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The mycorrhizal pathway is an important phosphorus (P) uptake pathway for more than two-thirds of land plants. The arbuscular mycorrhizal (AM) fungi-associated hyphosphere microbiome has been considered as the second genome of mycorrhizal P uptake pathway and functionality in mobilizing soil organic P (Po). However, whether there is a core microbiome in the hyphosphere and how this is implicated in mining soil Po are less understood. We established on-site field trials located in humid, semiarid, and arid zones and a microcosm experiment in a glasshouse with specific AM fungi and varying soil types to answer the above questions. The hyphosphere microbiome of AM fungi enhanced soil phosphatase activity and promoted Po mineralization in all sites. Although the assemblage of hyphosphere microbiomes identified in three climate zones was mediated by environmental factors, we detected a core set in three sites and the subsequent microcosm experiment. The core members were co-enriched in the hyphosphere and dominated by Alphaproteobacteria, Actinobacteria, and Gammaproteobacteria. Moreover, these core bacterial members aggregate into stable guilds that contributed to phosphatase activity. The core hyphosphere microbiome is taxonomically conserved and provides functions, with respect to the mineralization of Po, that AM fungi lack.

Biochemical pregnancy is a type of embryo transfer failure, patients with unexplained repeated implantation failure (RIF) also have higher biochemical pregnancy rate. Our study intends to evaluate the effect of granulocyte colony-stimulating factor (G-CSF) in patients with unexplained RIF with low hCG levels in early pregnancy. Unexplained RIF patients with low hCG levels after embryo transfer were allocated. G-CSF were administrated from the ninth days after embryo transfer. Clinical pregnancy, miscarriage and live birth rates were evaluated. The clinical pregnancy and live birth rates were 52.5% and 30%. G-CSF is an effective treatment for potential biochemical pregnancy in unexplained RIF patients.

Background: The connection between m6A-assiociateed lncRNAs and prognosis has been demonstrated in multiple types of tumors. However, potential roles of m6A-assiociateed lncRNAs in glioma is still rare. Methods: We implemented consensus cluster analysis to group the downloaded samples into two subtypes. The least absolute shrinkage and selection operator (LASSO) analysis was used to create a risk model. Additionally, the conjunction between m6A-related lncRNAs and immune cells infiltration was explored by conducting the R package. Ultimately, we inspected the underlying downstream pathways of the two subtypes by performing Gene Set Enrichment Analysis (GSEA). The expression level of m6A-connected lncRNAs in glioma were examined by conducting in vitro experiments. Results: We ascertained two subtypes of glioma in line with the consensus clustering of m6A-associated lncRNAs. We confirmed that age, grade, and IDH are related to the two subtypes. Additionally, the immune cells infiltration and immune checkpoint molecules of the two clusters were discussed. A risk signature including AL359643.3, AL445524.1, AL162231.2, AL117332.1, AP001486.2, POLR2J4, AC120036.4, LINC00641, LINC00900, CRNDE, and AL158212.3, was identified using the Cox regression and LASSO analyses. We also verified the prognostic value and discussed the immune cells infiltration and immune checkpoint molecules of the risk signature. In vitro experiments verified that the m6A-associated lncRNAs was abnormally expressed in glioma. Conclusion: We elaborated the significant role of m6A-connected lncRNAs in glioma prognosis and immune infiltration and suggest that these key regulators may serve as underlying therapeutic targets to build up the efficacy of glioma immunotherapy.

Background: The specific functions of PPP1R81 has been elucidated in multiple cancers; however, its role in lower-grade glioma (LGG) remains unknown. In this research, we inspected the specific role of PPP1R81 in LGG. Methods: We totally evaluated the expression pattern and prognostic role of PPP1R81 in multitudinous tumors. Subsequently, we systematically examined the connection between PPP1R81 expression and prognosis, clinical characteristics, biological functions, genetic variations, and immunological characteristics in LGG according to the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Altas (CGGA) databases. In vitro experiments were executed to inspect the expression level and specific roles of PPP1R81 in LGG. Results: PPP1R81 was elevated in multiple tumors and was tightly linked to a poor prognosis. LGG with higher expression of PPP1R81 showed poorer prognosis compared with lower expression of PPP1R81. The results of univariate and multivariate Cox regression analyses confirmed that the expression of PPP1R81 was an independent prognostic biomarker of LGG. Immune cell infiltration, immune checkpoint genes (ICPGs), copy number alterations (CNA), and tumor mutation burden (TMB) were also closely associated with PPP1R81 expression in LGG. In vitro experiments demonstrated that PPP1R81 was up-regulated and closely interrelated with cell proliferation and cell cycle in LGG. Conclusion: PPP1R81 was an independent prognostic signature and underlying therapeutic target for patients with LGG.

