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Introduction: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. Objective: To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. Methods: We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. Results: The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm−1 showed a positive linear correlation with PD-L1 expression level. Conclusions: This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

Abstract Of the hitherto over 60 taxonomically identified species in the genus of Pseudo-nitzschia, 26 have been confirmed to be toxigenic. Nevertheless, the acquisition and evolution of the toxin biosynthesis (dab) genes by this extensive group of Pseudo-nitzschia species remains unclear. Through constructing chromosome-level genomes of three Pseudo-nitzschia species and draft genomes of ten additional Pseudo-nitzschia species, putative genomic integration sites for the dab genes in Pseudo-nitzschia species were explored. A putative breakpoint was observed in syntenic regions in the dab gene cluster-lacking Pseudo-nitzschia species, suggesting potential independent losses of dab genes. The breakpoints between this pair of conserved genes were also identified in some dab genes-possessing Pseudo-nitzschia species, suggesting that the dab gene clusters transposed to other loci after the initial integration. A “single acquisition, multiple independent losses (SAMIL)” model is proposed to explain the acquisition and evolution of the dab gene cluster in Pseudo-nitzschia species.

Abstract This study aims to broaden the morphological scope of SDH-deficient renal cell carcinoma and to assist clinicians and pathologists in better understanding this entity to prevent misdiagnosis. This study used immunohistochemistry staining and the first-generation sequencing Sanger method for gene detection. It retrospectively analysed the clinical pathology, molecular characteristics, biological behaviour, and treatment information of one case of SDH-deficient renal cell carcinoma. The patient was a 57-year-old female with right back pain for more than 20 days and had no personal or family history of kidney tumours. In addition, the tumour cells had clear boundaries in morphology, and residual normal renal tubules could be seen around them. There were also ossification and adipose tissue around the tumour centre. The tumour cells were arranged in a glandular tubular and cord-like manner. Vacuolar and eosinophilic inclusion bodies could be observed in the cytoplasm. The nucleus was regular, the chromatin distribution was fine, and there were no obvious nucleoli. They were low-grade nuclei. In addition, no atypical mitosis or necrosis could been found. Furthermore, immunohistochemistry staining showed SDHB-negative and keratin 20 -positive tumour. Meanwhile, the first-generation sequencing also pointed out the presence of SDHB gene mutations in the tumour. After 12 months of follow-up, there was no evidence of disease recurrence in the patient. SDH-deficient renal cell carcinoma is a rare tumour associated with SDH gene germline mutations, and suspected cases should undergo SDHB immunohistochemistry staining. Most SDH-deficient renal cell carcinomas have a good prognosis, but undifferentiated cases require long-term follow-up.

Methane is one of the long-lived greenhouse gases, with a global warming potential 28 times that of carbon dioxide, accounting for about 16% of the global warming effect. Coal production activities are one of the main sources of methane emissions in China. As one of the main coal production bases in China, Shanxi Province’s coal industry emits a large amount of methane. Using the high-resolution remote sensing data to estimate the methane emission from the coal industry in Shanxi Province can lay a data foundation for establishing a refined methane emission inventory of the coal industry and provide scientific basis for formulating effective emission reduction measures. Using the Advanced Hyperspectral Imager (AHSI) carried by China’s GF–5–02 satellite, 838 methane plumes from 408 factories and mines in Shanxi Province’s coal mining areas were detected and their emission rates were calculated using data from October 2021 to March 2023. The results show that: ① the methane plume emission rate in Shanxi Province’s coal mining areas shows asymmetry, with 84% of the plumes having emission rates between 0.5−3.0 t/h, but there are also a few extreme cases, with the highest emission rate exceeding 10.0 t/h.② Shanxi Province has six dense areas of point source emissions of methane, five of which correspond to the high-value areas of XCH4. ③ Methane emission point sources are detected, with coal mines and coking enterprises being the majority of emission sources. The average emission rate of different types of emission sources differs greatly, and the emission rate fluctuates with time and source changes. Methane emissions may occur in all stages of the coal mining. ④ Highly persistent emission sources account for only 13% of all point sources, but contribute 41% of the total emission rate. Conversely, highly intermittent emission sources account for 59%, but contribute only 25% of the total emission rate. The comprehensive methane emission rate of the coal industry in Shanxi Province is 177.17±56.35 t/h, mainly contributed by the methane emissions from coal mines, coking and thermal power enterprises.

New psychoactive substances (NPS) have become a global health and social problem. Their structures are variable and can be easily modified to produce new compounds. Traditional analytical techniques mostly rely on standard substances and mass spectrometry databases. The increased structural diversity of NPS makes the mass spectrometry databases be unable to comprehensively cover the mass spectra of all possible NPS, which in turn makes it difficult to perform structural identification of completely unknown compounds. Advances in machine learning have emerged as a potential solution to this dilemma. In this study, the k-nearestneighbor (KNN), support vector machine (SVM), random forests (RF) and artificial neural network (ANN) algorithms were constructed based on a dataset of mass spectra of 871 compounds. The four algorithmic models for identifying new psychoactive substances were used for structural classification prediction. The training and test sets were divided according to the ratio of 7:3, and the fit method was invoked on the training set to construct the model and train the parameters of the model, and the generalization ability of the model was evaluated on the test set. A grid search with 5-fold cross-validation was used to optimize the hyperparameters of the models. The performance of the four classification prediction models was evaluated by using the confusion matrix, accuracy, precision, recall and f-scores for each of the four models for characterizing 261 samples from the test set. Overall, the RF prediction model has the best classification prediction for the seven NPS as well as negative samples, with an overall accuracy of 89.27%, which is higher than the other three classification prediction models. The overall accuracies of the KNN, SVM, and ANN models are 79.31%, 83.14%, and 83.52%, respectively. In addition, the RF prediction model also has high accuracy for the NPS prediction of specific classes, and the accuracies for synthetic cathinones, fentanyl, synthetic cannabinoids, and benzodiazepines are 100%, 93%, 95%, and 100%, respectively, which can warrant good prediction for the structural classes of unknown compounds. In conclusion, this study develops a strategy for rapid analysis of new psychoactive substances using machine learning algorithms based on mass spectral datasets, realizing the classification prediction of structural classes of unknown compounds, thus providing a basis for the structural identification of unknown psychoactive compounds.

Abstract Background To investigate the effect of different working periods on missed diagnoses in patients with colorectal polyps in colonoscopy. Methods We conducted a retrospective analysis of patients who were diagnosed with colorectal polyps during colonoscopy in an outpatient department between July and December 2022. These patients were subsequently hospitalized for resection during this period. Patients with missed diagnoses were those who had newly discovered polyps in a second colonoscopy. The working periods were categorized as work, near the end of work, and delayed work, respectively, in the morning and afternoon. Results A total of 482 patients were included, and the miss rate of diagnosis was 48.1% (232/482), mainly in the transverse colon (25%), and the ascending colon (23%). Patient age was a risk factor for the miss rate of diagnosis (OR = 1.025, 95%CI: 1.009–1.042, P = 0.003) and was also associated with the number of polyps detected for the first colonoscopy (χ2 = 18.196, P = 0.001). The different working periods had no statistical effect on the missed rate of diagnosis (χ2 = 1.998, P = 0.849). However, there was an increasing trend in miss rates towards the end of work and delayed work periods, both in the morning and afternoon. The highest miss rate (60.0%) was observed during delayed work in the afternoon. Additionally, poor bowel preparation was significantly more common during delayed work in the afternoon. Conclusions The increasing trend in miss rates towards the end of work and delayed work periods deserves clinical attention. Endoscopists cannot always stay in good condition under heavy workloads.

