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Abstract Platinum-based neoadjuvant chemotherapy (NACT) followed by radical hysterectomy has been proposed as an alternative treatment approach for cervical cancer (CC) in stage Ib2-IIb, who had a strong desire to be treated with surgery. Our study aims to develop a model based on multimodal MRI by using radiomics and deep learning to predict the treatment response in CC patients treated with neoadjuvant chemoradiotherapy (NACRT). From August 2009 to June 2013, CC patients in stage Ib2-IIb (FIGO 2008) who received NACRT at Fujian Cancer Hospital were enrolled in our study. Clinical information, contrast-enhanced T1-weighted imaging (CE-T1WI), and T2-weighted imaging (T2WI) data were respectively collected. Radiomic features and deep abstract features were extracted from the images using radiomics and deep learning models, respectively. Then, ElasticNet and SVM-RFE were employed for feature selection to construct four single-sequence feature sets. Early fusion of two multi-sequence feature sets and one hybrid feature set were performed, followed by classification prediction using four machine learning classifiers. Subsequently, the performance of the models in predicting the response to NACRT was evaluated by separating patients into training and validation sets. Additionally, overall survival (OS) and disease-free survival (DFS) were assessed using Kaplan-Meier survival curves. Among the four machine learning models, SVM exhibited the best predictive performance (AUC=0.86). Among the seven feature sets, the hybrid feature set achieved the highest values for AUC (0.86), ACC (0.75), Recall (0.75), Precision (0.81), and F1-score (0.75) in the validation set, outperforming other feature sets. Furthermore, the predicted outcomes of the model were closely associated with patient OS and DFS (p = 0.0044; p = 0.0039). A model based on MRI images with features from multiple sequences and different methods could precisely predict the response to NACRT in CC patients. This model could assist clinicians in devising personalized treatment plans and predicting patient survival outcomes.

Abstract The efficiency and stability of perovskite module devices are mainly limited by the quality of scalable perovskite films and sub-cells’ lateral contact. Here, firstly, we report constant low temperature substrate to regulate the growth of perovskite intermediate films to slow down the crystallization for obtaining high-quality homogeneous perovskite films in large scale size, which avoid the effect of the ambient temperature on the film quality. Secondly, a scribing step named P1.5 was added before the top function layers deposition, the diffusion barrier layer can be formed “naturally” at the interconnection interface without introducing any additional materials, which well alleviates the diffusion degradation process. As a result, our inverted perovskite devices exhibit a very small efficiency loss with area expansion comparable to other photovoltaic devices (for example, Cadmium Telluride), the perovskite module (aperture area 14.61 cm2) shows a certified quasi-steady-state power conversion efficiency of 22.73%, and the module maintaining over 90% of its initial efficiency after 1000 hours of continuous operation under illumination.

Abstract In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus. The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus. Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

Non-alcoholic fatty liver disease (NAFLD) is a clinicopathologic syndrome characterized by excessive fat deposition in hepatocytes and a major cause of end-stage liver disease. Autophagy is a metabolic pathway responsible for degrading cytoplasmic products and damaged organelles, playing a pivotal role in maintaining the homeostasis and functionality of hepatocytes. Recent studies have shown that pharmacological intervention to activate or restore autophagy provides benefits for liver function recovery by promoting the clearance of lipid droplets (LDs) in hepatocytes, decreasing the production of pro-inflammatory factors, and inhibiting activated hepatic stellate cells (HSCs), thus improving liver fibrosis and slowing down the progression of NAFLD. This article summarizes the physiological process of autophagy, elucidates the close relationship between NAFLD and autophagy, and discusses the effects of drugs on autophagy and signaling pathways from the perspectives of hepatocytes, kupffer cells (KCs), and HSCs to provide assistance in the clinical management of NAFLD.

Background and aimMetabolic-associated fatty liver disease (MAFLD) has gradually become one of the main health concerns regarding liver diseases. Postmenopausal women represent a high-risk group for MAFLD; therefore, it is of great importance to identify and intervene with patients at risk at an early stage. This study established a predictive nomogram model of MAFLD in postmenopausal women and to enhance the clinical utility of the new model, the researchers limited variables to simple clinical and laboratory indicators that are readily obtainable.MethodsData of 942 postmenopausal women from January 2023 to October 2023 were retrospectively collected and divided into two groups according to the collection time: the training group (676 cases) and the validation group (226 cases). Significant indicators independently related to MAFLD were identified through univariate logistic regression and stepwise regression, and the MAFLD prediction nomogram was established. The C-index and calibration curve were used to quantify the nomogram performance, and the model was evaluated by measuring the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).ResultsOf 37 variables, 11 predictors were identified, including occupation (worker), body mass index, waist-to-hip ratio, number of abortions, anxiety, hypertension, hyperlipidemia, diabetes, hyperuricemia, and diet (meat and processed meat). The C-index of the training group predicting the related risk factors was 0.827 (95% confidence interval [CI] 0.794–0.860). The C-index of the validation group was 0.787 (95% CI 0.728–0.846). Calibration curves 1 and 2 (BS1000 times) were close to the diagonal, showing a good agreement between the predicted probability and the actual incidence in the two groups. The AUC of the training group was 0.827, the sensitivity was 0.784, and the specificity was 0.735. The AUC of the validation group was 0.787, the sensitivity was 0.674, and the specificity was 0.772. The DCA curve showed that the nomogram had a good net benefit in predicting MAFLD in postmenopausal women.ConclusionsA predictive nomogram for MAFLD in postmenopausal women was established and verified, which can assist clinicians in evaluating the risk of MAFLD at an early stage.

BackgroundPrevious observational studies have demonstrated a link between diabetes mellitus(DM) and primary biliary cholangitis (PBC). Nevertheless, since these relationships might be confused, whether there is any causal connection or in which direction it exists is unclear. Our investigation aimed to identify the causal associations between DM and PBC.MethodsWe acquired genome-wide association study (GWAS) datasets for PBC, Type 1 diabetes(T1DM), and Type 2 diabetes(T2DM) from published GWASs. Inverse variance-weighted (IVW), MR-Egger, weighted median (WM), Simple mode, and weighted mode methods were used to determine the causal relationships between DM(T1DM or T2DM) and PBC. Sensitivity analyses were also carried out to ensure the results were robust. To determine the causal relationship between PBC and DM(T1DM or T2DM), we also used reverse MR analysis.ResultsT1DM was associated with a higher risk of PBC (OR 1.1525; 95% CI 1.0612-1.2517; p = 0.0007) in the IVW method, but no evidence of a causal effect T2DM on PBC was found (OR 0.9905; 95% CI 0.8446-1.1616; p = 0.9071) in IVW. Results of the reverse MR analysis suggested genetic susceptibility that PBC was associated with an increased risk of T1DM (IVW: OR 1.1991; 95% CI 1.12-1.2838; p = 1.81E-07), but no evidence of a causal effect PBC on T2DM was found (IVW: OR 1.0101; 95% CI 0.9892-1.0315; p = 0.3420).ConclusionThe current study indicated that T1DM increased the risk of developing PBC and vice versa. There was no proof of a causal connection between PBC probability and T2DM. Our results require confirmation through additional replication in larger populations.