Condensates are a hallmark of emergence in quantum materials with superconductors and charge density wave as prominent examples. An excitonic insulator (EI) is an intriguing addition to this library, exhibiting spontaneous condensation of electron-hole pairs. However, condensate observables can be obscured through parasitic coupling to the lattice. Time-resolved terahertz (THz) spectroscopy can disentangle such obscurants through measurement of the quantum dynamics. We target $Ta_{2}NiSe_{5}$, a putative room-temperature EI where electron-lattice coupling dominates the structural transition ($T_{c}$=326 K), hindering identification of excitonic correlations. A pronounced increase in the THz reflectivity manifests following photoexcitation and exhibits a BEC-like temperature dependence. This occurs well below the $T_{c}$, suggesting a novel approach to monitor exciton condensate dynamics. Nonetheless, dynamic condensate-phonon coupling remains as evidenced by peaks in the enhanced reflectivity spectrum at select infrared-active phonon frequencies. This indicates that parametric reflectivity enhancement arises from phonon squeezing, validated using Fresnel-Floquet theory and density functional calculations. Our results highlight that coherent dynamics can drive parametric stimulated emission with concomitant possibilities, including entangled THz photon generation., 51 pages, 14 figures, 1 table

Ecology seeks to explain species coexistence, but experimental tests of mechanisms for coexistence are difficult to conduct. We synthesized an arbuscular mycorrhizal (AM) fungal community with three fungal species that differed in their capacity of foraging for orthophosphate (P) due to differences in soil exploration. We tested whether AM fungal species-specific hyphosphere bacterial assemblages recruited by hyphal exudates enabled differentiation among the fungi in the capacity of mobilizing soil organic P (Po). We found that the less efficient space explorer, Gigaspora margarita, obtained less 13C from the plant, whereas it had higher efficiencies in Po mobilization and alkaline phosphatase (AlPase) production per unit C than the two efficient space explorers, Rhizophagusintraradices and Funneliformis mosseae. Each AM fungus was associated with a distinct alp gene harboring bacterial assemblage, and the alp gene abundance and Po preference of the microbiome associated with the less efficient space explorer were higher than those of the two other species. We conclude that the traits of AM fungal associated bacterial consortia cause niche differentiation. The trade-off between foraging ability and the ability to recruit effective Po mobilizing microbiomes is a mechanism that allows co-existence of AM fungal species in a single plant root and surrounding soil habitat.

Supplemental material, sj-docx-1-tan-10.1177_17562864231181180 for Comparative efficacy and safety of various mechanical thrombectomy strategies for patients with acute ischemic stroke: a Bayesian network meta-analysis by Jiahao Meng, Zeya Yan, Jie Zhang, Wei Wang, Xinyu Tao, Feng Gu, Xingyu Yang, Tao Xue, Wanchun You, Zhouqing Chen, Zhong Wang and Gang Chen in Therapeutic Advances in Neurological Disorders

Supplemental material, sj-docx-1-tan-10.1177_17562864231181180 for Comparative efficacy and safety of various mechanical thrombectomy strategies for patients with acute ischemic stroke: a Bayesian network meta-analysis by Jiahao Meng, Zeya Yan, Jie Zhang, Wei Wang, Xinyu Tao, Feng Gu, Xingyu Yang, Tao Xue, Wanchun You, Zhouqing Chen, Zhong Wang and Gang Chen in Therapeutic Advances in Neurological Disorders

Purpose: Due to the existing methodologies on two-sided matching seldom consider the asymmetry, uncertainty and fuzziness of the preference information, this paper aims to develop a methodology for solving the selection process between green suppliers and manufacturers with intuitionistic linguistic numbers. Methods: This paper first constructs the evaluation indicators for both sides, which are depicted as intuitionistic linguistic numbers. Subsequently, the authors redefine the intuitionistic linguistic numbers’ expected function based on regret theory. By considering the psychological behaviour of the regret aversion of decision makers, the paper constructs the comprehensive perceived values of decision makers. Furthermore, by maximizing the comprehensive perceived values for the two sides, the multi-objectives matching model is established. In addition, this paper adopts a min-max method to transform the multi-objective optimal model into the single-objective model. Conclusions: This paper considers fuzziness and hesitancy of the preference information, and also considering the psychological behaviour of the regret aversion of decision makers, the two-sided matching method proposed by this paper is more validity and effectiveness than existing methods.

Arbuscular mycorrhizal (AM) fungi form a continuum between roots and soil. One end of this continuum is comprised of the highly intimate plant-fungus interface with intracellular organelles for nutrient exchange, while on the other end the fungus interacts with bacteria to compensate for the AM fungus' inability to take up organic nutrients from soil. How both interfaces communicate in this highly complex tripartite mutualism is widely unknown. Here, the effects of phosphate solubilizing bacteria (PSB) Rahnella aquatilis dwelling at the surface of the extraradical hyphae of Rhizophagus irregularis was analyzed based on the expression of genes involved in C-P exchange at the peri-arbuscular space (PAS) in Medicago truncatula. The interaction between AM fungus and PSB resulted in an increase in uptake and transport of Pi along the extraradical hyphae and its transfer from AM fungus to plant. In return, this was remunerated by a transfer of C from plant to AM fungus, improving the C-P exchange at the PAS. These results demonstrated that a microorganism (i.e., a PSB) developing at the hyphosphere interface can affect the C-P exchange at the PAS between plant and AM fungus, suggesting a fine-tuned communication operated between three organisms via two distantly connected interfaces.

