus infection. METHODS: In our study, we constructed a mouse model of CVB3-related viral myocarditis via intraperitoneal injection of Fer-1 and detected myocarditis and ferroptosis markers in the mouse myocardium. Then, we performed co-IP and protein mass spectrometry analyses to explore which components interact with the ferroptosis gene transferrin receptor (TFRC). Finally, functional experiments were conducted to verify the role of complement components in regulating ferroptosis in CVB3 infection. RESULTS: It showed that the ferroptosis inhibitor Fer-1 could alleviate the inflammation in viral myocarditis as well as ferroptosis. Mechanistically, during CVB3 infection, the key factor TFRC was activated and inhibited by Fer-1. Fer-1 effectively prevented the consumption of complement C3 and overload of the complement product C4b. Interestingly, we found that TFRC directly interacts with complement C4, leading to an increase in the product of C4b and a decrease in the downstream complement C3. Functional experiments have also confirmed that regulating the complement C4/C3 pathway can effectively rescue cell ferroptosis caused by CVB3 infection. CONCLUSIONS: In this study, we found that ferroptosis occurs through crosstalk with complement C4 in viral myocarditis through interaction with TFRC and that regulating the complement C4/C3 pathway may rescue ferroptosis in CVB3-infected cardiomyocytes.

Acetylation of FOXO1 activates Bim expression involved in CVB3 induced cardiomyocyte apoptosis.

Viral myocarditis (VMC) is the major reason for sudden cardiac death among both children and young adults. Of these, coxsackievirus B3 (CVB3) is the most common causative agent of myocarditis. Recently, the role of signaling pathways in the pathogenesis of VMC has been evaluated in several studies, which has provided a new perspective on identifying potential therapeutic targets for this hitherto incurable disease. In the present study, in vivo and in vitro experiments showed that CVB3 infection leads to increased Bim expression and triggers apoptosis. In addition, by knocking down Bim using RNAi, we further confirmed the biological function of Bim in apoptosis induced by CVB3 infection. We additionally found that Bim and forkhead box O1 class (FOXO1) inhibition significantly increased the viability of CVB3-infected cells while blocking viral replication and viral release. Moreover, CVB3-induced Bim expression was directly dependent on FOXO1 acetylation, which is catalyzed by the co-regulation of CBP and SirTs. Furthermore, the acetylation of FOXO1 was an important step in Bim activation and apoptosis induced by CVB3 infection. The findings of this study suggest that CVB3 infection induces apoptosis through the FOXO1 acetylation-Bim pathway, thus providing new insights for developing potential therapeutic targets for enteroviral myocarditis.

Dry season temperature and rainy season precipitation significantly affect the spatio-temporal pattern of rubber plantation phenology in Yunnan province.