The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32 % accuracy improvement than supervised deep learning methods. It is also 33 % more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 min.

Abstract As an unconventional oil and gas resource, coalbed methane has become a key area of unconventional oil and gas exploration worldwide, and hydraulic fracturing is the critical technology for the efficient stimulation of coalbed methane. However, due to the strong heterogeneity of deep coal seam reservoirs and the development of natural cleat fractures, the fracture propagation path is quite complex and difficult to capture. In this study, we propose a hydraulic fracture propagation simulation method using the ABAQUS Software for natural cleat fracture networks and a fluid–solid fully coupled two‐dimensional finite element model with the global embedded cohesive zone model (CZM). CZM is established to simulate the propagation of hydraulic fractures in the heterogeneous combination of coal rock and mudstone. The accuracy of this model is verified by using Blanton's experiment criterion. Finally, the model is used to simulate the influence of cleat angle, cleat density, length ratio of coal rock and mudstone combination, and construction displacement on the propagation behavior of hydraulic fractures. This study aims to deepen the understanding of the mechanism of hydraulic fracture propagation in deep coal seams and provides guidance for deep coal seam fracturing and hydraulic fracturing design.

Yellow wine fermented from highland barley is an alcoholic beverage with high nutritional value. However, the industrialization of barley yellow wine has been constrained to a certain extent due to the lack of a systematic starter culture. Therefore, the present study aims to simulate barley yellow wine fermentation using a starter culture consisting of Rhizopus arrhizus, Saccharomyces cerevisiae, Pichia kudriavzevii, and Lacticaseibacillus rhamnosus. In this study, changes in enzyme activity, fermentation characteristics, volatile substance production, and amino acid content during the fermentation of highland barley yellow wine brewed with different starter cultures were evaluated. The results of this study show that regulating the proportion of mixed starter bacteria can effectively control the various stages of the fermentation process and improve the organoleptic characteristics and quality of yellow wine to varying degrees. Additionally, we found that the addition of probiotics could effectively improve the palatability of yellow wine. To the best of our knowledge, we have validated for the first time the use of the above multispecies starter culture, consisting of R. arrhizus, S. cerevisiae, P. kudriavzevii, and L. rhamnosus, in the production of highland barley yellow wine. The obtained findings provided reference data for optimizing highland barley yellow wine fermentation.

This paper aims to analyze the influencing factors of innovation and entrepreneurship of college students. By studying the framework of the TRIZ theory system, this paper summarizes the common principles of entrepreneurship, realizes the construction of a conflict matrix, establishes entrepreneurship evaluation indexes, and determines the weights of evaluation indexes by constructing a judgment matrix. Then, based on the theory, the influence of each factor on the innovation and entrepreneurship of college students is analyzed in terms of participation status, main obstacle factors, personal trait influence, market influence, and social and governmental support. As for the influence of main external factors, 43.57% of students chose “shortage of funds for innovation and entrepreneurship”, 42.04% of students chose “lack of creativity and cannot find a good direction for innovation and entrepreneurship”, 37.45% of students choose 37.45% of students chose “lack of good innovation and entrepreneurship projects and innovative teams”. In terms of personal traits, innovative thinking, stress resistance, social experience, leadership and coordination, risk tolerance, self-efficacy, and self-drive all affect the decision and effect of entrepreneurship. Support from the government and society is also beneficial for college students to carry out entrepreneurial activities. Innovative entrepreneurial ability is a comprehensive ability influenced by multiple factors and needs to be considered comprehensively in the analysis.

We study the Zcs(3985) and Zcs(4000) exotic states in the decays of Λb baryons through a molecular scenario. In the final state interaction, the Λb→Λc+Ds(⁎)− decays are followed by the Λc+Ds(⁎)− to Zcs−p rescatterings via exchange of a D(⁎) meson. We predict a branching fraction of (3.1−2.6+1.4)×10−4 for Λb→Zcs−p, which can be measured in the Λb→J/ψK(⁎)−p decay. This study proposes a new approach to test the molecular model, and guides future experimental searches for the Zcs(3985) and Zcs(4000).

Liver cancer manifests as a profoundly heterogeneous malignancy, posing significant challenges in terms of both therapeutic intervention and prognostic evaluation. Given that the liver is the largest metabolic organ, a prognostic risk model grounded in single-cell transcriptome analysis and a metabolic perspective can facilitate precise prevention and treatment strategies for liver cancer. Hence, we identified 11 cell types in a scRNA-seq profile comprising 105,829 cells and found that the metabolic activity of malignant cells increased significantly. Subsequently, a prognostic risk model incorporating tumor heterogeneity, cell interactions, tumor cell metabolism, and differentially expressed genes was established based on eight genes; this model can accurately distinguish the survival outcomes of liver cancer patients and predict the response to immunotherapy. Analyzing the immune status and drug sensitivity of the high- and low-risk groups identified by the model revealed that the high-risk group had more active immune cell status and greater expression of immune checkpoints, indicating potential risks associated with liver cancer-targeted drugs. In summary, this study provides direct evidence for the stratification and precise treatment of liver cancer patients, and is an important step in establishing reliable predictors of treatment efficacy in liver cancer patients.

In recent years, heavy metal pollution has become increasingly prominent, severely damaging ecosystems and biodiversity, and posing a serious threat to human health. However, the results of current methods for heavy metal restoration are not satisfactory, so it is urgent to find a new and effective method. Peptides are the units that make up proteins, with small molecular weights and strong biological activities. They can effectively repair proteins by forming complexes, reducing heavy metal ions, activating the plant’s antioxidant defense system, and promoting the growth and metabolism of microorganisms. Peptides show great potential for the remediation of heavy metal contamination due to their special structure and properties. This paper reviews the research progress in recent years on the use of peptides to remediate heavy metal pollution, describes the mechanisms and applications of remediation, and provides references for the remediation of heavy metal pollution.

