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Abstract “Candidatus Liberibacter asiaticus” (CLas) is a phloem-limited alpha-proteobacteria causing Citrus Huanglongbing, the destructive disease currently threatening global citrus industry. Genomic analyses of CLas provide insights into its evolution and biology. Here, we sequenced and assembled whole genomes of 135 CLas strains originally from 20 citrus cultivars collected at ten citrus-growing provinces in China. The resulting dataset comprised 135 CLas genomes ranging from 1,221,309 bp to 1,308,521 bp, with an average coverage of 675X. Prophage typing showed that 44 strains contained Type 1 prophage, 89 strains contained Type 2 prophage, 44 strains contained Type 3 prophage, and 34 of them contained more than one type of prophage/phage. The SNP calling identified a total of 5,090 SNPs. Genome-based phylogenetic analysis revealed two major clades among CLas strains, with Clade I dominated by CLas strains containing Type 1 prophage (79/95) and Clade II dominated by CLas strains containing Type 1 or Type 3 prophage (80/95). This CLas genome dataset provides valuable resources for studying genetic diversity and evolutionary pattern of CLas strains.

Highlights Co/Co3O4@NC nanosheets with gradient magnetic heterointerfaces have been fabricated by the high-temperature carbonization/low-temperature oxidation processes. Experimental and theoretical simulation results indicate that magnetic heterointerfaces engineering is beneficial for optimizing impedance matching and promoting electromagnetic wave absorption. Gradient magnetic heterointerfaces with magnetic-heteroatomic components realize the adjustment of interfacial polarization, magnetic coupling, and long-range magnetic diffraction.

The accurate measurement of the water level on the secondary side of the steam generator (SG) plays a crucial role in the safe and stable operation of the primary and secondary circuits of the nuclear power plant. In order to study the feasibility of applying the magnetostrictive liquid level gauge to the water level measurement of SG, the measurement results of the magnetostrictive liquid level gauge under the steady and transient conditions were obtained and compared with the traditional differential pressure liquid level gauge. The results indicated that the magnetostrictive liquid level gauge had good measurement accuracy under the cold-steady condition, thermal-steady condition and transient pressurization condition. The design parameters of float and operating parameters were necessary to correct the measurement results of magnetostrictive water level gauge. The measurement results under the transient depressurization condition were affected by the fluid movement in the container, resulting in a decrease in measurement accuracy. The results indicated that the magnetostrictive liquid level gauge had the potential to be used for water level measurement of SG in nuclear power plant.

Abstract Background Hepatic steatosis and its related complications are risk factors for multiple respiratory diseases; however, the causal relationship between metabolic dysfunction-associated steatotic liver disease (MASLD) and pulmonary function remains controversial. We aimed to identify it using a national cohort and Mendelian randomization (MR). Methods We enrolled 30,442 participants from the 2007 to 2012 National Health and Nutrition Examination Survey. Demographics, pulmonary function indices (forced expiratory volume in 1 s [FEV1], forced vital capacity [FVC]), and variables used to calculate the liver fat score (LFS) were collected. A two-sample MR analysis employing the summary data of genome-wide association studies on MASLD and FEV1/FVC, chronic obstructive pulmonary disease (COPD), and asthma from the Finngen Biobank and Medical Research Council Integrative Epidemiology Unit was performed. Results A total of 3,462 participants, 1,335 of whom had MASLD (LFS > -0.640), were finally included in the study. The FEV1 (3,204.7 vs. 3,262.5 ml, P = 0.061), FVC (4,089.1 vs. 4,143.8 ml, P = 0.146), FEV1/FVC ratio (78.5% vs. 78.8%, P = 0.233), and FEV1/predicted FEV1 ratio (146.5% vs. 141.7%, P = 0.366) were not significantly different between people with MASLD and those without. Additionally, the MR analysis suggested no causal correlation between MASLD and FEV1/FVC (P = 0.817), MASLD and COPD (P = 0.407), and MASLD and asthma (P = 0.808). Reverse MR studies showed no causal relationships yet (all P > 0.05). Conclusion Our study provides convincing evidence that there is no causal association between MASLD and pulmonary function.

Abstract The color of red-skinned pear (Pyrus spp.) is primarily attributed to accumulation of anthocyanins, which provide nutritional benefits for human health and are closely associated with the commercial value of fruits. Here, we reported the functional characterization of a R2R3-MYB repressor PyMYB107, which forms an ‘activator-repressor’ loop to control anthocyanin accumulation in the red-skinned pear. PyMYB107 overexpression inhibited anthocyanin biosynthesis in both pear calli and fruits, while virus-induced gene silencing of PyMYB107 increased anthocyanin accumulation in pear fruits. Furthermore, ectopic expression of PyMYB107 decreased anthocyanin accumulation in tomato, strawberry and tobacco. PyMYB107 can competitively bind to PybHLH3 with PyMYB10/MYB114, thereby suppressing the transcriptional activation of key anthocyanin biosynthesis genes, PyANS and PyUFGT. Site-directed mutagenesis showed that mutations within the R3 domain and EAR motif of PyMYB107 eliminated its repressive activity. Additionally, PyMYB107 exhibited a comparable expression pattern to PyMYB10/MYB114 and was transcriptionally activated by them. Our finding advanced comprehension of the repression mechanism underlying anthocyanin accumulation, providing valuable molecular insights into improving quality of pear fruits.

Objective Myelodysplastic syndrome (MDS) is a malignant clonal disorder of hematopoietic stem cells which is characterized by morphologic dysplasia. However, the pathological characteristics of megakaryocytes (MKs) in MDS patients with gene mutation are not well established.

In response to an ever-increasing demand of new small molecules therapeutics, numerous chemical and genetic tools have been developed to interrogate compound mechanism of action. Owing to its ability to approximate compound-dependent changes in thermal stability, the proteome-wide thermal shift assay has emerged as a powerful tool in this arsenal. The most recent iterations have drastically improved the overall efficiency of these assays, providing an opportunity to screen compounds at a previously unprecedented rate. Taking advantage of this advance, we quantified more than one million thermal stability measurements in response to multiple classes of therapeutic and tool compounds (96 compounds in living cells and 70 compounds in lysates). When interrogating the dataset as a whole, approximately 80% of compounds (with quantifiable targets) caused a significant change in the thermal stability of an annotated target. There was also a wealth of evidence portending off-target engagement despite the extensive use of the compounds in the laboratory and/or clinic. Finally, the combined application of cell- and lysate-based assays, aided in the classification of primary (direct ligand binding) and secondary (indirect) changes in thermal stability. Overall, this study highlights the value of these assays in the drug development process by affording an unbiased and reliable assessment of compound mechanism of action.