The ongoing global warming trajectory poses extensive challenges to plant ecosystems, with rubber plantations particularly vulnerable due to their influence on not only the longevity of the growth cycle and rubber yield, but also the complex interplay of carbon, water, and energy exchanges between the forest canopy and atmosphere. However, the response mechanism of phenology in rubber plantations to climate change remains unclear. This study concentrates on sub-optimal environment rubber plantations in Yunnan province, Southwest China. Utilizing the Google Earth Engine (GEE) cloud platform, multi-source remote sensing images were synthesized at 8-day intervals with a spatial resolution of 30-meters. The Normalized Difference Vegetation Index (NDVI) time series was reconstructed using the Savitzky-Golay (S-G) filter, coupled with the application of the seasonal amplitude method to extract three crucial phenological indicators, namely the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (LOS). Linear regression method, Pearson correlation coefficient, multiple stepwise regression analysis were used to extract of the phenology trend and find the relationship between SOS, EOS and climate factors. The findings demonstrated that 1) the phenology of rubber plantations has undergone dynamic changes over the past two decades. Specifically, the SOS advanced by 9.4 days per decade (R2 = 0.42, p< 0.01), whereas the EOS was delayed by 3.8 days per decade (R2 = 0.35, p< 0.01). Additionally, the LOS was extended by 13.2 days per decade (R2 = 0.55, p< 0.01); 2) rubber phenology demonstrated a notable sensitivity to temperature fluctuations during the dry season and precipitation patterns during the rainy season. The SOS advanced 2.0 days (r =-0.19, p< 0.01) and the EOS advanced 2.8 days (r =-0.35, p< 0.01) for every 1°C increase in the cool-dry season. Whereas a 100 mm increase in rainy season precipitation caused the SOS to be delayed by 2.0 days (r = 0.24, p< 0.01), a 100 mm increase in hot-dry season precipitation caused the EOS to be advanced by 7.0 days (r =-0.28, p< 0.01); 3) rubber phenology displayed a legacy effect of preseason climate variations. Changes in temperature during the fourth preseason month and precipitation during the fourth and eleventh preseason months are predominantly responsible for the variation in SOS. Meanwhile, temperature changes during the second, fourth, and ninth preseason months are primarily responsible for the variation in EOS. The study aims to enhance our understanding of how rubber plantations respond to climate change in sub-optimal environments and provide valuable insights for sustainable rubber production management in the face of changing environmental conditions.

Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G-Protein-Coupled Receptor GPR52.

Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5'-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 µs Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor.

Fractal two-scale method for calculating the laser scattering distribution of asphalt pavement.

The laser scattering characteristic of pavement is one of the important factors that affect the detection performance of optical sensors such as lidars. Because the wavelength of laser does not match the roughness of the asphalt pavement, the common analytical approximation model of electromagnetic scattering is not applicable in this case, so it is difficult to calculate the laser scattering distribution of the pavement accurately and effectively. According to the self-similarity of the asphalt pavement profile, a fractal two-scale method (FTSM) based on fractal structure is proposed in this paper. We used the Monte Carlo method to obtain the bidirectional scattering intensity distribution (SID) and the back SID of the laser on the asphalt pavement with different roughness. Then we designed a laser scattering measurement system to verify the simulation results. We calculated and measured the SIDs of s-light and p-light of three asphalt pavements with different roughness (σ=0.34 mm; 1.74 mm; 3.08 mm). The results show that, compared with the traditional analytical approximation methods, the results of FTSM are closer to the experimental results. Compared with the single-scale model based on the Kirchhoff approximation, FTSM has a significant improvement in computational accuracy and speed.

Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses.

We propose an improved transfer entropy approach called the dynamic version of the force constant fitted Gaussian network model based on molecular dynamics ensemble (dfcfGNMMD) to explore the allosteric mechanism of human mitochondrial phenylalanyl-tRNA synthetase (hmPheRS), one of the aminoacyl-tRNA synthetases that play a crucial role in translation of the genetic code. The dfcfGNMMD method can provide reliable estimates of the transfer entropy and give new insights into the role of the anticodon binding domain in driving the catalytic domain in aminoacylation activity and into the effects of tRNA binding and residue mutation on the enzyme activity, revealing the causal mechanism of the allosteric communication in hmPheRS. In addition, we incorporate the residue dynamic and co-evolutionary information to further investigate the key residues in hmPheRS allostery. This study sheds light on the mechanisms of hmPheRS allostery and can provide important information for related drug design.

Diversity and assembly of root-associated microbiomes of rubber trees.