BackgroundMultiple sclerosis (MS), an autoimmune disease, is characterized by inflammatory demyelinating lesions in the white matter of the central nervous system. Drugs targeting tyrosine kinase, a critical component of immune cell receptor signaling, have been developed to treat MS. However, the exact efficacy and safety of tyrosine kinase inhibitors (TKIs) are still controversial, and comprehensive analysis with a high level of evidence is needed.MethodsMedline, Embase, Cochrane Library, and Clinicaltrials.gov for randomized controlled trials (RCTs) evaluating TKIs versus placebo for MS were searched up to April 1st, 2022. The risk ratio (RR) and mean difference (MD) or standard mean difference (SMD) were analyzed using dichotomous outcomes and continuous outcomes, respectively, with a random effect model.ResultsA total of 1,043 patients derived from four clinical trials were included to investigate the efficacy and safety of TKI therapy for MS. According to our analysis, TKIs decreased the cumulative number of gadolinium-enhancing lesions on T1-weighted MRI with the application of high dose (SMD = −0.61, 95% CI: −0.93 to −0.30, P = 0.0001). Meanwhile, TKIs prevented the expanded disability status scale (EDSS) from rising (MD = −0.10, 95% CI: −0.19 to −0.00, P = 0.046). In terms of MS relapse, TKIs have not revealed an obvious statistical difference compared with placebo (RR = 0.96, 95% CI: 0.55–1.65, P = 0.8755). However, more adverse events seem to occur in the TKIs group, both for adverse events (RR = 1.12, 95% CI: 1.05–1.19, P = 0.0009) and serious adverse events (RR = 1.91, 95% CI: 1.30–2.81, P = 0.001).ConclusionTyrosine kinase inhibitors have shown promise in treating MS. Generally, TKIs that attain the effective dose demonstrate definite efficacy and have tolerable side effects. More clinical trials and validation are needed, and we anticipate that TKIs will be a viable alternative for MS patients.

Phosphorus (P) constraint can be alleviated by increasing C inputs, which can help to improve crop production and P fertilizer use efficiency. However, the effects of different manures on soil microbial biomass P (MBP) and P fractions as well as C fractions in calcareous soils remain poorly understood. Soil MBP pool involves the P mineralization and immobilization processes, potentially changing P fractions and P availability. Therefore, the effects of different manures on soil microbial biomass (MBP, MBC) pool, P, and C fractions and crop P utilization were evaluated in greenhouse experiments with maize plantation. Treatments included no manure (control), poultry manure (PM), cow manure (CM), goat manure (GM), mixed manure (MM), and three inorganic P (Pi) rates; P0: 0 mg kg-1, P50: 50 mg kg-1, and P100: P100 mg kg-1 (P2O5). For plant growth comparison, crop physiological growth indices, shoot P contents and total P uptake were increased by PM and P100 as compared to other treatments. The PM with P100 significantly increased the plant growth by inducing P uptake of ∼18% compared with control. The results exhibited that Pi (P100) combined with manure (PM) significantly (p < 0.05) increased the soil physicochemical properties, that is, 683.76 mg kg-1 total P, 21.5 mg kg-1 Olsen P, 4.26 g kg-1 SOC, 2.41 g kg-1 POC, as well as microbial biomass C and P increased by 152.84 mg kg-1 and 36.83 mg kg-1, respectively. Consequently, we concluded that PM with Pi (P100) application builds up soil microbial biomass, which is more beneficial for promoting P utilization for maize.

The effect and relative contributions of C and P inputs on soil microbial biomass P (MBP) accumulation were studied in three long-term soil fertility experiments with various soil and climate characteristics at Qiyang, Yangling, and Wulumuqi. The maximum of soil MBP in all three sites was 47.8 mg P kg-1. The MBP accumulated per unit in soil (mg P kg-1 soil) was correlated with a 4.91 mg kg-1 increase in Olsen P. For each unit increase in P surplus (kg P ha-1), manure C (kg C ha-1), and stubble C (kg C ha-1), MBP accumulation increased by 330, 3.7, and 13 units (μg P kg-1 soil), respectively. The soil MBP was positively correlated with crop yield and P uptake, making the soil MBP a useful soil P fertility index. The critical levels of the soil MBP pool were 140 kg ha-1, 57–62 kg ha-1, and 33–35 kg ha-1 in acidic red soil, loessial soil, and grey desert soil, respectively. This is the first report to establish a quantitative index of soil fertility based on the soil MBP pool. Our findings demonstrate that C input is a good driver of soil MBP accumulation. Integration of the soil MBP as an index of soil P fertility into agricultural P management is useful to help manage mineral P fertilizers as part of sustainable agricultural practices.

International audience; AbstractTo propose an accurate and less complex model of a special unmanned aerial vehicle (UAV), namely tilt-rotor UAV (TRUAV), this study identifies the active model-based nonlinear system of a quadTRUAV. First, a nominal nonlinear model of the vehicle is formulated. Some unstructured nonlinearities are ignored to reduce the complexity of the model. Then, due to the unstable dynamics of the open-loop system, the format of this nominal model is considered to design an innovative smooth-switch attitude control via interconnection and damping assignment passivity-based control (IDA-PBC). Active model-based nonlinear system identification is studied for the vehicle with the designed control method and flight experiments. The model error vector is defined and estimated by the unscented Kalman filter (UKF) to improve the accuracy of the model. The main contribution of this paper is to identify the nominal nonlinear model and to develop an active model method of the quad-TRUAV. The attitude control method with an innovative smooth-switch structure is another contribution to flight experiments. Numerical results are displayed to present the experimental results and effectiveness of the proposed nonlinear models.