Abstract Background Observational studies have explored the relationships of periodontitis with brain atrophy and cognitive impairment, but these findings are limited by reverse causation, confounders and have reported conflicting results. Our study aimed to investigate the causal associations of periodontitis with brain atrophy and cognitive impairment through a comprehensive bidirectional Mendelian randomization (MR) research. Methods We incorporated two distinct genome-wide association study (GWAS) summary datasets as an exploration cohort and a replication cohort for periodontitis. Four and eight metrics were selected for the insightful evaluation of brain atrophy and cognitive impairment, respectively. The former involved cortical thickness and surface area, left and right hippocampal volumes, with the latter covering assessments of cognitive performance, fluid intelligence scores, prospective memory, and reaction time for mild cognitive impairment to Alzheimer's disease (AD), Lewy body dementia, vascular dementia and frontotemporal dementia for severe situations. Furthermore, supplementary analyses were conducted to examine the associations between the longitudinal rates of change in brain atrophy and cognitive function metrics with periodontitis. The main analysis utilized the inverse variance weighting (IVW) method and evaluated the robustness of the results through a series of sensitivity analyses. For multiple tests, associations with p-values < 0.0021 were considered statistically significant, while p-values ≥ 0.0021 and < 0.05 were regarded as suggestive of significance. Results In the exploration cohort, forward and reverse MR results revealed no causal associations between periodontitis and brain atrophy or cognitive impairment, and only a potential causal association was found between AD and periodontitis (IVW: OR = 0.917, 95% CI from 0.845 to 0.995, P = 0.038). Results from the replication cohort similarly corroborated the absence of a causal relationship. In the supplementary analyses, the longitudinal rates of change in brain atrophy and cognitive function were also not found to have causal relationships with periodontitis. Conclusions The MR analyses indicated a lack of substantial evidence for a causal connection between periodontitis and both brain atrophy and cognitive impairment.

Abstract The production plan of an open-pit mine depends on the block model, so it's crucial to determine the appropriate method and size for partitioning it. This study proposes a new method based on a closed shell three-dimensional geological model for determining block model size in open-pit mines. Instead of using regular block models, the shell model is directly cut, and the discrete geological body is referred to as the "mining model." Mining parameters and the shovel-truck's performance are integrated into the method. Bench height determines the Z-axis size, bench slope angle determines the inclination angle, and shovel width determines the X-axis size of the block model. The operation efficiency of the shovel-truck considers the probability distribution of simultaneous operations, allowing the determination of the Y-axis size of block models for different types of shovels. The developed "Mining Model" module in the software "Life Cycle Mining System" is used for practical implementation. By comparing the results with traditional block models, the superiority of the proposed method is demonstrated. This study provides a more accurate model for optimizing the production plan of open-pit mines throughout their life cycle.

Abstract Purpose Under the background of the regular implementation of the National Centralized Drug Procurement (NCDP) policy, this study aimed to assess the impacts of the NCDP policy on drug utilization of county-level medical institutions, and probe into the influencing factors of the changes in drug utilization. Method A pre-post study was applied using inpatient data from a county-level medical institution in Nanjing. Drug utilization behavior of medical institutions of 88 most commonly used policy-related drugs (by generic name, including bid-winning and bid-non-winning brands) was analyzed, and the substitution of bid-winning brands for brand-name drugs after policy intervention was evaluated. Results After policy intervention, 43.18% of policy-related drugs realized the substitution of bid-winning brands for bid-non-winning brands (6.82% of complete substitution, 36.36% of partial substitution). Meanwhile, 40.90% of policy-related drugs failed to realize brand substitution. Multiple factors affected brand substitution, including: (1) Policy effect: brand substitution was more obvious after the intervention of the first and third round of NCDP. (2) Drug market competition: the greater the price reduction of bid-non-winning brands, the more the drugs for the same indication, the more likely that medical institutions keep using the same brands as they did before policy intervention. (3) Previous drug utilization of medical institutions: brand substitution was more obvious in drugs with large number of prescriptions and weak preference for brand-name drugs. Conclusion The NCDP policy promoted the substitution of bid-winning brands for bid-non-winning brands. However, the NCDP policy remained to be further implemented in county-level medical institutions. Policy implememtation efforts, drug market competition and drug utilization of medical institutions would affect the implementation of the NCDP policy.

Abstract Background DNA methylation is an essential epigenetic modification. However, its contribution to trait changes and diversity in the domestication of perennial fruit trees remains unknown. Results Here, we investigate the variation in DNA methylation during pear domestication and improvement using whole-genome bisulfite sequencing in 41 pear accessions. Contrary to the significant decrease during rice domestication, we detect a global increase in DNA methylation during pear domestication and improvement. We find this specific increase in pear is significantly correlated with the downregulation of Demeter-like1 (DML1, encoding DNA demethylase) due to human selection. We identify a total of 5591 differentially methylated regions (DMRs). Methylation in the CG and CHG contexts undergoes co-evolution during pear domestication and improvement. DMRs have higher genetic diversity than selection sweep regions, especially in the introns. Approximately 97% of DMRs are not associated with any SNPs, and these DMRs are associated with starch and sucrose metabolism and phenylpropanoid biosynthesis. We also perform correlation analysis between DNA methylation and gene expression. We find genes close to the hypermethylated DMRs that are significantly associated with fruit ripening. We further verify the function of a hyper-DMR-associated gene, CAMTA2, and demonstrate that overexpression of CAMTA2 in tomato and pear callus inhibits fruit ripening. Conclusions Our study describes a specific pattern of DNA methylation in the domestication and improvement of a perennial pear tree and suggests that increased DNA methylation plays an essential role in the early ripening of pear fruits.

Abstract Evaporative cooling stands as the prevailing method for achieving ultracold temperatures in atomic systems. Current schemes of evaporation selectively remove the hotter atoms near the edge of the trap, as the hotter and colder atoms are distributed in different spatial regions of the trapping potential. However, a long-standing goal is to directly remove the higher momentum atoms, irrespective of their spatial distribution. For this purpose, we demonstrate collisional cooling for a 6Li Fermi gas through inelastic three-body recombination near a narrow Feshbach resonance. Such three-body recombination can induce either heating or cooling effects, and the decay of the quasi-bound Feshbach molecule stirs the hotter atoms away from the trapping potential. When the threshold energy of the Feshbach molecule exceeds the atom’s average kinetic energy of 3/2k B T, the cooling effect becomes more pronounced. Finally, we observe strong temperature dependence in this collisional cooling process, with greater efficiency achieved at lower temperatures.

Abstract Sugar Will Eventually be Exported Transporter (SWEET) proteins are highly conserved in various organisms and play crucial roles in sugar transport processes. However, SWEET proteins in peanuts, an essential leguminous crop worldwide, remain lacking in systematic characterization. Here, we identified 94 SWEET genes encoding the conservative MtN3/saliva domains in three peanut species, including 47 in Arachis hypogea, 23 in Arachis duranensis, and 24 in Arachis ipaensis. We observed significant variations in the exon-intron structure of these genes, while the motifs and domain structures remained highly conserved. Phylogenetic analysis enabled us to categorize the predicted 286 SWEET proteins from eleven species into seven distinct groups. Whole genome duplication/segment duplication and tandem duplication were the primary mechanisms contributing to the expansion of the total number of SWEET genes. In addition, an investigation of cis-elements in the potential promoter regions and expression profiles across 22 samples uncovered the diverse expression patterns of AhSWEET genes in peanuts. AhSWEET24, with the highest expression level in seeds from A. hypogaea Tifrunner, was observed to be localized on both the plasma membrane and endoplasmic reticulum membrane. Moreover, qRT-PCR results suggested that twelve seed-expressed AhSWEET genes were important in the regulation of seed development across four different peanut varieties. Together, our results provide a foundational basis for future investigations into the functions of SWEET genes in peanuts, especially in the process of seed development.