Microplastics (MPs), found in many places around the world, are thought to be more detrimental than other forms of plastics. At present, physical, chemical, and biological methods are being used to break down MPs. Compared with physical and chemical methods, biodegradation methods have been extensively studied by scholars because of their advantages of greenness and sustainability. There have been numerous reports in recent years summarizing the microorganisms capable of degrading MPs. However, there is a noticeable absence of a systematic summary on the technology for breeding strains that can degrade MPs. This paper summarizes the strain-breeding technology of MP-degrading strains for the first time in a systematic way, which provides a new idea for the breeding of efficient MP-degrading strains. Meanwhile, potential techniques for breeding bacteria that can degrade MPs are proposed, providing a new direction for selecting and breeding MP-degrading bacteria in the future. In addition, this paper reviews the sources and pollution status of soil MPs, discusses the current challenges related to the biodegradation of MPs, and emphasizes the safety of MP biodegradation.

Photosynthetic induction and stomatal kinetics are acknowledged as pivotal factors in regulating both plant growth and water use efficiency under fluctuating light conditions. However, the considerable variability in methodologies and light regimes used to assess the dynamics of photosynthesis (A) and stomatal conductance (gs) during light induction across studies poses challenges for comparison across species. Moreover, the influence of stomatal morphology on both steady-state and non-steady-state gs remains poorly understood. In this study, we show the strong impact of IRGA Chamber Illumination and Whole Plant Illumination on the photosynthetic induction of two rice species. Our findings reveal that these illuminations significantly enhance photosynthetic induction by modulating both stomatal and biochemical processes. Moreover, we observed that a higher density of smaller stomata plays a critical role in enhancing the stomatal opening and photosynthetic induction to fluctuating light conditions, although it exerts minimal influence on steady-state gs and A under constant light conditions. Therefore, future studies aiming to estimate photosynthetic induction and stomatal kinetics should consider the light environments at both the leaf and whole plant levels.

Since industrialization, global temperatures have continued to rise. Human activities have resulted in heavy metals being freed from their original, fixed locations. Because of global warming, glaciers are melting, carbon dioxide concentrations are increasing, weather patterns are shifting, and various environmental forces are at play, resulting in the movement of heavy metals and alteration of their forms. In this general context, the impact of heavy metals on ecosystems and organisms has changed accordingly. For most ecosystems, the levels of heavy metals are on the rise, and this rise can have a negative impact on the ecosystem as a whole. Numerous studies have been conducted to analyze the combined impacts of climate change and heavy metals. However, the summary of the current studies is not perfect. Therefore, this review discusses how heavy metals affect ecosystems during the process of climate change from multiple perspectives, providing some references for addressing the impact of climate warming on environmental heavy metals.

The diversity of alcohol beverage microorganisms is of great significance for improving the brewing process and the quality of alcohol beverage products. During the process of making alcoholic beverages, a group of microorganisms, represented by yeast and lactic acid bacteria, conducts fermentation. These microorganisms have complex synergistic or competitive relationships, and the participation of different microorganisms has a major impact on the fermentation process and the flavor and aroma of the product. Strain selection is one of the key steps. Utilizing scientific breeding technology, the relationship between strains can be managed, the composition of the alcoholic beverage microbial community can be improved, and the quality and flavor of the alcoholic beverage products can be increased. Currently, research on the microbial diversity of alcohol beverages has received extensive attention. However, the selection technology for dominant bacteria in alcohol beverages has not yet been systematically summarized. To breed better-quality alcohol beverage strains and improve the quality and characteristics of wine, this paper introduces the microbial diversity characteristics of the world’s three major brewing alcohols: beer, wine, and yellow wine, as well as the breeding technologies of related strains. The application of culture selection technology in the study of microbial diversity of brewed wine was reviewed and analyzed. The strain selection technology and alcohol beverage process should be combined to explore the potential application of a diverse array of alcohol beverage strains, thereby boosting the quality and flavor of the alcohol beverage and driving the sustainable development of the alcoholic beverage industry.

This study utilized 16S rRNA high-throughput sequencing technology to analyze the community structure and function of endophytic bacteria within the roots of three plant species in the vanadium–titanium–magnetite (VTM) mining area. The findings indicated that mining activities of VTM led to a notable decrease in both the biodiversity and abundance of endophytic bacteria within the root systems of Eleusine indica and Carex (p < 0.05). Significant reductions were observed in the populations of Nocardioides, concurrently with substantial increments in the populations of Pseudomonas (p < 0.05), indicating that Pseudomonas has a strong adaptability to this environmental stress. In addition, β diversity analysis revealed divergence in the endophytic bacterial communities within the roots of E. indica and Carex from the VTM mining area, which had diverged to adapt to the environmental stress caused by mining activity. Functional enrichment analysis revealed that VTM mining led to an increase in polymyxin resistance, nicotinate degradation I, and glucose degradation (oxidative) (p < 0.05). Interestingly, we found that VTM mining did not notably alter the endophytic bacterial communities or functions in the root systems of Dodonaea viscosa, indicating that this plant can adapt well to environmental stress. This study represents the primary investigation into the influence of VTM mining activities on endophytic bacterial communities and the functions of nearby plant roots, providing further insight into the impact of VTM mining activities on the ecological environment.

Mining activities in the kaolin mining area have led to the disruption of the ecological health of the mining area and nearby soils, but the effects on the fungal communities in the rhizosphere soils of the plants are not clear. Three common plants (Conyza bonariensis, Artemisia annua, and Dodonaea viscosa) in kaolin mining areas were selected and analyzed their rhizosphere soil fungal communities using ITS sequencing. The alpha diversity indices (Chao1, Shannon, Simpson, observed-species, pielou-e) of the fungal communities decreased to different extents in different plants compared to the non-kauri mining area. The β-diversity (PCoA, NMDS) analysis showed that the rhizosphere soil fungal communities of the three plants in the kaolin mine area were significantly differentiated from those of the control plants grown in the non-kaolin mine area, and the extent of this differentiation varied among the plants. The analysis of fungal community composition showed that the dominant fungi in the rhizosphere fungi of C. bonariensis and A. annua changed, with an increase in the proportion of Mycosphaerella (genus) by about 20% in C. bonariensis and A. annua. An increase in the proportion of Didymella (genus) by 40% in D. viscosa was observed. At the same time, three plant rhizosphere soils were affected by kaolin mining activities with the appearance of new fungal genera Ochrocladosporium and Plenodomus. Predictive functional potential analysis of the samples revealed that a significant decrease in the potential of functions such as biosynthesis and glycolysis occurred in the rhizosphere fungal communities of kaolin-mined plants compared to non-kaolin-mined areas. The results show that heavy metals and plant species are the key factors influencing these changes, which suggests that selecting plants that can bring more abundant fungi can adapt to heavy metal contamination to restore soil ecology in the kaolin mining area.