Graphene serves as an ideal platform to investigate the microscopic structure and reaction kinetics at the graphitic electrode interfaces. However, graphene is susceptible to various extrinsic factors, e.g. substrate, causing much confusion and controversy. Hereby we have obtained cm-sized substrate-free monolayer graphene suspended on electrolyte surface with gate tunability. Using sum-frequency spectroscopy, we have observed the structural evolution versus the gate voltage at the graphene/water interface. The Stern layer structure is invariant within the water electrolysis window, but undergoes drastic change when switching on the electrochemical reactions. The electrode is turned from hydrophobic to hydrophilic near the onset of hydrogen evolution reaction due to hydrogen adsorption. The large-size suspended pristine graphene offers a new platform to unravel the microscopic processes at the graphitic electrode interfaces.

Little is known about the impact application of fertilizer and manure nutrients on the nutrient stoichiometry of crop–soil–microbe systems. We ask the question to what extent the nutrient availability in the microbe–soil–plant system may be affected by the application of fertilizers or manures. The influence of application of inorganic fertilizers or composted manure on the concentrations of carbon (C), nitrogen (N), and phosphorus (P) and their stoichiometric ratios in soil, microbial biomass, enzymes, and plant tissues within the rhizosphere of maize was investigated in a maize–wheat rotation established for 10 years in China. The higher rate of composted manure was most effective in increasing soil C, N, and P contents and the microbial biomass. Microbes changed biomass stoichiometry instead of regulating related enzyme secretion under different nutrient supplies. Although plants and microbes showed tight but different relationships with the two nutrient sources, competition for N consistently occurred. Pearson’s inter-correlation demonstrates stable Redfield-like C:N:P fractions existed in soil properties and related enzyme activity, but was not always found in crop and microbial biomass after fertilizer and manure application. The results indicate that soil microbial functioning and coupled feedback with the plants are important in maintaining the stability of fertilized/manured agricultural ecosystems.

Nutrient resource utilization is essential for plant community composition and productivity. Previous studies found that an increase in resource diversity causes species losses and reduces plant diversity. Arbuscular mycorrhizal (AM) fungi can increase plant productivity and nutrient uptake, however, whether AM fungi can reduce the negative influence of nutrient resource diversity on plant composition is still not well understood. A microcosm experiment was conducted with four phosphorus (P) sources (at five levels of P resource diversity) and two AM fungal species, and the plant community composition, aboveground biomass, and P content were measured and calculated. Plant species diversity and richness decreased with increasing soil P resource diversity in the absence of AM fungi, while the decrease was less when AM fungi were present. The biomass and P content of the aboveground plants increased with increasing AM fungal diversity and soil P resource diversity. The results of a structural equation model suggest that AM fungi could reduce the negative effects of increasing P resource diversity on plant community composition by improving plant density and P uptake. Our results indicate that AM fungi can maintain higher plant species diversity and increase plant productivity by increasing P resource utilization efficiency.

Soil Olsen P level has a major influence on crop yield, efficient P utilization, and soil fertility. In this study, the optimum Olsen P range was determined from long-term (1990–2012) field experiments in three typical soil types of China under single cropping of maize or double cropping of maize and wheat. The critical soil Olsen P value for crop yield was evaluated using three different models, and the relationships among P use efficiency (PUE), Olsen P, and total P were analyzed. The agronomic critical soil Olsen P values obtained from the three models for the neutral soil of Gongzhuling and the calcareous soil of Zhengzhou were similar; however, the values from the linear-linear and linear-plateau models for both maize and wheat were substantially lower than those from the Mitscherlich model for the acidic soil of Qiyang. The PUE response change rates (linear equation slopes) under different soil Olsen P levels were small, indicating slight or no changes in the PUE as the soil Olsen P increased in all three soils. A comparison of the Olsen P levels that achieved the maximal PUE with the agronomic critical values derived from the three models indicated that the linear-plateau model exhibited the best performance. The regression equation coefficients of Olsen P response to total P decreased as follows: Zhengzhou (73 mg g−1) > Qiyang (65 mg g−1) > Gongzhuling (55 mg g−1). The Olsen P level increased as the total P increased, which may result in a decrease in PUE. To achieve a relatively high crop yield, PUE, and soil fertility, the optimum Olsen P range should be 13–40, 10–40, and 29–40 mg kg−1 at Gongzhuling, Zhengzhou, and Qiyang, respectively.