Genomic selection (GS) has the potential to improve selection efficiency and shorten the breeding cycle in fruit tree breeding. In this study, we evaluated the effect of prediction methods, marker density and the training population (TP) size on pear GS for improving its performance and reducing cost. We evaluated GS under two scenarios: (1) five-fold cross-validation in an interspecific pear family; (2) independent validation. Based on the cross-validation scheme, the prediction accuracy (PA) of eight fruit traits varied between 0.33 (fruit core vertical diameter) and 0.65 (stone cell content). Except for single fruit weight, a slightly better prediction accuracy (PA) was observed for the five parametrical methods compared with the two non-parametrical methods. In our TP of 310 individuals, 2 000 single nucleotide polymorphism (SNP) markers were sufficient to make reasonably accurate predictions. PAs for different traits increased by 18.21%–46.98% when the TP size increased from 50 to 100, but the increment was smaller (−4.13%–33.91%) when the TP size increased from 200 to 250. For independent validation, the PAs ranged from 0.11 to 0.45 using rrBLUP method. In summary, our results showed that the TP size and SNP numbers had a greater impact on the PA than prediction methods. Furthermore, relatedness among the training and validation sets, and the complexity of traits should be considered when designing a TP to predict the test panel.

ObjectiveThis study aimed to evaluate the impact of the National Centralized Drug Procurement (NCDP) policy on chemical pharmaceutical enterprises’ R&D investment and provide references for improving NCDP policy design and encouraging innovation in the pharmaceutical industry.MethodsUsing the panel data of 102 Shanghai and Shenzhen A-share listed enterprises from 2016 to 2022 under the chemical pharmaceutical classification of Shenwan in Wind database as the research sample, this study developed difference-in-differences (DID) models on bid-winning and bid-non-winning enterprises, respectively, to evaluate the impact of NCDP policy on their R&D investment. In addition, this study tested the heterogeneity of bid-winning enterprises based on the bid success rate, the decline of drug price, and enterprise size.ResultsThe NCDP policy could encourage chemical pharmaceutical companies to increase R&D investment, but the low bid success rate and excessive drug price reduction would reduce their R&D enthusiasm, especially for small- and medium-sized enterprises.DiscussionIt is suggested that the NCDP policy should be further improved: first, revise the bidding rule of the NCDP policy and increase the bid success rate so that more enterprises can win bids, and second, to solve the problem of excessive drug price reduction, evaluate the rationality of bid-winning prices, and introduce a two-way selection mechanism between medical institutions and supply enterprises. Integrate pharmacoeconomic evaluation into the NCDP rules to form a benign competition among enterprises. Third, attention should be paid to supporting policies for small- and medium-sized enterprises. By increasing procurement volume, shortening payment time limits, and increasing the proportion of advance payments, enterprises’ cash flow shortages can be alleviated, thus achieving fairness and inclusiveness in the implementation of the NCDP policy.

Multi-access Edge Computing (MEC) is an emerging and promising computing paradigm that distributes computational resources closer to users at the network edge, effectively reducing both computation and communication latency. In practical Internet of Things (IoT) systems, many applications consist of interdependent subtasks. Therefore, determining how to offload these tasks while maintaining their dependencies to minimize latency becomes a challenging problem. Particularly in a dynamic environment with multiple users and MEC servers. Most existing studies rely on heuristic approaches, which lack adaptability in dynamic MEC environments, while machine learning-based methods often overlook task dependencies. Unlike previous work, our research focuses on the problem of offloading dependent tasks in multi-user, multi-MEC server scenarios. In this article, we first model the dependent task offloading problem as a Markov Decision Process (MDP). Then we propose a deep reinforcement learning (DRL)-based framework called GDDTO, with the aim of reducing task completion time. Specifically, this framework employs a Graph Convolutional Network (GCN) to extract task dependencies and dynamic MEC environment features, combined with a Double Deep Q-learning Network (DDQN) model and an optimized experience replay mechanism to select and evaluate task offloading strategies. Finally, comparative experiments demonstrate that this method significantly reduces task completion latency across various scenarios, proving its effectiveness.

The linear flux-switching permanent magnet motor (LFSPM) has significant potential for practical applications in the field of rail transit due to its advantages of high thrust density and high efficiency. However, LFSPM not only generates the thrust that provides power to the vehicle but also generates high normal force perpendicular to the track, which will have an important impact on the vertical dynamics of the train. The current research lacks an in-depth analysis of LFSPM normal force and a systematic study of the influence of LFSPM normal force on trains. Addressing this issue, this paper compares LFSPM with existing linear induction motors used in wheel-track trains. The causes of the normal force characteristics of LFSPM are analyzed by finite element calculation and air-gap magnetic density analysis. The specific effects of the normal force characteristics on the train system are discussed by building a motor-vehicle-track coupling dynamic model. The main effects include reducing the air gap width, increasing the air-gap fluctuation, and increasing the rail vibration. It is of great practical significance to reveal the generating principle of LFSPM normal force characteristics and the potential problems in wheel-track train application.

As the proportion of renewable energy (RE) increases, the inertia and the primary frequency regulation (FR) capability of the power system decrease. Thus, ensuring frequency security in the scheduling model has become a new technical requirement in power systems with a high share of RE. Due to a shortage of conventional synchronous generators, the frequency support of multi-source converters has become an indispensable part of the system frequency resources, especially variable-speed wind turbine generation (WTG) and battery energy storage (BES). Quantitative expression of the FR capability of multi-source converters is necessary to construct frequen-cyconstrained scheduling model. However, the frequency support performance of these converter-interfaced devices is related to their working states, operation modes, and parameters, and the complex coupling of these factors has not been fully exploited in existing models. In this study, we propose an integrated frequency-constrained scheduling model considering the coordination of FR capabilities from multi-source converters. Switchable FR control strategies and variable FR parameters for WTG with or without reserved power are modeled, and multi-target allocation of BES capacity between tracking dispatch instruction and emergency FR is analyzed. Then, the variable FR capabilities of WTG and BES are embedded into the integrated frequency-constrained scheduling model. The nonlinear constraints for frequency security are precisely linearized through an improved iteration-based strategy. The effectiveness of the proposed model is verified in a modified IEEE 24-bus standard system. The results suggest that the coordinated participation of BES and WTG in FR can effectively reduce the cost of the scheduling model while meeting frequency security constraints.