Abstract Hydrogen sulfide is essential in numerous physiological and pathological processes and has emerged as a promising cancer imaging and signaling molecule and a potentially versatile therapeutic agent. However, the endogenous levels of hydrogen sulfide remain insufficient to perform its biological functions, and thus, developing novel strategies that amplify hydrogen sulfide signals at lesion sites is of increasing interest. In this work, a nanoplatform (SNP) based on hydrogen sulfide-responsive self-immolative poly(thiocarbamate) with localized hydrogen sulfide signal amplification capability is developed to encapsulate a hydrogen sulfide-responsive fluorescent probe (e.g., hemicyanine dye; p-Cy) or an anticancer prodrug (e.g., doxorubicin; p-DOX) to form a nanoprobe (SNPp-Cy) or nanomedicine (SNPp-DOX) for cancer imaging and therapy, respectively. SNPp-Cy exhibits a low detection limit for hydrogen sulfide, enabling ultrasensitive detection of small (

Abstract Background Work-related musculoskeletal disorders (WMSDs) show a rapid growth trend. It has brought a huge economic burden to the society and become a serious occupational health problem that needs to be solved urgently. This study aimed to analyze the local muscle response under continuous ergonomic load, screen sensitive fatigue-related biomarkers and provide data support for the early prevention of local muscle damage and the exploration of early warning indicators. Methods Thirteen male college student volunteers were recruited to perform simulated repetitive manual lifting tasks in the laboratory. The lifting task was designed for 4 periods which lasted for 12 min in each, and then paused for 3 min for sampling. Local muscle fatigue is assesed by the Rating of perceived exertion (RPE) and the Joint analysis of sEMG spectrum and amplitude (JASA). Elbow venous blood was collected and 14 kinds of biomarkers were analyzed, which included Metabolic markers Ammonia (AMM), Lactic acid (LAC), Creatine kinase (CK), Lactate dehydrogenase (LDH), Cartilage oligomeric matrix protein (COMP), C-telopeptide of collagen I and II (CTX-I, CTX-II) and Calcium ion (Ca2+); Oxidative stress marker Glutathione (GSH); Inflammatory markers C-reaction protein (CRP), Prostaglandin E2 (PG-E2), Interleukin-6 (IL-6) and Tumor necrosis factor α (TNF-α); Pain marker Neuropeptide Y (NPY). Repeated measures analysis of variance (Repeated ANOVA), linear regression analysis, t-test and spearman correlation analysis were used to analyze the data. Results Both subjective and objective fatigue appeared at the same period. Serum AMM, LAC, CK, LDH, COMP, CTX-II, Ca2+ and NPY after fatigue were significantly higher than those before fatigue (p

This is an article in the field of metallurgical engineering. A beneficiation and smelting plant processes two kinds of gold ores: primary ore and oxidized ore. The primary ore is treated by conventional flotation process. The gold recovery rate of flotation concentrate is about 85%, which is sold to smelting enterprises outside the province for cyanide leaching. The oxidized ore is treated by stirring cyanidation leaching activated carbon adsorption gold loaded carbon analytical electrodeposition gold slime smelting ingot casting process. The output gold ingot is sold outside, and the total recovery rate of gold dressing and metallurgy is about 90%. At present, with the deepening of mining depth, the ore properties change, the amount of oxidized ore gradually decreases, and the amount of primary ore gradually increases, resulting in excessive ore treatment in flotation system and insufficient ore treatment in leaching system, affecting the economic benefits of enterprises. Therefore, the enterprise considers adding the primary ore that cannot be treated by the flotation system to the existing oxidized ore all slime cyanidation leaching system to increase the gold ingot output and economic benefits of the enterprise. In order to enable the existing full slime cyanidation leaching system to leach the primary ore, based on the field investigation, the grinding fineness, reagent dosage and dissolved oxygen condition tests were carried out for the primary ore, and the alkali leaching pretreatment test and mixed oxidation ore leaching test were carried out in combination with the actual production. Based on these test and research results, specific rectification requirements and measures are put forward for the production site.

Abstract Thiophene is the organic sulfur with good thermal stability in carbon-based fuel, clarifying the conversion mechanism between thiophene and COS is beneficial for achieving in-situ sulfur fixation during CO2 gasification of carbon-based fuels, but the mechanism has rarely been reported. Therefore, calculations based on density functional theory were performed and 16 reaction paths were proposed in this research, clarifying the decomposition mechanism of thiophene and re-fixation mechanism of COS. The attachment of CO2 will lead to the destruction of the thiophene ring and the generation of COS, and CO2 adsorption is the rate-determined step, while the carbon atom that adjacent sulfur atom is the reaction active site. However, the energy barriers of CO2 addition reactions are lower than those of CO2 adsorption reactions, and the energy barrier of reactions occurring on the aliphatics are lower than that occurring on the aromatics. The combination of CO2 and thiophene will thermodynamically lead to the generation of COS and CO. Moreover, gaseous sulfur generated from thiophene decomposition will be converted mutually, while H2S will not be converted into COS. Furthermore, COS will be captured by char, forming solid organic sulfur. The re-fixation of COS will occur on aliphatic chains from the decomposition of aromatics.

ABSTRACT: As the stress-inducible isoform of the heat-shock protein 90 (HSP90), the HSP90AA1 gene encodes HSP90α and plays an important role in heat stress (HS) response. Therefore, this study aimed to investigate the role of the HSP90AA1 gene in cellular responses during HS and to identify functional SNPs associated with thermotolerance in Holstein cattle. For the in vitro validation experiment of acute HS, cells from the Madin-Darby bovine kidney cell line were exposed to 42°C for 1 h, and various parameters were assessed, including cell apoptosis, cell autophagy, and the cellular functions of HSP90α by using its inhibitor 17-allylamino-17-demethoxygeldanamycin (17-AAG). Furthermore, the polymorphisms identified in the HSP90AA1 gene and their functions related to HS were validated in vitro. Acute HS exposure induced cell apoptosis, cell autophagy, and upregulated expression of the HSP90AA1 gene. Inhibition of HSP90α by 17-AAG treatment had a significant effect on the expression of the HSP90α protein and increased cell apoptosis. However, autophagy decreased in comparison to the control treatment when cells were exposed to 42°C for 1 h. Five SNPs identified in the HSP90AA1 gene were significantly associated with rectal temperature and respiration score in Holstein cows, in which the rs109256957 SNP is located in the 3′ untranslated region (3′ UTR). Furthermore, we demonstrated that the 3′ UTR of HSP90AA1 is a direct target of bta-miR-1224 by cell transfection with exogenous microRNA (miRNA) mimic and inhibitor. The luciferase assays revealed that the SNP rs109256957 affects the regulation of bta-miR-1224 binding activity and alters the expression of the HSP90AA1 gene. Heat stress–induced HSP90AA1 expression maintains cell survival by inhibiting cell apoptosis and increasing cell autophagy. The rs109256957 located in the 3′ UTR region is a functional variation and it affects the HSP90AA1 expression by altering its binding activity with bta-miR-1224, thereby associating with the physiological parameters of Holstein cows.

Abstract Knowledge Distillation has shown promising results for classifying skin lesions in dermatology images. Traditional knowledge distillation typically involves the student model passively mimicking the teacher model's knowledge. We propose utilizing AdaBoost to enable the student to actively mine the teacher's learning representation for skin lesion classification. This paradigm allows the student to determine the “granularity” in mining the teacher's knowledge. As the student's learning process progresses, it can become challenging to pinpoint specific learning difficulties, especially with potential interference from the teacher. To address this issue, we introduce a variational difficulty mining strategy to reduce the impact of such interference. This strategy involves the distillation module capturing more nuanced classification difficulties by extracting information from the node's $$l$$ l th hops. By maximizing the mutual information between the teacher and student, we effectively filter out noise interference from these nuanced difficulties. Our proposed framework, Variational AdaBoost Knowledge Distillation (VAdaKD), allows the student to actively mine and leverage the teacher's knowledge for improved skin lesion classification. Our proposed method performs satisfactorily on three benchmark datasets: the Dermnet dataset, ISIC 2019 dataset, and HAM10000 dataset, respectively. Specifically, our method shows an improvement of 2–3% over the baseline on the Dermnet dataset and outperforms the best results of the other compared methods by 1%. Experimental results and visualization performance indicate that our proposed method effectively captures the learning difficulties and achieves better visualized t-distributed stochastic neighbor embedding classification results. Our code is available at https://github.com/25brilliant/VAdaKD .

Abstract During brain development, neural circuits undergo major activity-dependent restructuring. Circuit wiring mainly occurs through synaptic strengthening following the Hebbian “fire together, wire together” precept. However, select connections, essential for circuit development, are transient. They are effectively connected early in development, but strongly diminish during maturation. The mechanisms by which transient connectivity recedes are unknown. To investigate this process, we characterize transient thalamocortical inputs, which depress onto somatostatin inhibitory interneurons during development, by employing optogenetics, chemogenetics, transcriptomics and CRISPR-based strategies in mice. We demonstrate that in contrast to typical activity-dependent mechanisms, transient thalamocortical connectivity onto somatostatin interneurons is non-canonical and involves metabotropic signaling. Specifically, metabotropic-mediated transcription, of guidance molecules in particular, supports the elimination of this connectivity. Remarkably, we found that this process impacts the development of normal exploratory behaviors of adult mice.