PurposeHigher serum estradiol levels occur in women undergoing assisted reproductive technology (ART) owing to ovarian stimulation. Here, we investigated the association between maternal serum estradiol levels and the intellectual development of offspring conceived with ART.MethodsA total of 204 singletons born after fresh embryo transfer were recruited for this cohort study. Among them, 102 children were born from mothers with high serum estradiol levels (> 12,000 pmol/L) on the day that human chorionic gonadotropin was administered. Another 102 children, matched by gestational age and age of the children, were recruited as controls from mothers with low serum estradiol (≤ 12,000 pmol/L). The Wechsler Preschool and Primary Scale of Intelligence was used to evaluate the intellectual development of the children.ResultsChildren from mothers with higher serum estradiol levels scored lower in the verbal intelligence quotient (IQ) tests and verbal comprehension than children whose mothers had lower estradiol levels. The main difference between the two groups was in verbal subtests including information, vocabulary, and sorting. Partial correlation analysis revealed that the logarithm of maternal serum estradiol level negatively correlated with verbal IQ, performance IQ, and full scale IQ.ConclusionOur data demonstrate that a high maternal serum estradiol level may negatively associate the verbal ability of children conceived via ART.

Arbuscular mycorrhizal fungi play important roles in plant phosphorus (P) accumulation. The aim of this study was to uncover how and to what extent soil plant-available P levels and maize genotypes influence the contribution of mycorrhizal P uptake pathway to plant P nutrition. We selected an old genotype HMY and a modern genotype XY335, combined with 32P labeling and qPCR to quantify P uptake efficiency of the direct pathway (DP) and the mycorrhizal pathway (MP) at three Olsen-P levels: 4.5 (low), 8 (medium) and 50 (high) mg kg−1. The P uptake efficiency ratio PAE-MP/PAE-DP was highest in the treatment with medium Olsen-P, and was correlated positively with MP contribution. The traits of arbuscular mycorrhizal fungi, such as percent colonization, hyphal length density, P uptake per unit hyphae length, and the expression of the mycorrhiza-specific P transporter ZmPT1;6 were higher in XY335 than HMY in high-P soil, which was in accordance with the importance of the MP contribution. Greater mycorrhizal responsiveness in the modern maize genotype than the old genotype under high P soil condition is related to higher P uptake efficiency of MP than DP; the inherent potential of MP can be maximized by managing soil plant P availability to achieve optimal P supply in intensive farming.

Phosphorus (P) fertilizer is generally applied to enhance the soil P pool and meet crop demand, but most of the added P is absorbed by soil. This study aimed to explore the importance of P fractions and adsorption–desorption characteristics on the demand for P fertilizer to determine the optimum P fertilizer amount for a cotton field under mulched drip irrigation in Xinjiang, China. A 4-year experiment (2016–2019) was conducted in a cotton field to evaluate the effects of five P fertilizer addition levels (0, 75, 150, 300, and 450 kg P2O5 ha−1 year−1) on inorganic P fractions and P adsorption–desorption properties at different soil depths and explore the effects of soil properties on P adsorption. The 4-year continuous P fertilization enhanced the inorganic P content and altered the proportions of various P forms. A large proportion of P accumulated in soil was transformed into Ca8-P, followed by Ca2-P, mainly in the surface layer. The accumulation and transformation of P in fertilized soil reduced P adsorption and enhanced P desorption. Soils with higher P application levels had higher inorganic P accumulation with lower adsorption and higher desorption. The total P and Olsen-P in a 0- to 5-cm soil layer; Ca8-P and calcium carbonate (CaCO3) in a 5- to 10-cm soil layer; Olsen-P, Ca10-P, clay, and cation exchange capacity in a 10- to 20-cm soil layer; and Olsen-P in a 20- to 40-cm soil layer significantly affected the P adsorption–desorption (p < 0.05). The application rate of 75–150 kg P2O5 ha−1 year−1 produced lower inorganic P accumulation, favorable adsorption–desorption properties, and high cotton yield, and thus could be considered the optimal P fertilizer application level.

The machine learning approaches are applied in the dynamical simulation of open quantum systems. The long short-term memory recurrent neural network (LSTM-RNN) models are used to simulate the long-time quantum dynamics, which are built based on the key information of the short-time evolution. We employ various hyperparameter optimization methods, including the simulated annealing, Bayesian optimization with tree-structured parzen estimator and random search, to achieve the automatic construction and adjustment of the LSTM-RNN models. The implementation details of three hyperparameter optimization methods are examined, and among them the simulated annealing approach is strongly recommended due to its excellent performance. The uncertainties of the machine learning models are comprehensively analyzed by the combination of bootstrap sampling and Monte-Carlo dropout approaches, which give the prediction confidence of the LSTM-RNN models in the simulation of the open quantum dynamics. This work builds an effective machine learning approach to simulate the dynamics evolution of open quantum systems. In addition, the current study provides an efficient protocol to build the optimal neural networks and to estimate the trustiness of the machine learning models.