A series of chromone-thiazolidine-2,4-dione derivatives (e1 ∼ 28) were synthesized and screened for their α-glucosidase inhibitory. All synthetic derivatives presented excellent α-glucosidase inhibitory with IC50 values ranging from 2.40 ± 0.11 to 5.66 ± 0.15 μM, comparing to positive control acarbose (IC50 value: 640.57 ± 5.13 μM). Among them, compound e28 displayed the strongest α-glucosidase inhibitory (IC50 value: 2.40 ± 0.11), ∼267 times stronger than positive control acarbose. Kinetic studies revealed that compound e28 was a reversible non-competitive inhibitor. CD spectra and 3D fluorescence spectra results explained that compound e28 changed the conformational changes of α-glucosidase. Molecular docking simulated the binding between compound e28 and α-glucosidase. In vitro cytotoxicity assay ascertained the good security of e28.

In this study, we successfully synthesized a novel glycyrrhetinic acid (GA) derivate compound as a liposomal carrier. Glycyrrhetinic acid-diaminododecane-cholesterol (GA-DA-CH) was synthesized from GA, diaminododecane, and cholesteryl hemisuccinate by two-step amidation under catalytic conditions. The chemical structures of GA-DA (glycyrrhetinic acid-diaminododecane) and GA-DA-CH were confirmed by Mass Spectrum (MS), Nuclear Magnetic Resonance (NMR) spectrometer, and analyzed by Fourier Transform Infrared spectroscopy (FTIR), High-Performance Liquid Chromatography (HPLC). Glycyrrhetinic acid ligand-modified liposomes (GA-DA-CH-Lips) were prepared, consisting of egg phosphatidylcholine, cholesterol and GA-DA-CH. GA-DA-CH was integrated into the liposomal capsule to promote hepatocellular carcinoma targeting. The particle size of GA-DA-CH-Lips was calculated to be between 122.87 and 133.30 nm, with an approximate polydispersity index (PDI) was 0.20, and a zeta potential was in the range of –32.50 to –26.53 mV. GA-DA-CH-Lips were constructed with more than 90% encapsulation efficient and drug loading efficiency of no

Polaron formation is considered to play a crucial role to enhance photoelectric performance of hybrid halide perovskites. Here, the authors report the real-time observation of polaron formation process by terahertz emission spectroscopy and reveal two different polaron modes in FAPbI3 films.

Chlorophyll content and fluorescence parameters are crucial indicators to evaluate the light use efficiency in rice; however, the correlations among these parameters and the underlying genetic mechanisms remain poorly understood. Here, to clarify these issues, we conducted a genome-wide association study (GWAS) on 225 rice accessions. In the phenotypic and Mendelian randomization (MR) analysis, a weak negative correlation was observed between the chlorophyll content and actual quantum yield of photosystem II (ΦII). The phenotypic diversity observed in SPAD, NPQt, ΦNPQ, and Fv/Fm among accessions was affected by genetic background. Furthermore, the GWAS identified 78 SNPs and 17 candidate genes significantly associated with SPAD, NPQt, ΦII, ΦNPQ, qL and qP. Combining GWAS on 225 rice accessions with transcriptome analysis of two varieties exhibiting distinct fluorescence characteristics revealed two potential candidate genes (Os03g0583000 from ΦII & qP traits and Os06g0587200 from NPQt trait), which are respectively associated with peroxisomes, and protein kinase catalytic domains might involve in regulating the chlorophyll content and chlorophyll fluorescence. This study provides novel insights into the correlation among chlorophyll content and fluorescence parameters and the genetic mechanisms in rice, and offers valuable information for the breeding of rice with enhanced photosynthetic efficiency.

An analysis of the J/ψ→ηη′γ decay by the BESIII collaboration claims the observation of an exotic state η1(1855) with IGJPC=0+1−+. To establish its C-parity partner η1′(1855) in the picture of the KK¯1(1400) molecular state, we propose that J/ψ→η1′(1855)η(′) receives the main contributions from the final state interaction of KK⁎(K+K⁎−, K−K⁎+, K0K¯⁎0, and K¯0K⁎0). Specifically, K and K⁎ in J/ψ→KK⁎ decays transform as η1′(1855)η(′), by exchanging a K1(1400). We predict B(J/ψ→η1′(1855)η)=(6.3−3.5+12.6)×10−6, and B(J/ψ→η1′(1855)η′)=(6.5−4.6+6.6)×10−6, which can be studied in the J/ψ→K⁎K¯⁎η(′) decays.

Different oleanolic acid (OA) oxime ester derivatives (3a-3t) were designed and synthesised to develop inhibitors against α-glucosidase and α-amylase. All the synthesised OA derivatives were evaluated against α-glucosidase and α-amylase in vitro. Among them, compound 3a showed the highest α-glucosidase inhibition with an IC50 of 0.35 µM, which was ∼1900 times stronger than that of acarbose, meanwhile compound 3f exhibited the highest α-amylase inhibitory with an IC50 of 3.80 µM that was ∼26 times higher than that of acarbose. The inhibition kinetic studies showed that the inhibitory mechanism of compounds 3a and 3f were reversible and mixed types towards α-glucosidase and α-amylase, respectively. Molecular docking studies analysed the interaction between compound and two enzymes, respectively. Furthermore, cytotoxicity evaluation assay demonstrated a high level of safety profile of compounds 3a and 3f against 3T3-L1 and HepG2 cells.Highlights Oleanolic acid oxime ester derivatives (3a–3t) were synthesised and screened against α-glucosidase and α-amylase. Compound 3a showed the highest α-glucosidase inhibitory with IC50 of 0.35 µM. Compound 3f presented the highest α-amylase inhibitory with IC50 of 3.80 µM. Kinetic studies and in silico studies analysed the binding between compounds and α-glucosidase or α-amylase.

A novel series of thirty coumarin derivatives (4a ∼ r, 5a ∼ l) constituted by coumarin and cinnamic acid/benzoic acid through oxime linkage were synthesized and evaluated for their potential anti-tyrosinase activity. Among them, compound 5l exhibited outstanding anti-tyrosinase activity with IC50 of 3.04 ± 0.01 μM compared to 14.13 ± 0.80 μM of kojic acid. Kinetic study revealed compound 5l to be a reversible and uncompetitive tyrosinase inhibitor. 3D fluorescence and CD spectra results showed treatment of compound 5l lead to the conformational changes of tyrosinase. Molecular docking revealed the binding between compound 5l and tyrosinase. Furthermore, compound 5l inhibited melanin content and cellular tyrosinase activity both in B16F10 cells and zebrafish model with no toxicity effect. Taken together, our findings suggested that compound 5l could be used as potential candidate to relieve tyrosinase-related hyperpigmentation.