Introduction: Understanding the diversity and assembly of the microbiomes of plant roots is crucial to manipulate them for sustainable ecosystem functioning. However, there are few reports about microbial communities at a continuous fine-scale of roots for rubber trees. Methods: We investigate the structure, diversity, and assembly of bacterial and fungal communities for the soil (non-rhizosphere), rhizosphere, and rhizoplane as well as root endosphere of rubber trees using the amplicon sequencing of 16S ribosomal ribonucleic acid (rRNA) and Internally Transcribed Spacer (ITS) genes. Results: We show that 18.69% of bacterial and 20.20% of fungal operational taxonomic units (OTUs) in the rhizoplane derived from the endosphere and 20.64% of bacterial and 20.60% of fungal OTUs from the soil. This suggests that the rhizoplane microbial community was a mixed community of soil and endosphere microbial communities and that microorganisms can disperse bidirectionally across different compartments of the plant root. On the other hand, in the absence of an enrichment or depletion of core bacterial and fungal OTUs in the rhizosphere, little differences in microbial composition as well as a more shared microbial network structure between the soil and the rhizosphere support the theory that the rhizosphere microbial community is a subset of the soil community. A large number of functional genes (such as nitrogen fixation and nitrite reduction) and more enriched core OTUs as well as a less stable but more complex network structure were observed in the rhizoplane of rubber tree roots. This demonstrated that the rhizoplane is the most active root compartment and a hotspot for plant-soil-environment interactions. In addition, bacterial and fungal communities in the rhizoplane were more stochastic compared to the rhizosphere and soil. Discussion: Our study expands our understanding of root-associated microbial community structure and function, which may provide the scientific basis for sustainable agriculture through biological process management.

Diversified land conversion deepens understanding of impacts of rapid rubber plantation expansion on plant diversity in the tropics.

Understanding the status and changes of plant diversity in rubber (Hevea brasiliensis) plantations is essential for sustainable plantation management in the context of rapid rubber expansion in the tropics, but remains very limited at the continental scale. In this study, we investigated plant diversity from 10-meter quadrats in 240 different rubber plantations in the six countries of the Great Mekong Subregion (GMS)-where nearly half of the world's rubber plantations are located-and analyzed the influence of original land cover types and stand age on plant diversity using Landsat and Sentinel-2 satellite imagery since the late 1980s. The results indicate that the average plant species richness of rubber plantations is 28.69 ± 7.35 (1061 species in total, of which 11.22 % are invasive), approximating half the species richness of tropical forests but roughly double that of the intensively managed croplands. Time-series satellite imagery analysis revealed that rubber plantations were primarily established in place of cropland (RPC, 37.72 %), old rubber plantations (RPORP, 27.63 %), and tropical forests (RPTF, 24.12 %). Plant species richness in RPTF (34.02 ± 7.62) was significantly (p < 0.001) higher than that in RPORP (26.41 ± 7.02) and RPC (26.34 ± 5.37). More importantly, species richness can be maintained for the duration of the 30-year economic cycle, and the number of invasive species decreases as the stand ages. Given diverse land conversions and changes in stand age, the total loss of species richness due to rapid rubber expansion in the GMS was 7.29 %, which is far below the traditional estimates that only consider tropical forest conversion. In general, maintaining higher species richness at the earliest stages of cultivation has significant implications for biodiversity conservation in rubber plantations.

Identification and low-frequency vibrational analysis of three free anthraquinones via terahertz spectroscopy.

In this study, terahertz time-domain spectroscopy (THz-TDS) was used to obtain the terahertz absorption spectra of three free anthraquinones (Chrysophanol, Emodin, Physcion) in the frequency range of 0.2-4.3 THz. The results show that terahertz spectroscopy is an effective detecting such compounds. Meanwhile, the theoretical spectrum using density functional theory calculations agrees well with the experimental spectrum. A modal decoupling method was used to identify each low-frequency vibrational mode and determine the average contribution of different atoms and groups. Modal decoupling provides a better understanding of molecules' mixed vibrational modes and enables quantifying the atoms' vibrational contributions. Results show that the substituent group facilitates the transition between the fundamental vibrational modes; subsequently, the substituent group shifts the vibrational centre of gravity of the three molecules and affects the vibrational contribution of hydrogen bonds. Furthermore, insignificant Emodin absorption is related to the nearly symmetrical structure formed by the substituents. The feasibility of terahertz analysis of differential molecular structures has also been confirmed.