A high-sensitive DC Magneto-Optical Kerr Effect (MOKE) apparatus is described in this letter. Via detailed analysis on several dominating noise sources, we have proposed solutions that significantly lower the MOKE noise, and a sensitivity of $1.5\times10^{-7} \text{rad}/\sqrt{\text{Hz}}$ is achieved with long-term stability. The sensitivity of the apparatus is tested by measuring a wedge-shaped Ni thin film on $\text{SiO}_2$ with Ni thickness varying from 0 to 3 nm. A noise floor of $1.5\times10^{-8}$ rad is demonstrated. The possibility of further improving sensitivity to $10^{-9}$ rad via applying ac modulation is also discussed., 16 pages, 7 figures

The supervised machine learning (ML) approach is applied to realize the trajectory-based nonadiabatic dynamics within the framework of the symmetrical quasi-classical dynamics method based on the Meyer-Miller mapping Hamiltonian (MM-SQC). After the construction of the long short-term memory recurrent neural network (LSTM-RNN) model, it is used to perform the entire trajectory evolutions from initial sampling conditions. The proposed idea is proven to be reliable and accurate in the simulations of the dynamics of several site-exciton electron-phonon coupling models, which cover two-site and three-site systems with biased and unbiased energy levels, as well as include a few or many phonon modes. The LSTM-RNN approach also shows the powerful ability to obtain the accurate and stable results for the long-time evolutions. It indicates that the LSTM-RNN model perfectly captures of dynamical correction information in the trajectory evolution in the MM-SQC dynamics. Our work provides the possibility to employ the ML methods in the simulation of the trajectory-based nonadiabatic dynamic of complex systems with a large number of degrees of freedoms.

Additional file 1: Figure S1. The PCR identification results of single oocyst strains. Figure S2. Oocyst production of the ethanamizuril sensitive (S) and resistant strains (R10 and R200). Figure S3. Oocyst sporulation of the ethanamizuril sensitive (S) and resistant strains (R10 and R200). Table S1. The schedule for increasing the EZL dosage from 3 to 200 mg/kg in the chicken feed. Table S2. The categorization of 10 groups of drug resistance evaluation test. Table S3. Primers used for qRT-PCR validation. Table S4. The lesion value, oocyst value and ACI value of Eimeria tenella strains against ethanamizuril. Table S5. The percentage of sporulated oocysts of the ethanamizuril sensitive (S) and resistant strains (R10 and R200). Table S8. Differentially expressed proteins in each comparison group. Table S9. Statistical analysis of 86 differentially expressed proteins in R10 vs. S and R200 vs. S comparison groups. Table S10. The reported drug-target in apicomplexan parasites. Supplementary material S1：The calculated method of the four anticoccodial indices.

More than two-thirds of terrestrial plants acquire nutrients by forming a symbiosis with arbuscular mycorrhizal (AM) fungi. AM fungal hyphae recruit distinct microbes into their hyphosphere, the narrow region of soil influenced by hyphal exudates. They thereby shape this so-called second genome of AM fungi, which significantly contributes to nutrient mobilization and turnover. We summarize current insights into characteristics of the hyphosphere microbiome and the role of hyphal exudates on orchestrating its composition. The hyphal exudates not only contain carbon-rich compounds but also promote bacterial growth and activity and influence the microbial community structure. These effects lead to shifts in function and cause changes in organic nutrient cycling, making the hyphosphere a unique and largely overlooked functional zone in ecosystems.