This is an article in the field of mineral processing engineering. The gold mineral in an arsenic bearing high sulfur gold mine has a close symbiotic relationship with pyrite and arsenopyrite, and the recovery rate of concentrate gold is not ideal in the actual production process. In order to improve the recovery rate of concentrate gold and take into account the grade of concentrate gold, according to the characteristics of this mineral, the flotation process parameters and process are obtained through system condition test, flotation time test and beneficiation test, and then the open circuit test and closed circuit test are carried out to obtain better flotation indexes. In order to further improve the flotation index, the regrinding and flotation test of flotation middling is carried out, and the cyanide leaching test of middling regrinding flotation tailings is carried out. Finally, the satisfactory index of 91.94% of the total recovery of gold dressing and metallurgy is obtained.

Abstract Accurate prediction of oocyte maturation is a critical determinant of success in in vitro fertilization-embryo transfer (IVF-ET) procedures. This review provides a comprehensive analysis of the various predictive approaches employed to assess oocyte maturity, including single indicators, combined indicators, and predictive models. Factors such as ovarian reserve, patient characteristics, and controlled ovarian hyperstimulation (COH) strategies can significantly influence oocyte maturation rates. Single indicators, including hormone levels, ultrasound parameters, and clinical parameters, have been extensively studied. However, their predictive power may be limited when used in isolation. Combined indicators, integrating multiple parameters, have demonstrated improved predictive performance compared to single indicators. Additionally, predictive models and algorithms, such as machine learning and deep learning models, have emerged as promising tools for assessing oocyte maturity. These models leverage advanced statistical and computational methods to analyze complex datasets and identify patterns that can predict oocyte maturation rates with potentially higher accuracy. Despite these advancements, several gaps and limitations persist, including limited generalizability, lack of standardization, insufficient external validation, and the need to incorporate patient-specific factors and emerging technologies. The review highlights potential areas for further research, such as multicenter collaborative studies, integration of advanced omics technologies, development of personalized prediction models, and investigation of trigger time optimization strategies. Recommendations for clinical practice include utilizing a combination of indicators, adopting validated predictive models, tailoring approaches based on individual patient characteristics, continuous monitoring and adjustment, and fostering multidisciplinary collaboration. Accurate prediction of oocyte maturation holds profound implications for improving the success rates of IVF-ET and enhancing the chances of achieving a healthy pregnancy. Continued research, innovative approaches, and the implementation of evidence-based practices are essential to optimize assisted reproductive outcomes.

Abstract Background Inherited variations in DNA double-strand break (DSB) repair pathway are known to influence ovarian cancer occurrence, progression and treatment response. Despite its significance, survival-associated genetic variants within the DSB pathway remain underexplored. Methods In the present study, we performed a two-phase analysis of 19,290 single-nucleotide polymorphisms (SNPs) in 199 genes in the DSB repair pathway from a genome-wide association study (GWAS) dataset and explored their associations with overall survival (OS) in 1039 Han Chinese epithelial ovarian carcinoma (EOC) patients. After utilizing multivariate Cox regression analysis with bayesian false-discovery probability for multiple test correction, significant genetic variations were identified and subsequently underwent functional prediction and validation. Results We discovered a significant association between poor overall survival and the functional variant GEN1 rs56070363 C > T (CT + TT vs. TT, adjusted hazard ratio (HR) = 2.50, P T on survival was attributed to its reduced binding affinity to hsa-miR-1287-5p and the resultant upregulation of GEN1 mRNA expression. Overexpression of GEN1 aggregated EOC cell proliferation, invasion and migration presumably by influencing the expression of immune inhibitory factors, thereby elevating the proportion of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and then constructing an immunosuppressive tumor microenvironment. Conclusions In conclusion, GEN1 rs56070363 variant could serve as a potential predictive biomarker and chemotherapeutic target for improving the survival of EOC patients.

Aspergillus niger is an efficient cell factory for organic acids production, particularly l-malic acid, through genetic manipulation. However, the traditional method of collecting A. niger spores for inoculation is labor-intensive and resource-consuming. In our study, we used the CRISPR-Cas9 system to replace the promoter of brlA, a key gene in Aspergillus conidiation, with a xylose-inducible promoter xylP in l-malic acid-producing A. niger strain RG0095, generating strain brlAxylP. When induced with xylose in submerged liquid culture, brlAxylP exhibited significant upregulation of conidiation-related genes. This induction allowed us to easily collect an abundance of brlAxylP spores (>7.1 × 106/mL) in liquid xylose medium. Significantly, the submerged conidiation approach preserves the substantial potential of A. niger as a foundational cellular platform for the biosynthesis of organic acids, including but not limited to l-malic acid. In summary, our study offers a simplified submerged conidiation strategy to streamline the preparation stage and reduce labor and material costs for industrial organic acid production using Aspergillus species.

BackgroundBrain metastasis (BM) from cervical cancer (CC) is extremely rare. The prognosis of BM is poor. To our knowledge, no satisfactory therapeutic and standard effective treatments have been established. Immune checkpoint inhibitors (ICIs) treatment is emerging as a promising treatment in recurrence and metastasis(B/M) cervical cancer in recent years.CaseWe present a 50-year-old patient with CC who developed multiple metastasis (lung, brain and skin) 2 years after postoperative chemoradiotherapy. She received palliative therapy included chemotherapy, resection and stereotactic radiosurgery of BM with poor response. Then, the patient received second-line palliative monotherapy with a PD-1/CTLA-4 inhibitor(cadonilimab) and achieved clinical very good partial response (VGPR), a progression-free survival (PFS) of 14 months and overall survival of more than 18 months since BM.ConclusionWe report a case of cervical cancer with multiple metastasis receiving cadonilimab and achieved considerable response and survival benefit.

Abstract Precise identification of glioblastoma (GBM) microinfiltration, which is essential for achieving complete resection, remains an enormous challenge in clinical practice. Here, the study demonstrates that Raman spectroscopy effectively identifies GBM microinfiltration with cellular resolution in clinical specimens. The spectral differences between infiltrative lesions and normal brain tissues are attributed to phospholipids, nucleic acids, amino acids, and unsaturated fatty acids. These biochemical metabolites identified by Raman spectroscopy are further confirmed by spatial metabolomics. Based on differential spectra, Raman imaging resolves important morphological information relevant to GBM lesions in a label‐free manner. The area under the receiver operating characteristic curve (AUC) for Raman spectroscopy combined with machine learning in detecting infiltrative lesions exceeds 95%. Most importantly, the cancer cell threshold identified by Raman spectroscopy is as low as 3 human GBM cells per 0.01 mm2. Raman spectroscopy enables the detection of previously undetectable diffusely infiltrative cancer cells, which holds potential value in guiding complete tumor resection in GBM patients.

Although emerging evidence on the association between per- and polyfluoroalkyl substances (PFASs) and neurodevelopment have been investigated, there is no consensus on the effect of maternal PFASs on neurodevelopment in offspring. Here, we assessed the risk of maternal PFASs exposure on the neurodevelopment of offspring using a novel Targeted Risk Assessment of Environmental Chemicals (TRAEC) strategy based on multiple evidence. The evidence from five online databases were analyzed the effect of PFASs on neurodevelopment. The potential neurodevelopment risk of PFASs was evaluated by the TRAEC strategy, which was conducted on a comprehensive scoring system with reliability, correlation, outcome fitness and integrity. The studies from five databases and additional researchers’ experiments were included the present study to proceed following risk assessment. Based on the framework with TRAEC strategy, the comprehensive evaluation of health risks was classified as low (absolute value 0–4), medium (absolute value 4–8), high (absolute value 8–10). In the present study, the effect of PFASs exposure on neurodevelopment was a medium-risk level with 5.61 overall risk-score. The population-attributable risk (PAR) was 8.26 % for maternal PFASs exposure. The study identified a low-risk effect of prenatal PFASs exposure on ASD and behavioral disabilities. The chain length, type of PFASs and neurodevelopmental trajectories contributed to the risk of maternal PFASs on the neurodevelopment of offspring. Consistent with results of four criteria-based tools (ToxRTool, SciRAP, OHAT and IRIS), health risk assessment based on the TRAEC strategy demonstrated robustness and reliability in the present study. These results illustrated a medium-risk effect of maternal PFASs exposure on neurodevelopmental disorders of offspring. In addition, the TRAEC strategy provided a scientific and structured method for effect evaluation between prenatal PFASs and neurodevelopmental disorders, promoting the consistency and validation in risk assessment.