Plant multidrug and toxic compound extrusion (MATE) genes play an important role in the process of detoxification, plant morphogenesis, and anthocyanin accumulation. However, whether the MATE gene family functions in pear peel coloration is still unknown. To evaluate and identify the MATE gene family members which are involving in anthocyanin accumulation and coloration in pear. In this study, 85 MATE genes were identified in the reference pear genome of ‘Dangshansuli’ through genome-wide identification. Based on gene structure and phylogenetic tree analysis, the MATE family was divided into five subfamilies. RNA sequencing and quantitative real-time polymerase chain reaction (qRT-PCR) indicated that the expression patterns of PbrMATEs were tissue-specific. 28.24% (24) of PbrMATE genes were expressed in the fruits, and 44.71% (38) of PbrMATE genes were expressed in the leaves. Additionally, we found that the expression levels of PbrMATE9, PbrMATE26, PbrMATE50, and PbrMATE69 in debagged fruits with red peel were significantly higher than those in bagged fruits without red peel, according to our bagging/debagging treatment of ‘Mantianhong’. The expression pattern of PbrMATE9 was consistent with the variation trend in anthocyanin content, suggesting that it might play an important role in anthocyanin accumulation in response to light exposure. Subcellular localization showed that PbrMATE9 was a membrane protein. More strikingly, the transient overexpression of PbrMATE9 promoted anthocyanin accumulation in the peel of pear, and the expression of structural genes (PbrCHI, PbrANS, PbrDFR, and PbrUFGT) in the anthocyanin biosynthesis pathway also increased significantly. Through co-expression network analysis, the transcription factors were identified, such as WRKY, COL, GATA, and BBX, which might be involved in the regulation of PbrMATE9. The study has enriched the genetic resources and improved the understanding of the regulation network of anthocyanin accumulation in pear.

Semiconductors with visible light catalytic characteristics can realize the degradation of pollutants, CO2 reduction, and hydrogen preparation in sunlight. They have huge application value in the fields of environmental repair and green energy. Graphite phase nitride (g-C3N4, CN) is widely used in various fields such as photocatalytic degradation of pollutants due to its suitable gap width, easy preparation, low cost, fast visible light response, and rich surface activity sites. However, the absorption rate of ordinary CN on visible light is low, and the carriers are easy to recombination, making the lower optical catalytic activity. Therefore, in order to improve the photocatalytic characteristics of the CN, it is necessary to make the surface modification. This article first introduces several main methods for the current surface modification of CN, including size regulation, catalyst embedding, defect introduction, heterostructure construction, etc., and then summarizes the optical catalytic application and related mechanisms of CN. Finally, some challenges and development prospects of CN in preparation and photocatalytic applications are proposed.

Anthocyanins are important secondary metabolites in plants, which contribute to fruit color and nutritional value. Anthocyanins can be regulated by environmental factors such as light, low temperature, water conditions, and nutrition limitations. Nitrogen (N) is an essential macroelement for plant development, its deficiency as a kind of nutrition limitation often induces anthocyanin accumulation in many plants. However, there is a lack of reports regarding the effect of nitrogen deficiency on anthocyanin biosynthesis in pears. In this study, we found that N deficiency resulted in anthocyanin accumulation in pear callus and upregulated the expression of anthocyanin biosynthesis pathway structural genes (PyPAL, PyCHS, PyCHI, PyF3H, PyDFR, PyANS, and PyUFGT) and key regulatory factors (PyMYB10, PyMYB114, and PybHLH3). Through analysis of transcriptome data of treated pear callus and RT-qPCR assay, a differentially expressed gene PyNAC42 was identified as significantly induced by the N deficiency condition. Overexpression of PyNAC42 promoted anthocyanin accumulation in “Zaosu” pear peels. Additionally, dual luciferase assay and yeast one-hybrid assay demonstrated that PyNAC42 could not directly activate the expression of PyDFR, PyANS, and PyUFGT. Furthermore, yeast two-hybrid and pull-down assays confirmed that PyNAC42 interacted with PyMYB10 both in vivo and in vitro. Co-expression of PyNAC42 and PyMYB10 significantly enhanced anthocyanin accumulation in “Zaosu” pear peels. Dual luciferase assay showed that PyNAC42 significantly enhanced the activation of PyDFR, PyANS, and PyUFGT promoters by interacting with PyMYB10, which suggests that PyNAC42 can form the PyNAC42-PyMYB10 complex to regulate anthocyanin biosynthesis in pear. Thus, the molecular mechanism underlying anthocyanin biosynthesis induced by N deficiency is preliminarily elucidated. Our finding has expanded the regulatory network of anthocyanin biosynthesis and enhanced our understanding of the mechanisms underlying nutrient deficiency modulates anthocyanin biosynthesis in pear.

Mitochondria are the energy factories of cells and are important targets for the development of novel tumour treatment strategies owing to their involvement in processes such as apoptosis, oxidative stress, and metabolic programming. Thiosemicarbazone metal complexes target mitochondria and reduce mitochondrial membrane potential. The breakdown of mitochondrial membrane potential is a key event in the early stage of apoptosis, which releases cytochrome C and other pro-apoptotic factors, activates the intracellular apoptotic enzyme cascade, and eventually causes irreversible apoptosis of tumour cells. Thiosemicarbazone metal complexes targeting the mitochondria have recently emerged as potential antitumour agents; therefore, this review describes the structural diversity of thiosemicarbazone metal [Fe(III), Cu(II), Ni(II), Zn(II), Ga(III), Pb(II), Au(III), and Ir(III)] complexes and explores their anti-tumour mechanisms that target mitochondrial pathways.

Background: As a fatal disease, cytokine storm has garnered research attention in recent years. Nonetheless, as the body of related studies expands, a thorough and impartial evaluation of the current status of research on cytokine storms remains absent. Consequently, this study aimed to thoroughly explore the research landscape and evolution of cytokine storm utilizing bibliometric and knowledge graph approaches. Methods: Research articles and reviews centered on cytokine storms were retrieved from the Web of Science Core Collection database. For bibliometric analysis, tools such as Excel 365, CiteSpace, VOSviewer, and the Bibliometrix R package were utilized. Results: This bibliometric analysis encompassed 6647 articles published between 2004 and 2022. The quantity of pertinent articles and citation frequency exhibited a yearly upward trend, with a sharp increase starting in 2020. Network analysis of collaborations reveals that the United States holds a dominant position in this area, boasting the largest publication count and leading institutions. Frontiers in Immunology ranks as the leading journal for the largest publication count in this area. Stephan A. Grupp, a prominent researcher in this area, has authored the largest publication count and has the second-highest citation frequency. Research trends and keyword evaluations show that the connection between cytokine storm and COVID-19, as well as cytokine storm treatment, are hot topics in research. Furthermore, research on cytokine storm and COVID-19 sits at the forefront in this area. Conclusion: This study employed bibliometric analysis to create a visual representation of cytokine storm research, revealing current trends and burgeoning topics in this area for the first time. It will provide valuable insights, helping scholars pinpoint critical research areas and potential collaborators.