P300 Interacted With N-Myc and Regulated Its Protein Stability via Altering Its Post-Translational Modifications in Neuroblastoma.

MYCN amplification is an independent risk factor for poor prognosis in neuroblastoma (NB), but its protein product cannot be directly targeted because of protein structure. Thus, this study aimed to explore novel ways to indirectly target N-Myc by regulating its post-translational modifications (PTMs) and therefore protein stability. N-Myc coimmunoprecipitation combined with HPLC-MS/MS identified 16 PTM residues and 114 potential N-Myc-interacting proteins. Notably, both acetylation and ubiquitination were identified on lysine 199 of N-Myc. We then discovered that p300, which can interact with N-Myc, modulated the protein stability of N-Myc in MYCN-amplified NB cell lines and simultaneously regulated the acetylation level and ubiquitination level on lysine-199 of N-Myc protein in vitro. Furthermore, p300 correlated with poor prognosis in NB patients. Taken together, p300 can be considered as a potential therapeutic target to treat MYCN-amplified NB patients, and other identified PTMs and interacting proteins also provide potential targets for further study.

Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.

Study on dietary intake, risk assessment, and molecular toxicity mechanism of benzo[α]pyrene in college students in China Bashu area.

As an extremely strong polycyclic aromatic hydrocarbon carcinogen, benzo[α]pyrene (BaP) is often produced during food processing at high temperatures. Recently, food safety, as well as toxicity mechanism and risk assessment of BaP, has received extensive attention. We first constructed the database of BaP pollution concentration in Chinese daily food with over 104 data items; collected dietary intake data using online survey; then assessed dietary exposure risk; and finally revealed the possible toxicity mechanism through four comparative molecular dynamics (MD) simulations. The statistical results showed that the concentration of BaP in olive oil was the highest, followed by that in fried meat products. The margins of exposure and incremental lifetime cancer risk both indicated that the dietary exposure to BaP of the participants was generally safe, but there were still some people with certain carcinogenic risks. Specifically, the health risk of the core district population was higher than that of the noncore district in Bashu area, and the female postgraduate group was higher than the male group with bachelor degree or below. From MD trajectories, BaP binding does not affect the global motion of individual nucleic acid sequences, but local weak noncovalent interactions changed greatly; it also weakens molecular interactions of nucleic acid with Bacillus stearothermophilus DNA polymerase I large fragment (BF), and significantly changes the cavity structure of recognition interface. This work not only reveals the possible toxicity mechanism of BaP, but also provides theoretical guidance for the subsequent optimization of food safety standards and reference of rational diet.

Space Rather than Seasonal Changes Explained More of the Spatiotemporal Variation of Tropical Soil Microbial Communities.

Soil microbiomes play an essential role in maintaining soil geochemical cycle and function. Although there have been some reports on the diversity patterns and drivers of the tropical forest soil microbial community, how space and seasonal changes affect spatiotemporal distribution at the regional scales are poorly understood. Based on 260 soil samples, we investigated the spatiotemporal patterns of rubber plantations and rainforest soil microbial communities across the whole of Hainan Island, China during the dry and rainy seasons. We examined soil bacterial and fungal composition and diversity and the main drivers of these microbes using Illumina sequencing and assembly. Our results revealed that the diversity (both alpha and beta) spatiotemporal variation in microbial communities is highly dependent on regional location rather than seasonal changes. For example, the site explained 28.5% and 37.2% of the variation in alpha diversity for soil bacteria and fungi, respectively, and explained 34.6% of the bacterial variance and 14.3% of the fungal variance in beta diversity. Soil pH, mean annual temperature, and mean annual precipitation were the most important factors associated with the distribution of soil microbial communities. Furthermore, we identified that variations in edaphic (e.g., soil pH) and climatic factors (e.g., mean annual temperature [MAT] and mean annual precipitation [MAP]) were mainly caused by regional sites (P < 0.001). Collectively, our work provides empirical evidence that space, rather than seasonal changes, explained more of the spatiotemporal variation of soil microbial communities in tropical forests, mediated by regional location-induced changes in climatic factors and edaphic properties. IMPORTANCE The soil microbiomes communities of the two forests were not only affected by environmental factors (e.g., edaphic and climatic factors), but also by different dominant geographic factors. In particular, our work showed that spatial variation in bacterial and fungal community composition was mainly dominated by edaphic properties (e.g., pH) and climatic factors (e.g., MAT and MAP). Moreover, the environmental factors were mainly explained by geographic location effect rather than by seasonal effect, and environmental dissimilarity significantly increased with geographic distance. In conclusion, our study provides solid empirical evidence that space rather than season explained more of the spatiotemporal variation of soil microbial communities in the tropical forest.