This study evaluates the carbon neutrality of eco-slope protection projects to understand their role in climate change mitigation. Utilizing life cycle assessment, it defines system boundaries and compiles inventories to calculate and analyze carbon emissions and assimilations of a wet-spraying vegetation concrete eco-slope protection project in China, simplifying previous methodologies and emphasizing the critical role of vegetation. Findings indicate lifecycle carbon emissions total 608.01 tCO2e, broken down by source as follows: material (54.69%), maintenance (40.11%), energy (3.27%), transport (1.32%), and workforce (0.6%). Slope protection plants are estimated to assimilate 2,676.30 tCO2. The project is estimated to reach carbon neutrality in its 4.59th year, with an anticipated net carbon sink contribution of 2,068.29 tons over its lifespan. These results underscore eco-slope protection projects’ significant carbon neutral capacity, highlighting their importance in combating climate change and fostering the civil engineering industry's green transformation. HIGHLIGHTS People are getting more serious about global warming. The Paris Climate Agreement of 2015 sets targets to limit global temperature rise.; A large number of traditional slope protection projects have generated a significant amount of GHG emissions, and eco-slope protection methods have attracted widespread attention.; Wet-spraying vegetation concrete eco-slope protection produces 608.01 tCO2e over its lifecycle.; Slope protection vegetations absorb 2,676.30 tCO2 over their lifecycle.;

Abstract Covalent organic frameworks (COFs) have been utilized as the ideal candidates to preciously construct electrocatalysts. However, the highly ordered degree of COFs renders the catalytic centers closely stacked, which limits the utilization efficiency of catalytic sites. Herein, we have first constructed dangling and staggered‐stacking aldehyde (–CHO) from [4 + 3] COFs as catalytic centers for 2e− oxygen reduction reaction (ORR). The new catalytic COFs have unreacted dangling ‐CHO out of the COFs' planes, which are more easily exposed in electrolytes than the sites in the frameworks. More importantly, these –CHO adopt staggered stacking models, and thus provide larger space for mass transport than those with eclipsed stacking models. In addition, by tuning the triratopic linkers in the COFs, the catalytic properties are well modulated. The optimized COF shows high selectivity and activity for 2e− ORR, with H2O2 selectivity of 91%, and mass activity of 12.2 A g−1, respectively. The theoretical calculation further reveals the higher activity for the pyridine‐contained B18C6‐PTTA‐COF due to the promoted binding ability of the intermediate OOH* at the carbon in dangling –CHO. This work provides us with a new insight into designing electrocatalysts based on COFs.

The growing interest in the growth and study of thin films of low-dimensional metallic delafossites, with the general formula ABO2, is driven by their potential to exhibit electronic and magnetic characteristics that are not accessible in bulk systems. The layered structure of these compounds introduces unique surface states as well as electronic and structural reconstructions, making the investigation of their surface behavior pivotal to understanding their intrinsic electronic structure. In this work, we study the surface phenomena of epitaxially grown PtCoO2, PdCoO2, and PdCrO2 films, utilizing a combination of molecular-beam epitaxy and angle-resolved photoemission spectroscopy. Through precise control of surface termination and treatment, we discover a pronounced 3×3 surface reconstruction in PtCoO2 films and PdCoO2 films, alongside a 2 × 2 surface reconstruction observed in PdCrO2 films. These reconstructions have not been reported in prior studies of delafossites. Furthermore, our computational investigations demonstrate the BO2 surface’s relative stability compared to the A-terminated surface and the significant reduction in surface energy facilitated by the reconstruction of the A-terminated surface. These experimental and theoretical insights illuminate the complex surface dynamics in metallic delafossites, paving the way for future explorations of their distinctive properties in low-dimensional studies.

Summary: The phytoplankton Phaeocystis globosa plays an important role in sulfur cycling and climate control, and can develop harmful algal blooms (HABs). Here we report a chromosome-scale reference genome assembly of P. globosa, which enable in-depth analysis of molecular underpinnings of important ecological characteristics. Comparative genomic analyses detected two-rounds of genome duplications that may have fueled evolutionary innovations. The genome duplication may have resulted in the formation of dual HiDP and LoDP dimethylsulphoniopropionate (DMSP) biosynthesis pathways in P. globosa. Selective gene family expansions may have strengthened biological pathways critical for colonial formation that is often associated with the development of algal blooms. The copy numbers of rhodopsin genes are variable in different strains, suggesting that rhodopsin genes may play a role in strain-specific adaptation to ecological factors. The successful reconstruction of the P. globosa genome sets up an excellent platform that facilitates in-depth research on bloom development and DMSP metabolism.

Deep-learning based approaches have been proven effective for Digital Elevation Model (DEM) super-resolution (SR) tasks. Previous networks typically treat DEM elevation values as single-channel image for input. However, DEM images alone cannot fully capture spatial and terrain features. Shaded relief images (SRIs), derived from DEMs, serve as crucial visual cues that intuitively convey terrain characteristics, addressing the limitations of DEM images and providing synergistic benefits for training DL models. The primary challenge in utilizing SRIs for guiding DEM SR lies in accurately selecting a consistent structure to extract and effectively integrate features from SRIs and DEMs. In this study, we propose an Attention-based Hierarchical Terrain Fusion (AHTF) framework for guided DEM SR. Specifically, an Attention-based Feature Fusion Module (AFFM) is designed to efficiently fuse relevant information from LR DEM and SRI, which includes a feature enhancement block to select valuable features and a feature recalibration block to fuse diverse terrain features. Additionally, we optimize the loss function from the perspectives of terrain analysis and visual effects. We validate AHTF on our newly constructed real-world Shade-DEM SR dataset and two open-source DEM SR datasets. Compared to the current state-of-the-art methods, our AHTF achieves the best results in terms of root mean square error (RMSE) for elevation, slope, and aspect. Furthermore, the extracted stream networks are closer to real-world conditions. This study offers new insights and methods for further research and application in the field of DEM super-resolution. Our dataset can be obtained at https://doi.org/10.6084/m9.figshare.25590945.

Magnetic Resonance Imaging (MRI) can provide the location and signal characteristics of pathological regions within a postmortem tissue block, thereby improving the efficiency of histopathological studies. However, such postmortem-MRI guided histopathological studies have so far only been performed on fixed samples as imaging tissue frozen at the time of extraction, while preserving its integrity, is significantly more challenging. Here we describe the development of cold-postmortem-MRI, which can preserve tissue integrity and help target techniques such as transcriptomics. As a first step, RNA integrity number (RIN) was used to determine the rate of tissue biomolecular degradation in mouse brains placed at various temperatures between -20 °C and +20 °C for up to 24 h. Then, human tissue frozen at the time of autopsy was immersed in 2-methylbutane, sealed in a bio-safe tissue chamber, and cooled in the MRI using a recirculating chiller to determine MRI signal characteristics. The optimal imaging temperature, which did not show significant RIN deterioration for over 12 h, at the same time giving robust MRI signal and contrast between brain tissue types was deemed to be −7 °C. Finally, MRI was performed on human tissue blocks at this optimal imaging temperatures using a magnetization-prepared rapid gradient echo (MPRAGE, isotropic resolution between 0.3–0.4 mm) revealing good gray-white matter contrast and revealing subpial, subcortical, and deep white matter lesions. RINs measured before and after imaging revealed no significant changes (n = 3, p = 0.18, paired t-test). In addition to improving efficiency of downstream processes, imaging tissue at sub-zero temperatures may also improve our understanding of compartment specificity of MRI signal.