BackgroundDrug-induced immune hemolytic anemia (DIIHA) is a rare but serious condition, with an estimated incidence of one in 100,000 cases, associated with various antibiotics. This study reports on a case of ceftizoxime-induced hemolysis observed in a patient in China.Case descriptionA Chinese patient diagnosed with malignant rectal cancer underwent antimicrobial therapy after laparoscopic partial recto-sigmoid resection (L-Dixon). After receiving four doses of ceftizoxime, the patient developed symptoms including rash, itchy skin, and chest distress, followed by a rapid decline in hemoglobin levels, the presence of hemoglobin in the urine (hemoglobinuria), renal failure, and disseminated intravascular coagulation. Laboratory analysis revealed high-titer antibodies against ceftizoxime and red blood cells (RBCs) in the patient’s serum, including immunoglobulin M (IgM) (1:128) antibodies and immunoglobulin G (IgG) (1:8) antibodies, with noted crossreactivity to ceftriaxone. Significant improvement in the patient’s hemolytic symptoms was observed following immediate discontinuation of the drug, two plasma exchanges, and extensive RBC transfusion.ConclusionThis case, together with previous reports, underscores the importance of considering DIIHA in patients who exhibit unexplained decreases in hemoglobin levels following antibiotic therapy. A thorough examination of the patient’s medical history can provide crucial insights for diagnosing DIIHA. The effective management of DIIHA includes immediate cessation of the implicated drug, plasma exchange, and transfusion support based on the identification of specific drug-dependent antibodies through serological testing.

Fibroblast growth factor 21 (FGF21) was originally identified as an important metabolic regulator which plays a crucial physiological role in regulating a variety of metabolic parameters through the metabolic network. As a novel multifunctional endocrine growth factor, the role of FGF21 in the metabolic network warrants extensive exploration. This insight was obtained from the observation that the FGF21-dependent mechanism that regulates lipid metabolism, glycogen transformation, and biological effectiveness occurs through the coordinated participation of the liver, adipose tissue, central nervous system, and sympathetic nerves. This review focuses on the role of FGF21-uncoupling protein 1 (UCP1) signaling in lipid metabolism and how FGF21 alleviates non-alcoholic fatty liver disease (NAFLD). Additionally, this review reveals the mechanism by which FGF21 governs glucolipid metabolism. Recent research on the role of FGF21 in the metabolic network has mostly focused on the crucial pathway of glucolipid metabolism. FGF21 has been shown to have multiple regulatory roles in the metabolic network. Since an adequate understanding of the concrete regulatory pathways of FGF21 in the metabolic network has not been attained, this review sheds new light on the metabolic mechanisms of FGF21, explores how FGF21 engages different tissues and organs, and lays a theoretical foundation for future in-depth research on FGF21-targeted treatment of metabolic diseases.

Abstract The kinematics and deformation pattern along the Altyn Tagh fault (ATF), one of the largest strike‐slip faults on Earth is of great significance for understanding the growth of the Tibetan Plateau. However, the initial rupture along the ATF remains debated given the limited constraints on the depositional age of associated Cenozoic syntectonic strata. Here we investigated the syntectonic Cenozoic strata in the Xorkol Basin, associated with the strike‐slip faulting along the ATF. New uranium‐lead analyses of the carbonate deposits in the Paleogene strata yield dates of 58.9 ± 1.29 Ma, representing the initial rupture of the ATF. This first documented radioisotopic age coincides with the ca. 60 Ma onset timing of India‐Asia collision, highlighting its far‐field effect at the northern edge of the Tibetan Plateau. We infer that the deformation of the entire Tibetan Plateau started synchronously with the India‐Asia collision.

For over a century, side-branch resonators have served as effective acoustic filters, yet the explanation for their sound reduction capability has varied. This paper introduces a novel theory applicable to all types of side-branch resonators from an energy perspective and explains sound reduction as a consequence of acoustic energy redistribution. Our theory posits that a standing wave inside the resonator induces air vibration at the opening, which then acts as a secondary sound source, emitting acoustic energy predominantly in the form of kinetic energy. Due to the formation process of the standing wave, the sound wave generated by the resonator undergoes a phase shift relative to the original sound wave in the main pipe. Consequently, this generated sound wave, while matching the amplitude, possesses an opposite phase compared to the original noise wave within the main pipe. This antiphase relationship results in the cancellation of sound waves when they interact post-resonator in the main pipe. Our theory, grounded in an energy perspective, is derived from the principles of standing wave vibration and energy conservation.

Background: Forkhead box M1 (FOXM1) functions as a transcription factor and is consistently overexpressed in various cancers, including non-small-cell lung-, breast-, cervical-, and colorectal cancer. Its overexpression is associated with poor prognosis in patients with non-small-cell lung cancer, although the detailed mechanisms by which FOXM1 promotes the development of non-small-cell lung cancer remain unclear. Objective: The mechanism of FOXM1 in migration, invasion, apoptosis, and viability of lung cancer cells was investigated. Methods: Transwell assay, scratch test, and flow cytometry were employed to study the effects of FOXM1 on migration, invasion, and apoptosis in A549 cells. A quantitative polymerase chain reaction was used to determine the impact of FOXM1 on miR-509-5p expression in A549 cells. Dual-luciferase reporter gene assay and chromatin immunoprecipitation were adopted to investigate the molecular mechanisms of FOXM1 on miR-509-5p expression. Results: FDI-6 (a FOXM1 inhibitor) reduced the protein abundance of FOXM1, thereby increasing the expression of miR-509-5p in A549 cells. Moreover, FDI-6 treatment significantly reduced migration, invasion, and viability of A549 cells while promoting cell apoptosis. Furthermore, miR-509-5p inhibitor obviously alleviated the biological effects of FDI-6 on A549 cells, suggesting that FOXM1 primarily exerted its cancer promoting effect by regulating miR-509-5p. Mechanistically, FOXM1 directly bound to the miR-509-5p promoter to inhibit miR-509-5p expression. Conclusion: FOXM1 directly binds to the promoter region of miR-509-5p to form a negative feedback loop, thereby inhibiting miR-509-5p expression and promoting the development of non-small-cell lung cancer. This study is expected to complement research on the pathogenesis of non-small-cell lung cancer and promote the development of novel therapeutic targets for this disease.

Abstract In this work, we report the monolithic three-dimensional integration (M3D) of hybrid memory architecture based on resistive random-access memory (RRAM), named M3D-LIME. The chip featured three key functional layers: the first was Si complementary metal-oxide-semiconductor (CMOS) for control logic; the second was computing-in-memory (CIM) layer with HfAlOx-based analog RRAM array to implement neural networks for feature extractions; the third was on-chip buffer and ternary content-addressable memory (TCAM) array for template storing and matching, based on Ta2O5-based binary RRAM and carbon nanotube field-effect transistor (CNTFET). Extensive structural analysis along with array-level electrical measurements and functional demonstrations on the CIM and TCAM arrays was performed. The M3D-LIME chip was further used to implement one-shot learning, where ~96% accuracy was achieved on the Omniglot dataset while exhibiting 18.3× higher energy efficiency than graphics processing unit (GPU). This work demonstrates the tremendous potential of M3D-LIME with RRAM-based hybrid memory architecture for future data-centric applications.

Low temperatures are the most significant abiotic stressor for the conservation and production of Phalaenopsis in non-tropical areas. CBF/DREB1 transcription factors play an important role in the plant abiotic stress response. In this study, 31 DREB family members were identified in the Phalaenopsis genome. Expression pattern analysis showed that the expression of different PaDREB members varied among tissue sites. PaDREB1D was isolated from Phalaenopsis aphrodite, and multiple sequence alignment showed that PaDREB1D belonged to the A1 subgroup of the DREB family and was localized in the nucleus. PaDREB1D overexpression in protocorm-like bodies of Phalaenopsis reduced cell damage during low-temperature stress, increased antioxidant enzyme activity, and enhanced the low-temperature tolerance of protocorm-like bodies. The results of this study provide a theoretical basis for breeding for cold resistance and investigating the molecular mechanisms related to low-temperature responses in Phalaenopsis.