Gegenstand dieser Dissertation ist die Entwicklung von effizienten Verfahren zur Visualisierung und Inspektion der Geometrie von Partikelmischungen. Um das Verhalten der Simulation für die Partikelmischung besser zu verstehen und zu überwachen, sollten nicht nur die Partikel selbst, sondern auch spezielle von den Partikeln gebildete Bereiche, die den Simulationsfortschritt und die räumliche Verteilung von Hotspots anzeigen können, visualisiert werden können. Dies sollte auch bei großen Packungen mit Millionen von Partikeln zumindest mit einer interaktiven Darstellungsgeschwindigkeit möglich sein. . Da die Simulation auf der Grafikkarte (GPU) durchgeführt wird, sollten die Visualisierungstechniken die Daten des GPU-Speichers vollständig nutzen. Um die Qualität von trockenen Partikelmischungen wie Beton zu verbessern, wurde der Korngrößenverteilung große Aufmerksamkeit gewidmet, die die Raumfüllungsrate hauptsächlich beeinflusst und daher zwei der wichtigsten Eigenschaften des Betons bestimmt: die strukturelle Robustheit und die Haltbarkeit. Anhand der Korngrößenverteilung kann die Raumfüllungsrate durch Computersimulationen bestimmt werden, die analytischen Ansätzen in der Praxis wegen der breiten Größenverteilung der Partikel oft überlegen sind. Eine der weit verbreiteten Simulationsmethoden ist das Collective Rearrangement, bei dem die Partikel zunächst an zufälligen Positionen innerhalb eines Behälters platziert werden. Später werden Überlappungen zwischen Partikeln aufgelöst, indem überlappende Partikel voneinander weggedrückt werden. Durch geschickte Anpassung der Behältergröße während der Simulation, kann die Collective Rearrangement-Methode am Ende eine ziemlich dichte Partikelpackung generieren. Es ist jedoch sehr schwierig, den gesamten Simulationsprozess ohne ein interaktives Visualisierungstool zu optimieren oder dort Fehler zu finden. Ausgehend von der etablierten rasterisierungsbasierten Methode zum Darstellen einer großen Menge von Kugeln, bietet diese Dissertation zunächst schnelle und pixelgenaue Methoden zur neuartigen Visualisierung der Überlappungen und Freiräume zwischen kugelförmigen Partikeln innerhalb eines Behälters.. Die auf Rasterisierung basierenden Verfahren funktionieren gut für kleinere Partikelpackungen bis ca. eine Million Kugeln. Bei größeren Packungen entstehen Probleme durch die lineare Laufzeit und den Speicherverbrauch. Zur Lösung dieses Problems werden neue Methoden mit Hilfe von Raytracing zusammen mit zwei neuen Arten von Bounding-Volume-Hierarchien (BVHs) bereitgestellt. Diese können den Raytracing-Prozess deutlich beschleunigen --- die erste kann die vorhandene Datenstruktur für die Simulation wiederverwenden und die zweite ist speichereffizienter. Beide BVHs nutzen die Idee des Loose Octree und sind die ersten ihrer Art, die die Größe von Primitiven für interaktives Raytracing mit häufig aktualisierten Beschleunigungsdatenstrukturen berücksichtigen. Darüber hinaus können die Visualisierungstechniken in dieser Dissertation auch angepasst werden, um Eigenschaften wie das Volumen bestimmter Bereiche zu berechnen. All diese Visualisierungstechniken werden dann auf den Fall nicht-sphärischer Partikel erweitert, bei denen ein nicht-sphärisches Partikel durch ein starres System von Kugeln angenähert wird, um die vorhandene kugelbasierte Simulation wiederverwenden zu können. Dazu wird auch eine neue GPU-basierte Methode zum effizienten Füllen eines nicht-kugelförmigen Partikels mit polydispersen überlappenden Kugeln vorgestellt, so dass ein Partikel mit weniger Kugeln gefüllt werden kann, ohne die Raumfüllungsrate zu beeinträchtigen. Dies erleichtert sowohl die Simulation als auch die Visualisierung. Basierend auf den Arbeiten in dieser Dissertation können ausgefeiltere Algorithmen entwickelt werden, um großskalige nicht-sphärische Partikelmischungen effizienter zu visualisieren. Weiterhin kann in Zukunft Hardware-Raytracing neuerer Grafikkarten anstelle des in dieser Dissertation eingesetzten Software-Raytracing verwendet werden. Die neuen Techniken können auch als Grundlage für die interaktive Visualisierung anderer partikelbasierter Simulationen verwendet werden, bei denen spezielle Bereiche wie Freiräume oder Überlappungen zwischen Partikeln relevant sind., The aim of this dissertation is to find efficient techniques for visualizing and inspecting the geometry of particle packings. Simulations of such packings are used e.g. in material sciences to predict properties of granular materials. To better understand and supervise the behavior of these simulations, not only the particles themselves but also special areas formed by the particles that can show the progress of the simulation and spatial distribution of hot spots, should be visualized. This should be possible with a frame rate that allows interaction even for large scale packings with millions of particles. Moreover, given the simulation is conducted in the GPU, the visualization techniques should take full use of the data in the GPU memory. To improve the performance of granular materials like concrete, considerable attention has been paid to the particle size distribution, which is the main determinant for the space filling rate and therefore affects two of the most important properties of the concrete: the structural robustness and the durability. Given the particle size distribution, the space filling rate can be determined by computer simulations, which are often superior to analytical approaches due to irregularities of particles and the wide range of size distribution in practice. One of the widely adopted simulation methods is the collective rearrangement, for which particles are first placed at random positions inside a container, later overlaps between particles will be resolved by letting overlapped particles push away from each other to fill empty space in the container. By cleverly adjusting the size of the container according to the process of the simulation, the collective rearrangement method could get a pretty dense particle packing in the end. However, it is very hard to fine-tune or debug the whole simulation process without an interactive visualization tool. Starting from the well-established rasterization-based method to render spheres, this dissertation first provides new fast and pixel-accurate methods to visualize the overlaps and free spaces between spherical particles inside a container. The rasterization-based techniques perform well for small scale particle packings but deteriorate for large scale packings due to the large memory requirements that are hard to be approximated correctly in advance. To address this problem, new methods based on ray tracing are provided along with two new kinds of bounding volume hierarchies (BVHs) to accelerate the ray tracing process --- the first one can reuse the existing data structure for simulation and the second one is more memory efficient. Both BVHs utilize the idea of loose octree and are the first of their kind to consider the size of primitives for interactive ray tracing with frequently updated acceleration structures. Moreover, the visualization techniques provided in this dissertation can also be adjusted to calculate properties such as volumes of the specific areas. All these visualization techniques are then extended to non-spherical particles, where a non-spherical particle is approximated by a rigid system of spheres to reuse the existing simulation. To this end a new GPU-based method is presented to fill a non-spherical particle with polydisperse possibly overlapping spheres efficiently, so that a particle can be filled with fewer spheres without sacrificing the space filling rate. This eases both simulation and visualization. Based on approaches presented in this dissertation, more sophisticated algorithms can be developed to visualize large scale non-spherical particle mixtures more efficiently. Besides, one can try to exploit the hardware ray tracing of more recent graphic cards instead of maintaining the software ray tracing as in this dissertation. The new techniques can also become the basis for interactively visualizing other particle-based simulations, where special areas such as free space or overlaps between particles are of interest.