Objectives To evaluate the efficacy of peri-trigger female reproductive hormones (FRHs) in the prediction of oocyte maturation in normal ovarian reserve patients during the in vitro fertilization-embryo transfer (IVF-ET) procedure. Materials and Methods A hospital database was used to extract data on IVF-ET cases from January 2020 to September 2021. The levels of female reproductive hormones, including estradiol (E2), luteinizing hormone (LH), progesterone (P), and follicle-stimulating hormone (FSH), were initially evaluated at baseline, the day of the trigger, the day after the trigger, and the day of oocyte retrieval. The relative change in E2, LH, P, FSH between time point 1 (the day of trigger and baseline) and time point 2 (the day after the trigger and day on the trigger) was defined as E2_RoV1/2, LH_RoV1/2, P_RoV1/2, and FSH_RoV1/2, respectively. Univariable and multivariable regression were performed to screen the peri-trigger FRHs for the prediction of oocyte maturation. Results A total of 118 patients were enrolled in our study. Univariable analysis revealed significant associations between E2_RoV1 and the rate of MII oocytes in the GnRH-agonist protocol group (p

Grain chalkiness directly affects the commercial value of rice. Genes related to chalkiness reported thus far have been discovered in mutants, but it has not been identified whether these genes can be used to improve rice quality by breeding. Therefore, discovering more quantitative trait loci (QTLs) or genes related to chalkiness in the rice germplasm is necessary. This study entails a genome-wide association study on the degree of endosperm chalkiness (DEC) and percentage of grains with chalkiness (PGWC) by combining 1.2 million single-nucleotide polymorphisms (SNPs) with the phenotypic data of 173 rice accessions. Thirteen QTLs for DEC and nine for PGWC were identified, of which four were detected simultaneously for both DEC and PGWC; further, qDEC11/qPGWC11 was identified as the major QTL. By combining linkage disequilibrium analysis and SNP information, LOC_Os11g10170 was identified as the candidate gene for DEC. There were significant differences among the haplotypes of LOC_Os11g10170, and the Hap 1 of LOC_Os11g10170 was observed to reduce the DEC by 6.19%. The qRT-PCR results showed that the gene expression levels in accessions with high DEC values were significantly higher than those in accessions with low DEC values during days 21–42 after flowering, with a maximum at 28 days. These results provide molecular markers and germplasm resources for genetic improvement of the chalkiness-related traits in rice.

Abstract Self‐powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric sensors well respond to dynamic stimuli while overlooking static stimuli. This study proposes a dual‐response potentiometric pressure sensor that responds to both dynamic and static stimuli. The proposed sensor utilizes interdigital electrodes with MnO2/carbon/polyvinyl alcohol (PVA) as the cathode and conductive silver paste as the anode. The electrolyte layer incorporates a mixed hydrogel of PVA and phosphoric acid. The optimized interdigital electrodes and sandpaper‐like microstructured surface of the hydrogel electrolyte contribute to enhanced performance by facilitating an increased contact area between the electrolyte and electrodes. The sensor features an open‐circuit voltage of 0.927 V, a short‐circuit current of 6 µA, a higher sensitivity of 14 mV/kPa, and outstanding cycling performance (>5000 cycles). It can accurately recognize letter writing and enable capacitor charging and LED lighting. Additionally, a data acquisition and display system employing the proposed sensor, which facilitates the monitoring of athletes’ rehabilitation training, and machine learning algorithms that effectively guide rehabilitation actions are presented. This study offers novel solutions for the future development of smart wearable devices.

The advent of general anesthesia (GA) has significant implications for clinical practice. However, the exact mechanisms underlying GA-induced transitions in consciousness remain elusive. Given some similarities between GA and sleep, the sleep-arousal neural nuclei and circuits involved in sleep-arousal, including the 5-HTergic system, could be implicated in GA. Herein, we utilized pharmacology, optogenetics, chemogenetics, fiber photometry, and retrograde tracing to demonstrate that both endogenous and exogenous activation of the 5-HTergic neural circuit between the dorsal raphe nucleus (DR) and basolateral amygdala (BLA) promotes arousal and facilitates recovery of consciousness from sevoflurane anesthesia. Notably, the 5-HT1A receptor within this pathway holds a pivotal role. Our findings will be conducive to substantially expanding our comprehension of the neural circuit mechanisms underlying sevoflurane anesthesia and provide a potential target for modulating consciousness, ultimately leading to a reduction in anesthetic dose requirements and side effects.

Gypsum particleboard is attracting attention in the construction industry due to its excellent properties. However, the traditional raw materials for gypsum particleboard are facing a shortage of supply. In this study, we innovatively utilized bulk solid waste Phosphogypsum and Pennisetum giganteum for the first time to manufacture gypsum particleboard. This approach not only effectively addresses the issue of insufficient supply of traditional raw materials for gypsum particleboard but also provides a new pathway for the resource utilization of phosphogypsum. Through an orthogonal experimental design, we focused on optimizing the gypsum particleboard formulation, concentrating on factors such as density, the ratio of Pennisetum giganteum to gypsum (grass-plaster ratio), the ratio of water to gypsum (water-plaster ratio), and the size of the particles. The study determined that the optimal formulation parameters were a density of 1.2 g/cm³, a grass-plaster ratio of 0.20, a water-plaster ratio of 0.25, and a particle mesh number of 14. Under these conditions, the gypsum particleboard exhibited excellent performance, characterized by a static flexural strength of 6.5 MPa, a modulus of elasticity of 2010 MPa, an internal bond strength of 0.4 MPa, a 24-hour water-absorption thickness expansion rate of 2.2%, and an equilibrium moisture content of 1.6%, all meeting the American Society for Testing and Materials (ASTM) Standard D1037. These findings indicate that gypsum particleboards made with Pennisetum giganteum and phosphogypsum can perform comparably to those made with conventional materials. Additionally, a performance prediction model was established using Multiple Linear Regression Analysis (MLRA). The analysis revealed a significant linear relationship between the independent and dependent variables in the model, with the Analysis of Variance (ANOVA) significance levels being less than 0.05, demonstrating statistical significance. This result provides a theoretical basis for the future development of high-performance gypsum particleboard.

Exposure to PM2.5 is correlated with cardiac remodeling, of which cardiac hypertrophy is one of the main clinical manifestations. Ferroptosis plays an important role in cardiac hypertrophy. However, the potential mechanism of PM2.5-induced cardiac hypertrophy through ferroptosis remains unclear. This study aimed to explore the molecular mechanism of cardiac hypertrophy caused by PM2.5 and the intervention role of MitoQ involved in this process. The results showed that PM2.5 could induce cardiac hypertrophy and dysfunction in mice. Meanwhile, the characteristics of ferroptosis were observed, such as iron homeostasis imbalance, lipid peroxidation, mitochondrial damage and abnormal expression of key molecules. MitoQ treatment could effectively mitigate these alternations. After treating human cardiomyocyte AC16 with PM2.5, ferroptosis activator (Erastin) and inhibitor (Fer-1), it was found that PM2.5 could promote ferritinophagy and lead to lipid peroxidation, mitochondrial dysfunction as well as the accumulation of intracellular and mitochondrial labile iron. Subsequently, mitophagy was activated and provided an additional source of labile iron, enhancing the sensitivity of AC16 cells to ferroptosis. Furthermore, Fer-1 alleviated PM2.5-induced cytotoxicity and iron overload in the cytoplasm and mitochondria of AC16 cells. It was worth noting that during the process of PM2.5 caused ferroptosis, abnormal iron metabolism mediated the activation of ferritinophagy and mitophagy in a temporal order. In addition, NCOA4 knockdown reversed the iron homeostasis imbalance and lipid peroxidation caused by PM2.5, thereby alleviating ferroptosis. In summary, our study found that iron homeostasis imbalance-mediated the crosstalk of ferritinophagy and mitophagy played an important role in PM2.5-induced ferroptosis and cardiac hypertrophy.