Selenium is a vital trace mineral that is crucial for maintaining regular biological processes in aquatic animals. In this study, a four-week dietary trial was carried out to assess the impact of bio-fermented selenium (Bio−Se) on the growth and immune response of Chinese mitten crabs, Eriocheir sinensis. The crabs were randomly allocated to five dietary treatment groups, each receiving a different dose of Bio−Se. The doses included 0, 0.3, 0.6, 1.5, and 3.0 mg/kg and were accurately measured in basal diet formulations. The results showed the weight gain rate (WGR), specific growth rate (SGR), and survival rate (SR) in the 1.5 mg/kg Bio−Se group were the highest, and 3.0 mg/kg of Bio−Se has an inhibitory effect on the WGR, SGR, and SR. The activities of the immune enzymes, including glutathione peroxidase (GPX), superoxide dismutase (SOD), and acid phosphatase (ACP), of the hepatopancreas were significantly (p < 0.05) increased in the 1.5 mg/kg Bio−Se group, while they decreased (p < 0.05) in the 3.0 mg/kg feeding group compared to the 0 mg/kg feeding group. The concentration of maleic dialdehyde (MDA) exhibited the opposite pattern. Similarly, the mRNA expression levels of antimicrobial peptides (ALF-1, Crus-1, and LYS), ERK, and Relish genes were also observed to be the highest in the 1.5 mg/kg Bio−Se group compared with the other groups. Furthermore, the administration of 1.5 mg/kg of Bio−Se resulted in an increase in the thickness of the intestinal plica and mucosal layer, as well as in alterations in the intestinal microbial profile and bacterial diversity compared to the dose of 0 mg/kg of Bio−Se. Notably, the population of the beneficial bacterial phylum Fusobacteria was increased after crabs were fed the 1.5 mg/kg Bio−Se diet. In conclusion, the oral administration of 1.5 mg/kg of Bio−Se improved the growth efficiency, antioxidant capabilities, immunity, and intestinal health of E. sinensis. Through a broken-line analysis of the WGR against dietary Bio−Se levels, optimal dietary Bio−Se levels were determined to be 1.1 mg/kg. These findings contribute valuable insights to the understanding of crab cultivation and nutrition.

In this study, we describe the genetic characteristics of influenza A(H1N1)pdm09 strains detected in Myanmar from 2015 to 2019. Whole genomes from 60 A(H1N1)pdm09 virus isolates were amplified using real-time polymerase chain reaction and successfully sequenced using the Illumina iSeq100 platforms. Eight individual phylogenetic trees were retrieved for each segment along with those of the World Health Organization (WHO)-recommended Southern Hemisphere vaccine strains for the respective years. A(H1N1)pdm09 viruses from 2015 were found to belong to clade 6B, those from 2016 to 6B.1, 2017 to 6B.1A, and 2019 to 6B.1A.5a, and were genetically distinct from the Southern Hemisphere vaccine strains for the respective seasons, A/California/7/2009 and A/Michigan/45/2015. We observed one virus with intra-subtype reassortment, collected in the 2015 season. Importantly, three viruses possessed the H275Y substitution in the neuraminidase protein, appearing to be community-acquired without the prior administration of neuraminidase inhibitors. These viruses exhibited highly reduced susceptibility to oseltamivir and peramivir. This study demonstrates the importance of monitoring genetic variations in influenza viruses that will contribute to the selection of global influenza vaccines.

Ship trajectory prediction is a complex time series forecasting problem that necessitates models capable of accurately capturing both long-term trends and short-term fluctuations in vessel movements. While existing deep learning models excel in short-term predictions, they struggle with long-sequence time series forecasting (LSTF) due to difficulties in capturing long-term dependencies, resulting in significant prediction errors. This paper proposes the Informer-TP method, leveraging Automatic Identification System (AIS) data and based on the Informer model, to enhance the ability to capture long-term dependencies, thereby improving the accuracy of long-term ship trajectory predictions. Firstly, AIS data are preprocessed and divided into trajectory segments. Secondly, the time series is separated from the trajectory data in each segment and input into the model. The Informer model is utilized to improve long-term ship trajectory prediction ability, and the output mechanism is adjusted to enable predictions for each segment. Finally, the proposed model’s effectiveness is validated through comparisons with baseline models, and the influence of various sequence lengths Ltoken on the Informer-TP model is explored. Experimental results show that compared with other models, the proposed model exhibits the lowest Mean Squared Error, Mean Absolute Error, and Haversine distance in long-term forecasting, demonstrating that the model can effectively capture long-term dependencies in the trajectories, thereby improving the accuracy of long-term vessel trajectory predictions. This provides an effective and feasible method for ensuring ship navigation safety and advancing intelligent shipping.

Abstract Indole alkaloids are one of the largest alkaloid classes, proving valuable structural moiety in pharmaceuticals. Although methods for the synthesis of indole alkaloids are constantly explored, the direct single-step synthesis of these chemical entities with broad structural diversity remains a formidable challenge. Herein, we report a modular assembly of tetrahydrocarboline type of indole alkaloids from simple building blocks in a single step while showing broad compatibility with medicinally relevant functionality. In this protocol, the 2-alkylated or 3-alkylated indoles, formaldehyde, and amine hydrochlorides could undergo a one-pot reaction to deliver γ-tetrahydrocarbolines or β-tetrahydrocarbolines directly. A wide scope of these readily available starting materials is applicable in this process, and numerous structural divergent tetrahydrocarbolines could be achieved rapidly. The control reaction and deuterium-labelling reaction are conducted to probe the mechanism. And mechanistically, this multicomponent reaction relies on a multiple alkylamination cascade wherein an unusual C(sp3)–C(sp3) connection was involved in this process. This method could render rapid access to pharmaceutically interesting compounds, greatly enlarge the indole alkaloid library and accelerate the lead compound optimization thus facilitating drug discovery.

Abstract Acute lung injury (ALI) is one of the most common complications in COVID‐19 and also a syndrome of acute respiratory failure with high mortality rates, but lacks effective therapeutic drugs. Natural products provide inspiration and have proven to be the most valuable source for bioactive molecule discovery. In this study, the chemical evolution of the natural product Tanshinone IIA (Tan‐IIA) to achieve a piperidine‐fused scaffold through a synthetic route of pre‐activation, multi‐component reaction, and post‐modification is presented. Through biological evaluation, it is pinpointed that compound 8b is a standout candidate with remarkable anti‐inflammation and anti‐oxidative stress properties, coupled with low toxicity. The mechanistic study unveils a multifaceted biological profile of 8b and shows that 8b is highly efficient in vivo for the treatment of ALI. Therefore, this work not only provides an effective strategy for the treatment of ALI, but also offers a distinctive natural product‐inspired drug discovery.