IntroductionCodon usage bias is a prevalent phenomenon observed across various species and genes. However, the specific attributes of codon usage in the mitochondrial genome of Ganoderma species remain unknown.MethodsIn this study, we investigated the codon bias of 12 mitochondrial core protein-coding genes (PCGs) in 9 Ganoderma species, including 13 Ganoderma strains.ResultsThe codons of all Ganoderma strains showed a preference for ending in A/T. Additionally, correlations between codon base composition and the codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) were identified, demonstrating the impact of base composition on codon bias. Various base bias indicators were found to vary between or within Ganoderma strains, including GC3s, the CAI, the CBI, and the FOP. The results also revealed that the mitochondrial core PCGs of Ganoderma have an average effective number of codons (ENC) lower than 35, indicating strong bias toward certain codons. Evidence from neutrality plot and PR2-bias plot analysis indicates that natural selection is a major factor affecting codon bias in Ganoderma. Additionally, 11 to 22 optimal codons (ΔRSCU>0.08 and RSCU>1) were identified in 13 Ganoderma strains, with GCA, AUC, and UUC being the most widely used optimal codons in Ganoderma. By analyzing the combined mitochondrial sequences and relative synonymous codon usage (RSCU) values, the genetic relationships between or within Ganoderma strains were determined, indicating variations between them. Nevertheless, RSCU-based analysis illustrated the intra- and interspecies relationships of certain Ganoderma species.DiscussionThis study deepens our insight into the synonymous codon usage characteristics, genetics, and evolution of this important fungal group.

In this article, a series of betulinic acid derivatives (3a ∼ 3u, 4a ∼ 4e) were synthesized through a stepwise structure optimization and evaluated for their anti-α-glucosidase activities. All synthesized derivatives exhibited stronger anti-α-glucosidase activities (IC50: 0.56 ± 0.05 ∼ 3.99 ± 0.23 μM) than betulinic acid (IC50: 7.21 ± 0.58 μM) and acarbose (IC50: 611.45 ± 15.51 μM). Compound 3q presented the outstanding inhibitory activity (IC50: 0.56 ± 0.05 μM), which was ∼ 1100 time stronger than that of acarbose. Compound 3q was revealed as a reversible and noncompetitive α-glucosidase inhibitor by inhibitory mechanism assay. Fluorescence spectra, 3D fluorescence and CD spectra results showed that the interaction of compound 3q with α-glucosidase caused the conformational and secondary structure content change of α-glucosidase. Finally, the molecular docking simulated the interaction between compound 3q with α-glucosidase and the physicochemical parameter was assessed using SwissADME software.

IntroductionCodon basis is a common and complex natural phenomenon observed in many kinds of organisms.MethodsIn the present study, we analyzed the base bias of 12 mitochondrial core protein-coding genes (PCGs) shared by nine Amanita species.ResultsThe results showed that the codons of all Amanita species tended to end in A/T, demonstrating the preference of mitochondrial codons of Amanita species for a preference for this codon. In addition, we detected the correlation between codon base composition and the codon adaptation index (CAI), codon bias index (CBI), and frequency of optimal codons (FOP) indices, indicating the influence of base composition on codon bias. The average effective number of codons (ENC) of mitochondrial core PCGs of Amanita is 30.81, which is 0.08 and RSCU > 1) in nine Amanita species, and GCA and AUU were the most widely used optimal codons. Based on the combined mitochondrial sequence and RSCU value, we deduced the genetic relationship between different Amanita species and found large variations between them.DiscussionThis study promoted the understanding of synonymous codon usage characteristics and evolution of this important fungal group.

Deep neural networks have demonstrated great potential in solving dipole inversion for Quantitative Susceptibility Mapping (QSM). However, the performances of most existing deep learning methods drastically degrade with mismatched sequence parameters such as acquisition orientation and spatial resolution. We propose an end-to-end AFfine Transformation Edited and Refined (AFTER) deep neural network for QSM, which is robust against arbitrary acquisition orientation and spatial resolution up to 0.6 mm isotropic at the finest. The AFTER-QSM neural network starts with a forward affine transformation layer, followed by a Unet for dipole inversion, then an inverse affine transformation layer, followed by a Residual Dense Network (RDN) for QSM refinement. Simulation and in-vivo experiments demonstrated that the proposed AFTER-QSM network architecture had excellent generalizability. It can successfully reconstruct susceptibility maps from highly oblique and anisotropic scans, leading to the best image quality assessments in simulation tests and suppressed streaking artifacts and noise levels for in-vivo experiments compared with other methods. Furthermore, ablation studies showed that the RDN refinement network significantly reduced image blurring and susceptibility underestimation due to affine transformations. In addition, the AFTER-QSM network substantially shortened the reconstruction time from minutes using conventional methods to only a few seconds.

Immune checkpoint blockades (ICBs) have revolutionized cancer therapy by inducing durable clinical responses, but only a small percentage of patients can benefit from ICB treatments. Many studies have established various biomarkers to predict ICB responses. However, different biomarkers were found with diverse performances in practice, and a timely and unbiased assessment has yet to be conducted due to the complexity of ICB-related studies and trials. In this study, we manually curated 29 published datasets with matched transcriptome and clinical data from more than 1400 patients, and uniformly preprocessed these datasets for further analyses. In addition, we collected 39 sets of transcriptomic biomarkers, and based on the nature of the corresponding computational methods, we categorized them into the gene-set-like group (with the self-contained design and the competitive design, respectively) and the deconvolution-like group. Next, we investigated the correlations and patterns of these biomarkers and utilized a standardized workflow to systematically evaluate their performance in predicting ICB responses and survival statuses across different datasets, cancer types, antibodies, biopsy times, and combinatory treatments. In our benchmark, most biomarkers showed poor performance in terms of stability and robustness across different datasets. Two scores (TIDE and CYT) had a competitive performance for ICB response prediction, and two others (PASS-ON and EIGS_ssGSEA) showed the best association with clinical outcome. Finally, we developed ICB-Portal to host the datasets, biomarkers, and benchmark results and to implement the computational methods for researchers to test their custom biomarkers. Our work provided valuable resources and a one-stop solution to facilitate ICB-related research.

Quantitative susceptibility mapping (QSM) is an MRI post-processing technique that produces spatially resolved magnetic susceptibility maps from phase data. However, the traditional QSM reconstruction pipeline involves multiple non-trivial steps, including phase unwrapping, background field removal, and dipole inversion. These intermediate steps not only increase the reconstruction time but accumulates errors. This study aims to overcome existing limitations by developing a Laplacian-of-Trigonometric-functions (LoT) enhanced deep neural network for near-instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MRI phase data. The proposed iQFM and iQSM methods were compared with established reconstruction pipelines on simulated and in vivo datasets. In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the proposed neural networks. The proposed iQFM and iQSM methods in healthy subjects yielded comparable results to those involving the intermediate steps while dramatically improving reconstruction accuracies on intracranial hemorrhages with large susceptibilities. High susceptibility contrast between multiple sclerosis lesions and healthy tissue was also achieved using the proposed methods. Comparative studies indicated that the most significant contributor to iQFM and iQSM over conventional multi-step methods was the elimination of traditional Laplacian unwrapping. The reconstruction time on the order of minutes for traditional approaches was shortened to around 0.1 s using the trained iQFM and iQSM neural networks.