Abstract Background Haemaphysalis concinna, carrying multiple pathogens, has attracted increasing attention because of its expanded geographical range and significant role in disease transmission. This study aimed to identify the potential public health risks posed by H. concinna and H. concinna-associated pathogens. Methods A comprehensive database integrating a field survey, literature review, reference book, and relevant websites was developed. The geographical distribution of H. concinna and its associated pathogens was illustrated using ArcGIS. Meta-analysis was performed to estimate the prevalence of H. concinna-associated microbes. Phylogenetic and geographical methods were used to investigate the role of birds in the transmission of H. concinna-associated microbes. The potential global distribution of H. concinna was predicted by ecological niche modeling. Results Haemaphysalis concinna was distributed in 34 countries across the Eurasian continent, predominantly in China, Russia, and Central Europe. The tick species carried at least 40 human pathogens, including six species in the Anaplasmataceae family, five species of Babesia, four genospecies in the complex Borrelia burgdorferi sensu lato, ten species of spotted fever group rickettsiae, ten species of viruses, as well as Francisella, Coxiella, and other bacteria. Haemaphysalis concinna could parasitize 119 host species, with nearly half of them being birds, which played a crucial role in the long-distance transmission of tick-borne microbes. Our predictive modeling suggested that H. concinna could potentially survive in regions where the tick has never been previously recorded such as central North America, southern South America, southeast Oceania, and southern Africa. Conclusions Our study revealed the wide distribution, broad host range, and pathogen diversity of H. concinna. Authorities, healthcare professionals, and the entire community should address the growing threat of H. concinna and associated pathogens. Tick monitoring and control, pathogen identification, diagnostic tools, and continuous research should be enhanced. Graphical Abstract

Abstract Covalent organic frameworks (COFs) are ideal templates for constructing metal-free catalysts for the oxygen reduction reaction due to their highly tuneable skeletons and controllable porous channels. However, the development of highly active sites within COFs remains challenging due to their limited electron-transfer capabilities and weak binding affinities for reaction intermediates. Herein, we constructed highly active catalytic centres by modulating the electronic states of the pyridine nitrogen atoms incorporated into the frameworks of COFs. By incorporating different pyridine units (such as pyridine, ionic pyridine, and ionic imidazole units), we tuned various properties including dipole moments, reductive ability, hydrophilicity, and binding affinities towards reaction intermediates. Notably, the ionic imidazole COF (im-PY-BPY-COF) exhibited greater activity than the neutral COF (PY-BPY-COF) and ionic pyridine COF (ion-PY-BPY-COF). Specifically, im-PY-BPY-COF demonstrated a half-wave potential of 0.80 V in 0.1 M KOH, outperforming other metal-free COFs. Theoretical calculations and in situ synchrotron radiation Fourier transform infrared spectroscopy confirmed that the carbon atoms in the ionic imidazole rings improved the activity by facilitating binding of the intermediate OOH* and promoting the desorption of OH*. This study provides new insights into the design of highly active metal-like COF catalysts.

Abstract Background Haemaphysalis longicornis is drawing attentions for its geographic invasion, extending population, and emerging disease threat. However, there are still substantial gaps in our knowledge of viral composition in relation to genetic diversity of H. longicornis and ecological factors, which are important for us to understand interactions between virus and vector, as well as between vector and ecological elements. Results We conducted the meta-transcriptomic sequencing of 136 pools of H. longicornis and identified 508 RNA viruses of 48 viral species, 22 of which have never been reported. Phylogenetic analysis of mitochondrion sequences divided the ticks into two genetic clades, each of which was geographically clustered and significantly associated with ecological factors, including altitude, precipitation, and normalized difference vegetation index. The two clades showed significant difference in virome diversity and shared about one fifth number of viral species that might have evolved to “generalists.” Notably, Bandavirus dabieense, the pathogen of severe fever with thrombocytopenia syndrome was only detected in ticks of clade 1, and half number of clade 2-specific viruses were aquatic-animal-associated. Conclusions These findings highlight that the virome diversity is shaped by internal genetic evolution and external ecological landscape of H. longicornis and provide the new foundation for promoting the studies on virus-vector-ecology interaction and eventually for evaluating the risk of H. longicornis for transmitting the viruses to humans and animals. Video Abstract

Satellite-derived bathymetry (SDB) combining the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) measurements and multispectral images is expected to fill the gap of depth data in global coastal areas. Image radiometric resolution is an important index of surface reflectance recorded by satellite, which affects the seabed details by bathymetric methods. With the improvement of radiometric resolution, the effect of the radiometric resolution remains to be clarified. This study quantifies the performance of Landsat ETM+, OLI, and OLI-2 images through a mature workflow and provides a reference for selecting data with a suitable radiometric resolution for bathymetry. The results in Culebra, Puerto Rico, show that the performance of Landsat 8 OLI is the best, with an RMSE of 2.53 m. The radiometric resolution affects the sensor’s perception of watercolor changing with depth and environmental radiation changing. With the improvement of radiometric resolution, the negative impact of environmental factors will reduce the performance of images.

Accurate oceanic eddy detection is crucial for understanding their dynamic behavior. In this study, we apply attention dual-U-net, a specialized deep learning model, to simultaneously detect the location and contours of mesoscale eddies in the South China Sea (SCS). This model integrates various features from satellite-observed absolute dynamic topography and sea surface temperature anomaly (SSTA), and is established separately for anticyclonic eddies (AEs) and cyclonic eddies (CEs) detection. Eddy contours from the delayed-time altimetric mesoscale eddy trajectories atlas are used for model training and evaluation. Results indicate that the model excels in detecting the shape and location of mesoscale eddies in the SCS, achieving success detection rates (SDRs) of 95.2% for AEs and 94.7% for CEs. Incorporating SSTA as an additional input enhances the accuracy of eddy shape and aids in further distinguishing normal from abnormal eddies. Abnormal eddies, characterized by cold AEs and warm CEs, constitute 16.8% and 29.8% of total AEs and CEs, respectively, with SDRs of 95.3% and 94.7%, underscoring the model robustness to abnormal eddies. Moreover, the mean absolute errors of AEs (CEs) are notably smaller than those estimated by the pyramid scene parsing network and EddyNet, with reductions of 49.1% (45.1%) and 67.6% (70.8%), respectively. These reductions are particularly pronounced in coastal areas and deep waters exceeding 200 m in depth. The amalgamation of the accurate eddy detection model and high-resolution multisatellite observations presents an effective approach to capturing eddy occurrences, contributing to a comprehensive understanding of eddy dynamics in marginal seas and open oceans.

The precise generation of train control curves for the on-board Automatic Train Protection (ATP) of the Chinese Train Control System Level 2 (CTCS-2) relies significantly on accurate train control engineering data, which serves as a critical element in ensuring the safe operation of trains. However, the traditional verification methods of train control engineering data depend on manual validation, which lacks timeliness and completeness and makes it easy to overlook potential errors. On the other hand, traditional verification rules are derived from railway technical specifications and standards, expressed in textual language that is often ambiguous, which leads to insufficient completeness in data verification. To address these challenges, this paper proposes a formal verification method for train control engineering data based on a Reduced Ordered Binary Decision Diagram (ROBDD). First, the attribute constraints of the train control data and the implicit constraint relations between different data objects are mined using existing railway technical specifications and expert knowledge of railway signals. These constraints are then converted into Boolean function models. Second, we formulate the ROBDD generation algorithm and the evaluation decision algorithm of the Boolean function using the equivalent canonical data structure ROBDD of the Boolean function. Finally, based on the train control engineering data from actual passenger-dedicated lines, the automatic verification method is developed by constructing four types of “mutation” data, including mutate, swap, add, and remove. The test cases indicate that our proposed formal verification method is feasible and capable of achieving high efficiency and completeness in the verification of CTCS-2 level train control engineering data.

Abstract Background Malaria remains a significant public health concern in Niger, with the number of cases increasing from 592,334 in 2000 to 3,138,696 in 2010. In response, a concerted campaign against the disease has been initiated. However, the implementation of these malaria interventions and their association with epidemiological behaviour remains unclear. Methods A time-series study was conducted in Niger from 2010 to 2019. Multiple data sources concerning malaria were integrated, encompassing national surveillance data, Statistic Yearbook, targeted malaria control interventions, and meteorological data. Incidence rate, mortality rate, and case fatality ratio (CFR) by different regions and age groups were analysed. Joinpoint regression models were used to estimate annual changes in malaria. The changes in coverage of malaria interventions were evaluated. Results Between 2010 to 2019, the incidence rate of malaria decreased from 249.43 to 187.00 cases per 1,000 population in Niger. Niamey had a high annual mean incidence rate and the lowest CFR, while Agadez was on the contrary. Joinpoint regression analysis revealed a declining trend in malaria incidence for all age groups except the 10–24 years group, and the mortality rate and the CFR initially decreased followed by an increase in all age groups. Niger has implemented a series of malaria interventions, with the major ones being scaled up to larger populations during the study period. Conclusions The scale-up of multi-interventions in Niger has significantly reduced malaria incidence, but the rise in mortality rate and CFR addresses the challenges in malaria control and elimination. Malaria endemic countries should enhance surveillance of malaria cases and drug resistance in Plasmodium, improve diagnosis and treatment, expand the population coverage of insecticide-treated bed nets and seasonal malaria chemoprevention, and strengthen the management of severe malaria cases.