Cognitive impairments are a core feature of schizophrenia that have negative impacts on functional outcomes. However, it remains challenging to assess these impairments in clinical settings. Smartphone apps provide the opportunity to measure cognitive impairments in an accessible way; however, more research is needed to validate these cognitive assessments in schizophrenia. We assessed the initial accessibility, validity, and reliability of a smartphone-based cognitive test to measure cognition in schizophrenia. A total of 29 individuals with schizophrenia and 34 controls were included in the analyses. Participants completed the standard pen-and-paper Trail Making Tests (TMT) A and B, and smartphone-based versions, Jewels Trail Tests (JTT) A and B, at the single in-lab visit. Participants were asked to complete the JTT remotely once per week for three months. We also investigated how subjective sleep quality and mood may affect cognitive performance longitudinally. In-lab and remote JTT scores moderately and positively correlated with in-lab TMT scores. Moderate test-retest reliability was observed across the in-lab, first remote, and last remote completion times of the JTT. Additionally, individuals with schizophrenia had significantly lower performance compared to controls on both the in-lab JTT and TMT. Self-reported mood had a significant effect on JTT A performance over time but no other significant relationships were found remotely. Our results support the initial accessibility, validity and reliability of using the JTT to measure cognition in schizophrenia. Future research to develop additional smartphone-based cognitive tests as well as with larger samples and in other psychiatric populations are warranted.

With the progress of the aging population, bone-related diseases such as osteoporosis and osteoarthritis have become urgent problems. Recent studies have demonstrated the importance of osteoclasts in bone homeostasis, implying these will be an important mediator in the treatment of bone-related diseases. Up to now, several reviews have been performed on part of osteoclast biological behaviors such as differentiation, function, or apoptosis. However, few reviews have shown the complete osteoclast biology and research advances in recent years. Therefore, in this review, we focus on the origin, differentiation, apoptosis, behavior changes and coupling signals with osteoblasts, providing a simple but comprehensive overview of osteoclasts for subsequent studies.

Maximizing the function of indigenous arbuscular mycorrhizal (AM) fungi by choosing specific crop genotypes offers one of the few untapped opportunities to improve the sustainability of agriculture. In this study, the differences in mycorrhizal responsiveness (MR) in plant growth and shoot phosphorus (P) content among cotton (Gossypium spp. L.) genotypes from different release dates were compared and then the relationships between MR and P uptake-related traits were determined. The experimental design in a greenhouse included 24 genotypes released from 1950 to present in Xinjiang Province, inoculation with or without AM fungi, and P levels (15 and 150 mg P kg–1 added as KH2PO4). Results showed that the modern cotton genotypes exhibited a higher degree of mycorrhizal colonization, the hyphal length density (HLD), and mycorrhizae-induced changes in shoot growth than the old genotypes when inoculated with indigenous AM fungi at both the P levels. Moreover, MR was highly correlated with the HLD at low P levels and the HLD may provide useful insights for future cotton breeding aimed at delivering crop genotypes that can benefit more from AM fungi.

Sustainable phosphorus (P) management presents challenges in crop production and environmental protection; the current understanding of chemical P-fertilizer manufacturing, rock phosphate (RP) mining, P loss within supply chains, and strategies to mitigate loss is incomplete because of a fragmented understanding of P in the crop production supply chain. Therefore, we develop a knowledge-based management theoretical framework to analyze P supply chains to explore ways to mitigate China's P crisis. This framework connects upstream P industries and crop production, addressing knowledge gaps and stakeholder involvement. We demonstrate the potential to improve P use efficiency in the supply chain, thereby mitigating the P crisis using optimized P management. Our results showed that P footprint and grain production demand for RP can be reduced without yield penalty using a crop-demand-oriented P supply chain management that integrates P use in crop production, P-fertilizer manufacturing, and RP mining. Food security and P-related environment sustainability can be achieved by sharing responsibility and knowledge among stakeholders. QC 20220207

Aims: The benefits of arbuscular mycorrhizal fungi (AMF) on yield and phosphorus (P) uptake of crops have commonly been studied by inoculating a single mycorrhizal fungal species in pot experiments. Yet, how the native AMF community affects the performance of different maize varieties under field conditions remains obscure. Methods: In-growth cores with and without rotation were used in three soils that differed in P application to assess shoot biomass, P uptake, and mycorrhizal colonization of three maize varietal groups, encompassing four inbred lines, 12 hybrids, and four landraces. Results: Rotating cores drastically reduced mycorrhizal colonization, biomass and P uptake for each varietal group at every P level. Performance of plants at natural mycorrhizal colonization at 30 kg P ha−1 was equal to that of reduced-mycorrhizal plants at 60 kg P ha−1, suggesting the potential for adequate mycorrhizal management to save P fertilizer. Conclusion: There were no significant differences between varietal groups for mycorrhizal responsiveness, confirming that the ability to associate with and benefit from AMF has been maintained in modern breeding. Mycorrhizal plants both exhibited higher P acquisition efficiency and higher P use efficiency than reduced-mycorrhizal plants. Disadvantages of in-growth cores should be duly considered.