It is posited that cognitive and affective dysfunction in patients with major depression disorder (MDD) may be caused by dysfunctional signal propagation in the brain. By leveraging dynamic causal modeling, we investigated large-scale directed signal propagation (effective connectivity) among distributed large-scale brain networks with 43 MDD patients and 56 healthy controls. The results revealed the existence of two mutual inhibitory systems: the anterior default mode network, auditory network, sensorimotor network, salience network and visual networks formed an “emotional” brain, while the posterior default mode network, central executive networks, cerebellum and dorsal attention network formed a “rational brain”. These two networks exhibited excitatory intra-system connectivity and inhibitory inter-system connectivity. Patients were characterized by potentiated intra-system connections within the “emotional/sensory brain”, as well as over-inhibition of the “rational brain” by the “emotional/sensory brain”. The hierarchical architecture of the large-scale effective connectivity networks was then analyzed using a PageRank algorithm which revealed a shift of the controlling role of the “rational brain” to the “emotional/sensory brain” in the patients. These findings inform basic organization of distributed large-scale brain networks and furnish a better characterization of the neural mechanisms of depression, which may facilitate effective treatment.

Abstract Reasonable production capacity is related to the economic benefits of an open-pit coal mine. This study analyzes the relationship between the working face length, the annual advancing speed and the production capacity. It constructs a production capacity function relationship model. Take the Baorixile open-pit coal mine as an example. The remaining unmined parts are divided into four regions, and the range of production capacity in each region is analyzed by the established model and the determined respectively. On this basis, three mining district division plans are proposed. By analyzing and comparing the stripping ratio, mining life of the district, fault influence, difficulty of transition connection in the mining districts, the convenience of transportation system layout and other indexes of each plan, Plan 3 is determined to be the optimal plan. The production capacity planning results of each mining district in this plan are as follows: the production capacity of the 3rd mining district is 30–35 Mt/a; the production capacity of the 4th mining district in Region 1 is 20–31 Mt/a, and the production capacity in Region 2 is 24–33 Mt/a; the production capacity of the 5th mining district is 20–27 Mt/a.

Abstract Medical imaging is an important tool for accurate medical diagnosis, while state-of-the-art image reconstruction algorithms raise critical challenges in massive data processing for high-speed and high-quality imaging. Here, we present a memristive image reconstructor (MIR) to greatly accelerate image reconstruction with discrete Fourier transformation (DFT) by computing-in-memory (CIM) with memristor arrays. A high-accuracy quasi-analogue mapping (QAM) method and generic complex matrix transfer (CMT) scheme was proposed to improve the mapping precision and transfer efficiency, respectively. High-fidelity magnetic resonance imaging (MRI) and computed tomography (CT) image reconstructions were demonstrated, achieving software-equivalent qualities and DICE scores after segmentation with nnU-Net algorithm. Remarkably, our MIR exhibited 153× and 79× improvements in energy efficiency and normalized image reconstruction speed, respectively, compared to graphics processing unit (GPU). This work demonstrates MIR as a promising high-fidelity image reconstruction platform for future medical diagnosis, and also largely extends the application of memristor-based CIM beyond artificial neural networks.

Abstract Small‐array high‐frequency surface wave radar (HFSWR) is widely used to monitor maritime targets as it can be used to save on‐land resources. In small‐array HFSWR systems, the main lobe of the receiving angle spectrum is significantly broadened. In complex clutter backgrounds, an extremely wide beam severely influences clutter suppression performance; consequently, targets with a low signal‐to‐clutter ratio (SCR) may be eliminated, or the angle may be barely estimated. This study proposes a space‐time adaptive processing (STAP) algorithm based on hyper beamforming (HBF) to improve the clutter suppression performance of small‐array HFSWR. In addition, HBF can obtain more independent identical distributed training samples than the conventional beamforming; thus, the STAP algorithm can extract the clutter information with high accuracy in the covariance matrix estimation. Moreover, this study combines an efficient STAP algorithm with a joint domain localised (JDL) algorithm to improve clutter suppression. Based on the experimental results, the proposed HBF‐JDL algorithm performs satisfactorily and significantly improves the SCR. Moreover, HBF‐JDL is still applicable at lower SCRs of the target compared with JDL.

Abstract Background This study assessed the differences in daily virus reduction and the residual infectivity after the recommended home stay period in Japan in patients infected with influenza and treated with baloxavir (BA), laninamivir (LA), oseltamivir (OS), and zanamivir (ZA). Methods We conducted an observational study on children and adults at 13 outpatient clinics in 11 prefectures in Japan during seven influenza seasons from 2013/2014 to 2019/2020. Virus samples were collected twice from influenza rapid test-positive patients at the first and second visit 4–5 days after the start of treatment. The viral RNA shedding was quantified using quantitative RT-PCR. Neuraminidase (NA) and polymerase acidic (PA) variant viruses that reduce susceptibility to NA inhibitors and BA, respectively, were screened using RT-PCR and genetic sequencing. Daily estimated viral reduction was evaluated using univariate and multivariate analyses for the factors such as age, treatment, vaccination status, or the emergence of PA or NA variants. The potential infectivity of the viral RNA shedding at the second visit samples was determined using the Receiver Operator Curve based on the positivity of virus isolation. Results Among 518 patients, 465 (80.0%) and 116 (20.0%) were infected with influenza A (189 with BA, 58 with LA, 181 with OS, 37 with ZA) and influenza B (39 with BA, 10 with LA, 52 with OS, 15 with ZA). The emergence of 21 PA variants in influenza A was detected after BA treatment, but NA variants were not detected after NAIs treatment. Multiple linear regression analysis showed that the daily viral RNA shedding reduction in patients was slower in the two NAIs (OS and LA) than in BA, influenza B infection, aged 0–5 years, or the emergence of PA variants. The residual viral RNA shedding potentially infectious was detected in approximately 10–30% of the patients aged 6–18 years after five days of onset. Conclusions Viral clearance differed by age, type of influenza, choice of treatment, and susceptibility to BA. Additionally, the recommended homestay period in Japan seemed insufficient, but reduced viral spread to some extent since most school-age patients became non-infectious after 5 days of onset.

Anthocyanins play a crucial role in imparting red coloration to pear fruits. However, the specific number and expression patterns of each member within the anthocyanin biosynthesis-related gene families in pears require systematic exploration. In this study, based on the pear genome we identified 15 gene families involved in the anthocyanin biosynthesis pathway using the BLASTP and Hidden Markov Model search methods, comprising a total of 94 enzyme genes. Through phylogenetic analysis, conserved domains, motif, and gene structure analysis, these gene families were further categorized into eight distinct lineages. Subsequent collinearity analysis revealed that the expansion of anthocyanin synthesis-related gene families primarily originated from segmental duplications. Analysis of cis-element in the promoter regions of genes related to anthocyanin synthesis unveiled the presence of light-responsive elements and various hormone-responsive elements. This suggests that changes in light stimulation and hormone levels may influence anthocyanin synthesis. RNA-Seq and qRT-PCR analyses indicated differential expression of anthocyanin biosynthesis-related genes between the peel and flesh tissues. During the accumulation of anthocyanins in red-fleshed pears, upstream genes in the anthocyanin biosynthesis pathway such as PbrPAL2, PbrC4H2, PbrC4H3, Pbr4CL2, Pbr4CL17, PbrF3H5, and PbrF3H6 exhibited high expression levels, likely contributing significantly to the red coloration of pear flesh. In summary, we have identified the number of gene family members involved in pear anthocyanin biosynthesis and analyzed the expression patterns of the genes related to pear anthocyanin biosynthesis. These findings provide a solid foundation for further research on the regulatory mechanisms underlying pear anthocyanin biosynthesis and the breeding of red pear varieties.