Abstract Covalent organic frameworks (COFs) have been developed as the precursors to construct porous carbons for electrocatalytic systems. However, the influences of carbon dimensions on the catalytic performance are still underexplored. In this work, we have first constructed COF‐derived carbons by template‐synthesis strategy in different dimensions to catalyze the carbon dioxide reduction (CO2RR). By using different templates, the one‐dimensional (1D), two‐dimensional (2D), and three‐dimensional (3D) COF‐derived carbons have been employed to anchor Co‐porphyrin to form the Co‐N5 sites to catalyze CO2RR. The 1D catalyst templated by carbon nano tubes presents high binding ability of CO2, more defective sites, and higher electronic conductivity, resulting in a higher catalytic activity for CO2 and selectivity of CO than 2D and 3D carbon‐based catalysts. The 1D catalyst delivers the turnover frequency values of 1150 h−1 and the FECO of 94.5% at 0.7 V versus RHE, which is significantly better than those of 2D and 3D carbon‐based catalysts.

In autonomous driving, target tracking is essential to environmental perception. The study of target tracking algorithms can improve the accuracy of an autonomous driving vehicle’s perception, which is of great significance in ensuring the safety of autonomous driving and promoting the landing of technical applications. This study focuses on the fusion tracking algorithm based on visible and infrared images. The proposed approach utilizes a feature-level image fusion method, dividing the tracking process into two components: image fusion and target tracking. An unsupervised network, Visible and Infrared image Fusion Network (VIF-net), is employed for visible and infrared image fusion in the image fusion part. In the target tracking part, Siamese Region Proposal Network (SiamRPN), based on deep learning, tracks the target with fused images. The fusion tracking algorithm is trained and evaluated on the visible infrared image dataset RGBT234. Experimental results demonstrate that the algorithm outperforms training networks solely based on visible images, proving that the fusion of visible and infrared images in the target tracking algorithm can improve the accuracy of the target tracking even if it is like tracking-based visual images. This improvement is also attributed to the algorithm’s ability to extract infrared image features, augmenting the target tracking accuracy.

The flexible pressure sensor has been credited for leading performance including higher sensitivity, faster response/recovery, wider detection range and higher mechanical durability, thus driving the development of novel sensing materials enabled by new processing technologies. Using atomic layer infiltration, Pt nanocrystals with dimensions on the order of a few nanometers can be infiltrated into the compressible lamellar structure of Ti3C2Tx MXene, allowing a modulation of its interlayer spacing, electrical conductivity and piezoresistive property. The flexible piezoresistive sensor is further developed from the Pt-infiltrated MXene on a paper substrate. It is demonstrated that Pt infiltration leads to a significant enhancement of the pressure-sensing performance of the sensor, including increase of sensitivity from 0.08 ​kPa−1 to 0.5 ​kPa−1, extension of detection limit from 5 ​kPa to 9 ​kPa, decrease of response time from 200 ​ms to 20 ​ms, and reduction of recovery time from 230 ​ms to 50 ​ms. The mechanical durability of the flexible sensor is also improved, with the piezoresistive performance stable over 1000 cycles of flexure fatigue. The atomic layer infiltration process offers new possibilities for the structure modification of MXene for advanced sensor applications.

Abstract Introduction Throughout the COVID-19 pandemic, underserved populations, such as racial and ethnic minorities, were disproportionately impacted by illness, hospitalization, and death. Equity in clinical trials means that the participants in clinical trials represent the people who are most likely to have the health condition and need the treatment that the trial is testing. Infodemiology approaches examining user conversations on social media platforms have the potential to elucidate specific barriers and challenges related to clinical trial participation, including among racial and ethnic minority populations. Materials and methods The study retrospectively collected and analyzed user question and answer posts from Quora in October 2021 using an inductive content coding approach. We also examined user’s publicly available profile metadata to identify racial and ethnic minority users to capture their experiences, attitudes, topics, and discussions of barriers to COVID-19 vaccine trials. Results A total of 1073 questions and 7479 answers were collected. A total of 763 questions and 2548 answers were identified as related to COVID-19 vaccine clinical trials. The majority of these online interactions focused on asking questions and sharing knowledge and opinions about COVID-19 vaccine trials, including major topics related to: (a) interpreting whether clinical trial results could be trusted; (b) questions about vaccine efficacy and safety; (c) understanding trial design, regulatory considerations, and vaccine platforms; and (d) questions about trial enrollment, length, and adequate representation. Additionally, four major barriers discussed included: (i) disagreement from users regarding whether clinical trials require representation from different racial and ethnic minorities; (ii) concerns regarding the safety of trials when participating; (iii) lack of knowledge on how to participate in a trial; and (iv) questions of whether participants could withdraw from a trial to access an approved COVID-19 vaccine. Conclusions Our study found active user discussions related to COVID-19 vaccine clinical trials on Quora, including those specific to minority health topics and those posted by a smaller group of self-identified racial and ethnic minority online users. Results from this study can help identify barriers to participation among the general public and underrepresented groups while also supporting the design of future outreach strategies to help with recruitment and inclusive trial participation.

The Japanese grenadier anchovy Coilia nasus Temminck & Schlegel, 1846 belongs to the family Engraulidae of the order Clupeiformes. This species is widely distributed in China, Japan, and Korea and in Northwest Pacific Ocean. In China, C. nasus is found in the Bohai Sea, the Yellow Sea, the East China Sea, and the middle and lower reaches and the estuaries of some main rivers, such as the Liao River, the Yellow River, and the Yangtze River. The life history of C. nasus is diverse and it is found to have three main ecological types (i.e., anadromous migratory, freshwater resident, and freshwater landlocked), indicating its strong adaptability to different habitats. Because of its commercial importance in China, C. nasus has been heavily exploited for years. Due to the significant decline of the wild stocks and the degeneration of freshwater spawning grounds in its distribution region, C. nasus was listed in the IUCN Red List of Threatened Species as "Endangered" category in 2018.Currently, the exact distribution boundary of C. nasus to the southern limit of China is unclear. Based on the fishery surveys in the southern Zhejiang Province for the past 15 years, the adjacent waters of Ou River estuary in Wenzhou are the known southernmost distribution area for C. nasus. The distribution of C. nasus in Fujian waters, both freshwater and seawater was documented from 1960—2008; however, the sampled individuals were very rare. It is impossible to understand the habitat history and life history pattern of C. nasus using traditional fishery survey methods. In this study, three C. nasus individuals were collected by trawl net, set net, and gill net in Fuzhou and Ningde waters in 2017—2019 during various fishery surveys along the coastline of Fujian. To reconstruct the life history of C. nasus in Fujian waters, the X-ray electron probe micro-analysis (EPMA) approach was used to analyze otolith (sagitta) microchemistry patterns of the fish for the first time. Otolith microchemistry is an effective tool for revealing the anadromous pattern and the spatial and temporal distribution of fishes. The otolith Sr/Ca ratios are powerful indicators for identifying freshwater, brackish water, and seawater habitats throughout the life history of fish.The results of this study showed that the Sr/Ca ratios of the otolith core areas of all three C. nasus individuals were less than 3, and the core areas exhibited a blue pattern in the X-ray intensity maps of Sr content. Both results indicated that the three individuals originated from freshwater and hatched in freshwater habitat. Among the three individuals, the individual collected in Fuzhou waters was more dependent on freshwater at its early life stage and did not enter brackish water until it was almost 1-year-old. Combined with the sampling site and the adjacent water of Min River, it is deduced that it might have originated from the pure freshwater habitat of Min River. Two individuals collected in Ningde waters were less dependent on freshwater habitat at their early life stage. Combined with the sampling sites, i.e., the outer water of Sansha Bay, it is deduced that the two individuals from Ningde might have originated from the pure freshwater habitat of Jiao Brook in Ningde, Ou River in Wenzhou, or Min River in Fuzhou. According to the fluctuations of the Sr/Ca ratio from the core to the edge of the otoliths and X-ray intensity maps of Sr content through the otolith core, all three C. nasus individuals were confirmed to be typically anadromous ecological types. The habitat history of the only one C. nasus individual in Fuzhou was a freshwater-brackish type; its hatching and early life stage were also associated with freshwater habitat, and then it entered the brackish water habitat and traveled back and forth between brackish water and freshwater habitats to grow out until it was captured. The habitat history of the other two C. nasus individuals in Ningde was freshwater-brackish-seawater type; their hatching and early life stage were associated with freshwater habitat, and then they entered high salinity habitat and traveled back and forth between brackish water and seawater habitats for growth until captured. Moreover, we found that the higher salinity in the capture waters of the three C. nasus individuals did not correspond to the Sr/Ca ratio at the edge of the otoliths, indicating a certain time delay in otolith responding to the salinity of their most present living habitats.This study not only revealed the diversity of C. nasus life history patterns and habitat histories but also confirmed the current distribution of anadromous C. nasus in Fujian waters. Since February 2019, the Yangtze River, the most important habitat for C. nasus and many endangered fishes and mammals has initiated a new management measure, i.e., a 10-year fishing ban plan. However, there is still a lack of sufficient understanding of the distribution, the locations of spawning grounds and the population size of C. nasus in Fujian waters. Further studies on the key habitats of C. nasus such as spawning ground and ecological type are needed to formulate effective management measures for its natural resource conservation in Fujian waters.