Sensitivity Analysis of Biome-BGC for Gross Primary Production of a Rubber Plantation Ecosystem: A Case Study of Hainan Island, China.

Accurate monitoring of forest carbon flux and its long-term response to meteorological factors is important. To accomplish this task, the model parameters need to be optimized with respect to in situ observations. In the present study, the extended Fourier amplitude sensitivity test (eFAST) method was used to optimize the sensitive ecophysiological parameters of the Biome BioGeochemical Cycles model. The model simulation was integrated from 2010 to 2020. The results showed that using the eFAST method quantitatively improved the model output. For instance, the R2 increased from 0.53 to 0.72. Moreover, the root-mean-square error was reduced from 1.62 to 1.14 gC·m-2·d-1. In addition, it was reported that the carbon flux outputs of the model were highly sensitive to various parameters, such as the canopy average specific leaf area and canopy light extinction coefficient. Moreover, long-term meteorological factor analysis showed that rainfall dominated the trend of gross primary production (GPP) of the study area, while extreme temperatures restricted the GPP. In conclusion, the eFAST method can be used in future studies. Furthermore, eFAST could be applied to other biomes in response to different climatic conditions.

ß-hydroxybutyrate reduces reinstatement of cocaine conditioned place preference through hippocampal CaMKII-α ß-hydroxybutyrylation.

Studies have shown the therapeutic effects of a ketogenic diet (KD) on epilepsy, but the effect of a KD on drug reinstatement is largely unclear. This study aims to investigate whether KD consumption possesses therapeutic potential for cocaine reinstatement and the molecular mechanism. We find that a KD significantly reduces cocaine-induced reinstatement in mice, which is accompanied by a markedly elevated level of ß-hydroxybutyrate (ß-OHB), the most abundant ketone body, in the hippocampus. The underlying mechanism is that ß-OHB posttranslationally modifies CaMKII-α with ß-hydroxybutyrylation, resulting in significant inhibition of T286 autophosphorylation and downregulation of CaMKII activity. Collectively, our results reveal that ß-hydroxybutyrylation is a posttranslational modification of CaMKII-α that plays a critical role in mediating the effect of KD consumption in reducing cocaine reinstatement.

Broadband devices for a polarization converter based on optical metasurfaces.

Devices employed for optical polarization conversion are widely used in the areas of optical focusing, optical imaging, and microscopy. To circumvent the problems of traditional optical polarization conversion devices, such as a narrow bandwidth, bulky size, and integration difficulties, a linear-radial polarization converter (LRPC) method based on optical metasurfaces is proposed. For a visible wavelength, i.e., λ=632.8nm, an all-dielectric half-wave plate and a LRPC with a size of 40λ (25.312 µm) are designed. The simulated results demonstrate that the LRPC creates a radially polarized wave from a linearly polarized wave in the wavelength range of 620-680 nm. In addition, a cylindrical vectorial wave with different polarizations can be generated via an adjustment of the polarization direction of the incident wave. These types of polarization converters have the important advantage of high transmittance, while also being ultra-thin and easy to integrate. They are expected to be suitable for miniaturized and integrated optical devices.