Citri Reticulatae Pericarpium, especially the pericarp of Citrus reticulata Blanco cv. Chachiensis (PCRC), is an important edible and medicinal ingredient for health and pharmacological properties. Citrus Huanglongbing, a devastating disease that currently threatens the citrus industry worldwide, is caused by a phloem-limited alpha-proteobacterium, “Candidatus Liberibacter asiaticus” (CLas). The industry of cultivar Chachiensis has been suffering from HLB. Although HLB affected the quality of citrus fruit, whether the quality of PCRC was affected by HLB remains unclear. In this study, we compared the metabolite profiles between HLB-affected and healthy PCRC from three sources: fresh, 6-month-old, and 9-year-old PCRC, through the untargeted LC–MS method. Compared to healthy controls, various types of bioactive compounds, mainly flavonoids, terpenoids, alkaloids, coumarins, polysaccharides, and phenolic acids, accumulated in HLB-affected PCRC, especially in the HLB-affected 9-year PCRC. In particular, isorhamnetin, isoliquiritigenin, luteolin 7-O-beta-D-glucoside, limonin, geniposide, pyrimidodiazepine, scoparone, chitobiose, m-coumaric acid, malonate, and pantothenic acid, which contributed to the pharmacological activity and health care effects of PCRC, were highly accumulated in HLB-affected 9-year-old PCRC compared to the healthy control. Multibioassay analyses revealed that HLB-affected 9-year-old PCRC had a higher content of total flavonoids and total polyphenols and exhibited similar antioxidant capacity as compared to healthy controls. The results of this study provided detailed information on the quality of HLB-affected PCRC.

Internal pore defects are inevitable during laser powder bed fusion (LPBF), which have a significant impact on the mechanical properties of the parts. Therefore, detecting pores and obtaining their morphology will contribute to the quality of LPBF parts. Currently, supervised models are used for defect image detection, which requires a large amount of LPBF sample data, image labeling, and computing power equipment during the training process, resulting in high detection costs. This study extensively collected LPBF sample data and proposed a method for pore defect classification by obtaining its morphological features while detecting pore defects in optical microscopy (OM) images under various conditions. Compared with other advanced models, the proposed method achieves better detection accuracy on pore defect datasets with limited data. In addition, quickly detecting pore defects in a large number of labeling ground truth images will also contribute to the development of deep learning. In terms of image segmentation, the average accuracy scores of this method in the test images exceed 85%. The research results indicate that the algorithm proposed in this paper is suitable for quickly and accurately identifying pore defects from optical microscopy images.

Achieving efficient photocatalytic activation of peroxymonosulfate (PMS) degradation of pollutants through the regulation strategy of surface microstructure in catalysts remains a challenge. Herein, CuBi2O4 nanorods (CBO NRs) and CuBi2O4 microspheres (CBO Ms) were synthesized by simply regulating the alkalinity of the reaction solvent. Under full–spectrum irradiation, CBO Ms exhibited remarkable photocatalytic performance, removing 92.48% of tetracycline (TC) within 12 min, with the reaction rate constant reaching 0.2135 min−1, which is approximately 2.7 times that of CBO NRs (0.0798 min−1). The exposure of oxygen vacancies on the surface of CBO Ms significantly promoted the generation and migration of photogenerated carriers internally, accelerated charge accumulation at the Cu active sites on the surface, and thereby enhanced the adsorption of CBO Ms on PMS. The charge density difference results confirmed the rapid transference of surface–enriched electrons to the PMS, facilitating further activation of PMS. Radical quenching experiment and EPR testing verified that both radical (SO4•−, •OH) and non–radical (1O2) pathways were involved in the reaction system. This study offers novel insights into the design of catalysts for the photocatalytic activation of PMS to efficiently degrade environmental pollutants.

With the increasing global demand for new energy sources, Photovoltaic (PV) is increasingly emphasized as a renewable energy source globally. Consequently, the assessment of PV resources has become crucial. Existing single frameworks and algorithms for PV resource assessment lead to low assessment accuracy. To alleviate the deficiency, this study proposes a two-layer network algorithm based on Xception and VGG19 for the evaluation of PV resources. The proposed method combines Xception convolutional neural network and VGG19 convolutional neural network. In addition, this study constructs a two-layer network framework based on the two-layer network algorithm. The feasibility and reliability of the proposed method are verified by simulating the proposed method under the case. Compared with existing algorithms, the proposed method and framework can improve the accuracy of PV resource assessment.

Targeted proteomics enables robust hypothesis-driven research. Here, Yu et al. present a multiplexed approach for targeted pathway proteomics and apply it to quantify protein families across 480 fully genotyped Diversity Outbred mice, revealing impacts of genetic variation on protein expression and lipid metabolism.

Soybean (Glycine max (L.) Merr.) is a globally significant crop, widely cultivated for oilseed production and animal feeds. In recent years, the rapid growth of multi-omics data from thousands of soybean accessions has provided unprecedented opportunities for researchers to explore genomes, genetic variations, and gene functions. To facilitate the utilization of these abundant data for soybean breeding and genetic improvement, the SoybeanGDB database (https://venyao.xyz/SoybeanGDB/) was developed as a comprehensive platform. SoybeanGDB integrates high-quality de novo assemblies of 39 soybean genomes and genomic variations among thousands of soybean accessions. Genomic information and variations in user-specified genomic regions can be searched and downloaded from SoybeanGDB, in a user-friendly manner. To facilitate research on genetic resources and elucidate the biological significance of genes, SoybeanGDB also incorporates a variety of bioinformatics analysis modules with graphical interfaces, such as linkage disequilibrium analysis, nucleotide diversity analysis, allele frequency analysis, gene expression analysis, primer design, gene set enrichment analysis, etc. In summary, SoybeanGDB is an essential and valuable resource that provides an open and free platform to accelerate global soybean research.

With the rapid development of intelligent technology, the smart heightened-containment biological laboratory (sHCBL) has moved from concept to reality. Experimental activities and laboratory construction, operation, and management will undoubtedly lead to disruptive changes. Conventional laboratories are increasingly being replaced by smart laboratories; however, the key technologies involved in this transition remain at an exploratory stage. It is necessary for HCBLs to absorb the advanced ideas of smart laboratories to guarantee the establishment of biosafety and biosecurity in a more automated way. This study examines in detail sHCBL module structures, the functions of each module, laboratory operation processes, and the advanced nature of smart laboratories. It may provide a theoretical foundation for the future transformation and smart construction of sHCBLs.