In this study, potent coumarin derivatives containing oxime ester 1 ∼ 28 as α-glucosidase inhibitors were developed through a stepwise structure optimization, and the structure activity relationship was uncovered. Among them, compound 20 exhibited outstanding α-glucosidase inhibitory activity with IC50 of 2.54 ± 0.04 μM compared to 640.57 ± 1.13 μM of Acarbose. Kinetic study ascertained that compound 20 was a reversible and uncompetitive α-glucosidase inhibitor. 3D fluorescence results showed that the interaction of compound 20 with α-glucosidase caused the changes of microenvironments and polypeptide backbone structure of α-glucosidase. CD spectra results revealed that compound 20 decreased the α-helix content and increased the β-sheet content. Molecular docking analysis indicated that compound 20 well located into the active site and mainly bind with Phe157, His239, His279, Tyr71, and Arg312 to reduce the catalytic activity of α-glucosidase.

Due to the explosion of cancer genome data and the urgent needs for cancer treatment, it is becoming increasingly important and necessary to easily and timely analyze and annotate cancer genomes. However, tumor heterogeneity is recognized as a serious barrier to annotate cancer genomes at the individual patient level. In addition, the interpretation and analysis of cancer multi-omics data rely heavily on existing database resources that are often located in different data centers or research institutions, which poses a huge challenge for data parsing. Here we present CCAS (Cancer genome Consensus Annotation System, https://ngdc.cncb.ac.cn/ccas/#/home), a one-stop and comprehensive annotation system for the individual patient at multi-omics level. CCAS integrates 20 widely recognized resources in the field to support data annotation of 10 categories of cancers covering 395 subtypes. Data from each resource are manually curated and standardized by using ontology frameworks. CCAS accepts data on single nucleotide variant/insertion or deletion, expression, copy number variation, and methylation level as input files to build a consensus annotation. Outputs are arranged in the forms of tables or figures and can be searched, sorted, and downloaded. Expanded panels with additional information are used for conciseness, and most figures are interactive to show additional information. Moreover, CCAS offers multidimensional annotation information, including mutation signature pattern, gene set enrichment analysis, pathways and clinical trial related information. These are helpful for intuitively understanding the molecular mechanisms of tumors and discovering key functional genes.

Scaffolds are an essential component of bone tissue engineering. They provide support and create a physiological environment for cells to proliferate and differentiate. Bone allografts extracted from human donors are promising scaffolds due to their mechanical and structural characteristics. Bone microarchitecture is well known to be an important determinant of macroscopic mechanical properties, but its role at the microscopic, i.e., the trabeculae level is still poorly understood. The present study investigated linear correlations between microarchitectural parameters obtained from X-ray computed tomography (micro-CT) images of bone allografts, such as bone volume fraction (BV/TV), degree of anisotropy (DA), or ellipsoid factor (EF), and micromechanical parameters derived from micro-finite element calculations, such as mean axial strain (εz) and strain energy density (We). DAEF, a new parameter based on a linear combination of the two microarchitectural parameters DA and EF, showed a strong linear correlation with the bone mechanical characteristics at the microscopic scale. Our results concluded that the spatial distribution and the plate-and-rod structure of trabecular bone are the main determinants of the mechanical properties of bone at the microscopic level. The DAEF parameter could, therefore, be used as a tool to predict the level of mechanical stimulation at the local scale, a key parameter to better understand and optimize the mechanism of osteogenesis in bone tissue engineering.

α-Glucosidase inhibitors are known to prevent the digestion of carbohydrates and reduce the impact of carbohydrates on blood glucose. To develop novel α-glucosidase inhibitors, a series of 5-fluoro-2-oxindole derivatives (3a ∼ 3v) were synthesized, and their α-glucosidase inhibitory activities were investigated. Biological assessment results showed that most synthesized compounds presented potential inhibition on α-glucosidase. Among them, compounds 3d, 3f, and 3i exhibited much better inhibitory activity with IC50 values of 49.89 ± 1.16 μM, 35.83 ± 0.98 μM, and 56.87 ± 0.42 μM, respectively, which were about 10 ∼ 15 folds higher than acarbose (IC50 = 569.43 ± 43.72 μM). A kinetic mechanism study revealed that compounds 3d, 3f, and 3i inhibited the α-glucosidase in a reversible and mixed manner. Molecular docking was carried out to simulate the affinity between the compound and α-glucosidase.

A series of benzylidene analogs of oleanolic acid 4a∼4s were synthesized and assessed for their α-glucosidase and α-amylase inhibitory activities. The results presented that all synthesized analogs exhibited excellent-to-moderate inhibitory effects on α-glucosidase and α-amylase. Analog 4i showed the highest α-glucosidase inhibition (IC50: 0.40 μM), and analog 4o presented the strongest α-amylase inhibition (IC50: 9.59 μM). Inhibition kinetics results showed that analogs 4i and 4o were reversible and mixed-type inhibitors against α-glucosidase and α-amylase, respectively. Simulation docking results demonstrated the interaction between analogs and two enzymes. Moreover, analogs 4i and 4o showed a high level of safety against 3T3-L1 and HepG2 cells.

Coumarin and chalcone, two important kinds of natural product skeletons, both exhibit α-glucosidase inhibitory activity. In this work, coumarin-chalcone derivatives 3 (a∼v) were synthesized, and their α-glucosidase inhibitory activity was screened. The results showed that all synthetic derivatives (IC50: 24.09 ± 2.36 to 125.26 ± 1.18 μM) presented better α-glucosidase inhibitory activity than the parent compounds 3-acetylcoumarin (IC50: 1.5 × 105 μM) and the positive control acarbose (IC50: 259.90 ± 1.06 μM). Among them, compound 3t displayed the highest α-glucosidase inhibitory activity (IC50: 24.09 ± 2.36 μM), which was approximately 10 times stronger than that of acarbose. The kinetic assay of 3t (KI = 18.82 μM, KIS = 59.99 μM) revealed that these compounds inhibited α-glucosidase in a mixed-type manner. Molecular docking was used to simulate the interaction between α-glucosidase and compound 3t.