Precisely identifying interior decoration styles holds substantial significance in directing interior decoration practices. Nevertheless, constructing accurate models for the automatic classification of interior decoration styles remains challenging due to the scarcity of expert annotations. To address this problem, we propose a novel pseudo-label-guided contrastive mutual learning framework (PCML) for semi-supervised interior decoration style classification by harnessing large amounts of unlabeled data. Specifically, PCML introduces two distinct subnetworks and selectively utilizes the diversified pseudo-labels generated by each for mutual supervision, thereby mitigating the issue of confirmation bias. For labeled images, the inconsistent pseudo-labels generated by the two subnetworks are employed to identify images that are prone to misclassification. We then devise an inconsistency-aware relearning (ICR) regularization model to perform a review training process. For unlabeled images, we introduce a class-aware contrastive learning (CCL) regularization to learn their discriminative feature representations using the corresponding pseudo-labels. Since the use of distinct subnetworks reduces the risk of both models producing identical erroneous pseudo-labels, CCL can reduce the possibility of noise data sampling to enhance the effectiveness of contrastive learning. The performance of PCML is evaluated on five interior decoration style image datasets. For the average AUC, accuracy, sensitivity, specificity, precision, and F1 scores, PCML obtains improvements of 1.67%, 1.72%, 3.65%, 1.0%, 4.61%, and 4.66% in comparison with the state-of-the-art method, demonstrating the superiority of our method.

Autism spectrum disorder (ASD) is a group of developmental diseases characterized by social dysfunction and repetitive stereotype behaviors. Besides genetic mutations, environmental factors play important roles in the development of ASD. Valproic acid (VPA) is widely used for modeling environmental factor induced ASD in rodents. However, traditional VPA modeling is low-in-efficiency and the phenotypes often vary among different batches of experiments. To optimize this ASD-modeling method, we tested “two-hit” hypothesis by single or double exposure of VPA and poly:IC at the critical time points of embryonic and postnatal stage. The autistic-like behaviors of mice treated with two-hit schemes (embryonic VPA plus postnatal poly:IC, embryonic poly:IC plus postnatal VPA, embryonic VPA plus poly: IC, or postnatal VPA plus poly:IC) were compared with mice treated with traditional VPA protocol. The results showed that all single-hit and two-hit schemes produced core ASD phenotypes as VPA single treatment did. Only one group, namely, mice double-hit by VPA and poly:IC simultaneously at E12.5 showed severe impairment of social preference, social interaction and ultrasonic communication, as well as significant increase of grooming activity and anxiety-like behaviors, in comparation with mice treated with the traditional VPA protocol. These data demonstrated that embryonic two-hit of VPA and poly:IC is more efficient in producing ASD phenotypes in mice than the single-hit of VPA, indicating this two-hit scheme could be utilized for modeling environmental factors induced ASD.

IntroductionThis study investigates the mechanisms linking students’ perceived teacher support with math anxiety, focusing on the mediating roles of the teacher–student relationship and mathematics self-efficacy.MethodsThe research was conducted with 401 fifth-grade students in China, utilizing scales for Students’ Perceived Teacher Support, Teacher–Student Relationship, Math Self-Efficacy, and Math Anxiety.ResultsFindings revealed that student-perceived math teacher support, teacher–student relationship, and math self-efficacy were all significantly negatively correlated with math anxiety. It was notably found that student-perceived math teacher support influenced math anxiety through the chain mediation of teacher–student relationship and math self-efficacy. Additionally, the effect of students’ perceived emotional support from math teachers on math anxiety, mediated by teacher–student relationship intimacy, was significant only among male students.DiscussionThese results underscore the importance of fostering positive teacher–student interactions and enhancing self-efficacy to reduce math anxiety among primary school students. The gender-specific findings regarding emotional support and relationship intimacy highlight the need for tailored strategies in addressing math anxiety.

Dermacentor nuttalli, a member of family Ixodidae and genus Dermacentor, is predominantly found in North Asia. It transmits various pathogens of human and animal diseases, such as Lymphocytic choriomeningitis mammarenavirus and Brucella ovis, leading to severe symptoms in patients and posing serious hazards to livestock husbandry. To profile pathogen abundances of wild D. nuttalli, metagenomic sequencing was performed of four field-collected tick samples, revealing that Rickettsia, Streptomyces, and Pseudomonas were the most abundant bacterial genera in D. nuttalli. Specifically, four nearly complete Rickettsia genomes were assembled, closely relative to Rickettsia conorii subsp. raoultii. Then, a comprehensive meta-analysis was performed to evaluate its potential threats based on detected pathogens and geographical distribution positions reported in literature, reference books, related websites, and field surveys. At least 48 pathogens were identified, including 20 species of bacteria, seven species of eukaryota, and 21 species of virus. Notably, Rickettsia conorii subsp. raoultii, Coxiella burnetii, and Brucella ovis displayed remarkably high positivity rates, which were known to cause infectious diseases in both humans and livestock. Currently, the primary distribution of D. nuttalli spans China, Mongolia, and Russia. However, an additional 14 countries in Asia and America that may also be affected by D. nuttalli were identified in our niche model, despite no previous reports of its presence in these areas. This study provides comprehensive data and analysis on the pathogens carried by D. nuttalli, along with documented and potential distribution, suggesting an emerging threat to public health and animal husbandry. Therefore, there is a need for heightened surveillance and thorough investigation of D. nuttalli.

The objective of this study was to investigate the protective effect of Crataegus pinnatifida polysaccharide (CPP) on non-alcoholic fatty liver disease (NAFLD) induced by a high-fat diet (HFD) in mice. The findings demonstrated that CPP improved free fatty acid (FFA)-induced lipid accumulation in HepG2 cells and effectively reduced liver steatosis and epididymal fat weight in NAFLD mice, as well as decreased serum levels of TG, TC, AST, ALT, and LDL-C. Furthermore, CPP exhibited inhibitory effects on the expression of fatty acid synthesis genes FASN and ACC while activating the expression of fatty acid oxidation genes CPT1A and PPARα. Additionally, CPP reversed disturbances in intestinal microbiota composition caused by HFD consumption. CPP decreased the firmicutes/Bacteroidetes ratio, increased Akkermansia abundance, and elevated levels of total short-chain fatty acid (SCFA) content specifically butyric acid and acetic acid. Our results concluded that CPP may intervene in the development of NAFLD by regulating of intes-tinal microbiota imbalance and SCFAs production. Our study highlights that CPP has a potential to modulate lipid-related pathways via alterations to gut microbiome composition thereby ex-erting inhibitory effects on obesity and NAFLD development.