α-Glucosidase is a potent drug target for treating type II diabetes mellitus. A great number of α-glucosidase inhibitors have been developed based on the molecular skeletons of bioactive natural products. However, efficient fluorescent probes for α-glucosidase detection are still limited, not to mention the probes with additional inhibitory functions. In this work, aiming for the enzyme’s highly specific detection, we designed and synthesized two environmentally sensitive fluorescent probes, namely, LD01 and LD02, respectively, based on conjugates of coumarin and cinnamic acid derivatives. We found a significant responsive emission enhancement upon LD02’s binding to α-glucosidase. These newly designed probes can act as a simple but efficient tool to evaluate the binding affinity of α-glucosidase to their inhibitors.

In order to find potential inhibitors of tyrosinase, two series of pyrrole derivatives A (1–17) and B (1–8) were synthesized and screened for their inhibitory activities on tyrosinase. Most of the 2-cyanopyrrole derivatives exhibited effective inhibitory activities. In particular, A12 exhibited the strongest inhibitory activities, with the IC50 values of 0.97 μM, which is ∼30 times stronger than the reference inhibitor kojic acid (IC50: 28.72 μM). The inhibitory mechanism analysis results revealed that A12 was a reversible and mixed-type inhibitor. Molecular docking experiments clarified the interaction between A12 with tyrosinase. Furthermore, A12 (100 μM) presented effective inhibitory effect on tyrosinase in B16 melanoma cells with inhibition of 33.48%, which was equivalent to that of Kojic acid (39.81%). Accordingly, compound A12 may serve as the lead structure for the further design of potent tyrosinase inhibitors. Molecular docking studies confirmed the interaction between the compound and tyrosinase.

In this paper, bis (indol-3-yl) methanes (BIMs) were synthesised and evaluated for their inhibitory activity against α-glucosidase and α-amylase. All synthesised compounds showed potential α-glucosidase and α-amylase inhibitory activities. Compounds 5 g (IC50: 7.54 ± 1.10 μM), 5e (IC50: 9.00 ± 0.97 μM), and 5 h (IC50: 9.57 ± 0.62 μM) presented strongest inhibitory activities against α-glucosidase, that were ∼ 30 times stronger than acarbose. Compounds 5 g (IC50: 32.18 ± 1.66 µM), 5 h (IC50: 31.47 ± 1.42 µM), and 5 s (IC50: 30.91 ± 0.86 µM) showed strongest inhibitory activities towards α-amylase, ∼ 2.5 times stronger than acarbose. The mechanisms and docking simulation of the compounds were also studied. Compounds 5 g and 5 h exhibited bifunctional inhibitory activity against these two enzymes. Furthermore, compounds showed no toxicity against 3T3-L1 cells and HepG2 cells.Highlights A series of bis (indol-3-yl) methanes (BIMs) were synthesised and evaluated inhibitory activities against α-glucosidase and α-amylase. Compound 5g exhibited promising activity (IC50 = 7.54 ± 1.10 μM) against α-glucosidase. Compound 5s exhibited promising activity (IC50 = 30.91 ± 0.86 μM) against α-amylase. In silico studies were performed to confirm the binding interactions of synthetic compounds with the enzyme active site.

Purpose: Urolithiasis is highly prevalent worldwide. The aim of this study was to report the results of the Global Burden of Disease 2019 study on urolithiasis burden estimates grouped by gender, regions, countries or territories, and sociodemographic index (SDI) from 1990 to 2019 globally. Methods: We reported detailed estimates and temporal trends of the burden estimates of urolithiasis from 1990 to 2019 in 195 countries and territories and further evaluated the relationship between these estimates and SDI, a composite indicator of income per person, years of education, and fertility as a measurement of country/region socio-economic level. Urolithiasis incidence and disability-adjusted life years by gender, regions, countries or territories, and SDI were reported. The percentage change and estimated annual percentage change of these burden estimates were calculated to quantify temporal trends. Results: From 1990 to 2019, the age-standardized incidence rate (ASIR) and disability-adjusted life years (DALYs) of urolithiasis decreased globally by 0.459% and 1.898% per year, respectively. Such a trend of ASIR was prominently due to the decline in the middle, high-middle, and high SDI countries, including Eastern Asia, high-income Eastern Europe, and high-income North America. During this period, these estimates increased in low and low-middle SDI countries, particularly in South Asia, Andean Latin America, and Western Europe. A decline in DALYs was observed in all SDI countries. An approximate positive linear association existed between the burden estimate’s decreased APC and SDI level, except at the high SDI level. Both males and females showed the same trend. Conclusions: This study provides comprehensive knowledge of the burden estimate of urolithiasis. Although the burden estimates of urolithiasis showed a global decrease during the past 29 years, this progress has yet to be universal; the increasing trends were observed in countries with low and low-middle SDI countries. Research in these countries is needed and helps with the appropriate allocation of health resources for prevention, screening, and treatment strategies.

Plants are often confronted with light fluctuations from seconds to minutes due to altering sun angles, mutual shading, and clouds under natural conditions, which causes a massive carbon loss and water waste. The effect of stomatal morphology on the response of leaf gas exchange to fluctuating light remains disputable. In this study, we investigated the differences in leaf stomatal morphology and photosynthetic induction across twelve rice genotypes after a stepwise increase in light intensity. A negative correlation was observed between stomatal size and density across rice genotypes. Smaller and denser stomata contributed to a faster stomatal response under fluctuating light. Plants with faster stomatal opening also showed faster photosynthetic induction and higher biomass accumulation but lower intrinsic water use efficiency (iWUE) under fluctuating light. Moreover, stomatal morphology seemed to have less effect on the initial and final stomatal conductance, and there was a minimal correlation between steady-state and non-steady-state stomatal conductance among different rice genotypes. These results highlight the important role of stomatal morphology in regulating photosynthetic efficiency and plant growth under fluctuating light conditions. To simultaneously enhance leaf iWUE when improving the photosynthetic efficiency under fluctuating light, it may be necessary to take biochemical processes into account in the future.

The Illumina HumanMethylation BeadChip is one of the most cost-effective methods to quantify DNA methylation levels at single-base resolution across the human genome, which makes it a routine platform for epigenome-wide association studies. It has accumulated tens of thousands of DNA methylation array samples in public databases, providing great support for data integration and further analysis. However, the majority of public DNA methylation data are deposited as processed data without background probes which are widely used in data normalization. Here, we present Gaussian mixture quantile normalization (GMQN), a reference based method for correcting batch effects as well as probe bias in the HumanMethylation BeadChip. Availability and implementation: https://github.com/MengweiLi-project/gmqn.

Fluid charging and formation pressure evolution are of great significance for shale gas exploration and development. Taking the Longmaxi formation shale in southeast Chongqing as the research object, the fluid activity and pressure evolution process were studied by means of thin section observation, fluid inclusion analysis and testing, and basin numerical simulation. The results show that the area of the southeast of Chongqing, the Longmaxi formation of dike filling minerals, is mainly quartz vein and calcite part of the veins and arteries, and vein body captures the rich organic inclusions in minerals, sees fgas-liquid two-phase brine inclusions and methane inclusions, combining with the temperature and salinity of brine inclusions, and shows that the area has experienced two phases of oil and gas filling, the first period of gas-liquid fluid. The second stage is gas fluid. Combined with burial history and thermal maturation history, it is found that the filling time of oil and gas is late Cretaceous and Paleocene, respectively. In the Cretaceous, the pressure coefficient of Longmaxi formation reached the maximum value of 2.2 and remained above 1.5 overpressure after pressure unloading in the later period. In terms of the frequency of inclusions, the charging amount of the first stage is relatively large, and the charging time corresponds to the peak period of the palaeo-formation pressure. At the same time, fluid charging can timely supplement the pressure after unloading, which is conducive to high and stable production of shale gas.

Due to an anti-failure bias, theoretical and practical studies have not focused much on the problem of innovation failure. The literature does not include studies on how the effect of re-innovation input on firm performance can still be explained by existing theories, especially in the case of previous innovation failures. To explore the intrinsic relationship between the re-innovation from failure and firm performance, as well as the influencing mechanism of the institutional environment differences on a firm’s re-innovation activities, using the data of the Listed Companies in China’s pharmaceutical manufacturing industry from 2008 to 2014 and a multiple regression model, the relationships between the reinnovation from failure, institutional environment differences, and firm performance were analyzed from 3 aspects: government intervention, financial development, and legal environment. The results show that the re-innovation input from failure has a significant positive impact on firm performance. The level of government intervention and the level of financial development play significant negative and positive moderating roles in the relationship between the re-innovation input and firm performance, respectively, and the above-mentioned effects are more prominent in eastern China. Moreover, with the improvement of the marketization of the financial industry, the beneficial effect of the reinnovation input from failure on firm performance in state-owned firms will be further strengthened. However, the moderating effect of the legal environment is not obvious.

Manipulating the photoprotective mechanism has been demonstrated to be an effective way to enhance the photosynthetic productivity of crop plants. NPQ(T) is a chlorophyll fluorescence parameter for rapid estimation and imaging of non-photochemical quenching (NPQ) of excitons in the photoprotective mechanism. However, the variation and genetic basis of NPQ(T) are rarely reported in the Oryza sativa L. In this study, we collected 173 rice cultivars and investigated the NPQ(T) value. We found that the NPQ(T) has a wide variation, although it had not been under-selected in the different subspecies. A genome-wide association study (GWAS) utilizing 1,566,981 high-quality SNPs identified three significant associated signals on chromosomes 02, 05, and 07. Furthermore, one likely candidate gene Os02g0184100, underlying the associated signal on chromosome 02, was uncovered by identifying the expression pattern in flag leaves and testing the correlation between functional polymorphisms and phenotypic variation. The significant SNPs and candidate genes identified in this study provide us a comprehensive understanding of the genetic architecture of NPQ(T) and could be used for genetic improvement of rice photoprotection.

Abstract Piezoresponse force microscopy (PFM), as a powerful nanoscale characterization technique, has been extensively utilized to elucidate diverse underlying physics of ferroelectricity. However, intensive studies of conventional PFM have revealed a growing number of concerns and limitations which are largely challenging its validity and applications. In this study, an advanced PFM technique is reported, namely heterodyne megasonic piezoresponse force microscopy (HM‐PFM), which uses 106 to 108 Hz high‐frequency excitation and heterodyne method to measure the piezoelectric strain at nanoscale. It is found that HM‐PFM can unambiguously provide standard ferroelectric domain and hysteresis loop measurements, and an effective domain characterization with excitation frequency up to ≈110 MHz is demonstrated. Most importantly, owing to the high‐frequency and heterodyne scheme, the contributions from both electrostatic force and electrochemical strain can be significantly minimized in HM‐PFM. Furthermore, a special measurement of difference‐frequency piezoresponse frequency spectrum (DFPFS) is developed on HM‐PFM and a distinct DFPFS characteristic is observed on the materials with piezoelectricity. By performing DFPFS measurement, a truly existed but very weak electromechanical coupling in CH3NH3PbI3 perovskite is revealed. It is believed that HM‐PFM can be an excellent candidate for the ferroelectric or piezoelectric studies where conventional PFM results are highly controversial.

Single-cell transcriptome studies have revealed immune dysfunction in COVID-19 patients, including lymphopenia, T cell exhaustion, and increased levels of pro-inflammatory cytokines, while DNA methylation plays an important role in the regulation of immune response and inflammatory response. The specific cell types of immune responses regulated by DNA methylation in COVID-19 patients will be better understood by exploring the COVID-19 DNA methylation variation at the cell-type level. Here, we developed an analytical pipeline to explore single-cell DNA methylation variations in COVID-19 patients by transferring bulk-tissue-level knowledge to the single-cell level. We discovered that the methylation variations in the whole blood of COVID-19 patients showed significant cell-type specificity with remarkable enrichment in gamma-delta T cells and presented a phenomenon of hypermethylation and low expression. Furthermore, we identified five genes whose methylation variations were associated with several cell types. Among them, S100A9, AHNAK, and CX3CR1 have been reported as potential COVID-19 biomarkers previously, and the others (TRAF3IP3 and LFNG) are closely associated with the immune and virus-related signaling pathways. We propose that they might serve as potential epigenetic biomarkers for COVID-19 and could play roles in important biological processes such as the immune response and antiviral activity.

Background: The increasing number of graduate students in China has resulted in the wide concern for their mental health problems. The coping style and social support are important factors that affect the mental health of individuals. This study aims to explore the relationship of the mental health, social support, and coping style of graduate students. Methods: The sample consisted of 260 graduate students from three universities of China. The participants were evaluated using the Symptom Checklist-90 (SCL-90), Social Support Revalued Scale (SSRS), and Coping Style Questionnaire (CSQ) in October and November 2017. The data of the scale were analyzed with t-test, correlation, and multiple regression analysis. Results: The graduate students had lower scores than the national norm standard on all subscales, except for anxiety and phobic anxiety in the SCL-90. Graduate students’ mental health was significantly negatively correlated with social support, problem-solving, and help-seeking and significantly positively correlated with self-blame, fantasy, withdrawal, and rationalization. Coping style and social support affected the mental health of graduate students, in which the regression coefficients of the subscales of problem-solving, rationalization, self-blame, and fantasy were −0.168, 0.070, 0.125, and 0.113, respectively. The regression coefficients of the subscales of subjective and objective supports were −0.086 and −0.024, respectively. Conclusion: The positive coping style and social support improve the level of graduate students’ mental health through the gain effect and alleviate abnormal psychological symptoms. The conclusions of this study can provide a reference to improve the psychological intervention strategies for graduate students.