The economic consequence of large-scale epidemic outbreak: The path and loss evaluation of COVID-19 in China based on input-output analysis.

The COVID-19 pandemic has significantly impacted China's economic and social development. Understanding the direct and indirect effects of the epidemic on the economy is vital for formulating scientifically grounded epidemic management policies. This study assesses the economic losses and influence paths of a large-scale epidemic in China. We proposed three COVID-19 scenarios - serious, normal, and mild - to evaluate the direct economic impact on China's GDP from a demand perspective. An input-output model was used to estimate the indirect impact. Our findings show that China's GDP could lose 94,206, 75,365, and 56,524 hundred million yuan under serious, normal, and mild scenarios, respectively, with corresponding GDP decline rates of 9.27%, 7.42%, and 5.56%. Under the normal scenario, indirect economic loss and total loss are projected at 75,364 and 489,386 hundred million yuan, respectively. Additionally, the pandemic led to a reduction in carbon emissions: direct emissions decreased by 1,218.69 million tons, indirect emissions by 9,594.32 million tons, and total emissions by 10,813.01 million tons across various industries. This study provides a comprehensive analysis of the economic and environmental impacts of the pandemic.

Preparation of AIEgen-based near-infrared afterglow luminescence nanoprobes for tumor imaging and image-guided tumor resection.

Fluorescence imaging represents a vital tool in modern biology, oncology and biomedical applications. Afterglow luminescence (AGL), which circumvents the light scattering and tissue autofluorescence interference associated with real-time excitation source, shows remarkably increased imaging sensitivity and depth. Here we present a protocol for the design and synthesis of AGL nanoprobes with an aggregation-induced emission (AIE) effect to simultaneously red shift and amplify the afterglow signal for tumor imaging and image-guided tumor resection. The nanoprobe (AGL AIE dot) is composed of an enol ether format of Schaap's agent and a near-infrared AIE fluorogen (AIEgen) (tetraphenylethylene-phenyl-dicyanomethylene-4H-chromene, TPE-Ph-DCM) to suppress the nonradiative dissipation pathway. Pre-irradiating AGL AIE dots with white light could generate singlet oxygen to convert Schaap's agent to its 1,2-dioxetane format, thus initializing the AGL process. With the aid of AIEgen, the AGL shows simultaneously red shifted emission maximum (from ~540 nm to ~625 nm) and enhanced intensity (by 3.2-fold), facilitating better signal-to-background ratio, imaging sensitivity and depth. Intriguingly, the activated AGL can last for over 10 days. Compared with conventional approaches, our method provides a new solution to concurrently red shift and amplify afterglow signals for better in vivo imaging outcomes. The preparation of AGL AIE dots takes ~2 days, the in vitro characterization takes ~10 days (less than 1 day if not involving afterglow kinetic profile study) and the tumor imaging and image-guided tumor resection takes ~7 days. These procedures can be easily reproduced and amended after standard laboratory training in chemical synthesis and animal handling.

The environmental consequences of national Audit governance: An analysis based on county-level data in China.

Recent years have witnessed growing public concern over air pollution in China, posing a challenge to the government's environmental management efforts. Empirical evidence indicates that the digital economy contributes to mitigating environmental pollution. Given that national audits are a crucial part of the national oversight system and considering the significant role of digital technology in audit governance, it is relevant to explore how the digital economy can support national audits in enhancing China's environmental quality. This study investigates the environmental impact of national audit governance, utilizing a dataset from 1540 counties in China spanning from 2005 to 2018. The findings reveal that effective national audits contribute to reducing haze pollution (HP) levels, with the digital economy playing a moderating role. The results also demonstrate heterogeneity; national audits are particularly effective in regions characterized by high urbanization rates, severe HP, and stringent environmental regulations. The mechanism analysis suggests that industrial transformation and enhanced government governance are the key mechanisms through which national audits reduce regional HP. Additionally, reforming the audit management system can amplify the effects of national audits on reducing HP.

Thresholds of Nitrogen and Phosphorus Input Substantially Alter Arbuscular Mycorrhizal Fungal Communities and Wheat Yield in Dryland Farmland.

Arbuscular mycorrhizal (AM) fungi are essential for preserving the multifunctionality of ecosystems. The nitrogen (N)/phosphorus (P) threshold that causes notable variations in the AM fungus community of the soil and plant productivity is still unclear. Herein, a long-term (18 years) field experiment with five N and five P fertilizer levels was conducted to investigate the change patterns of soil AM fungus, multifunctionality, and wheat yield. High-N and -P fertilizer inputs did not considerably increase the wheat yield. In the AM fungal network, a statistically significant positive correlation was observed between ecosystem multifunctionality and the biodiversity of two primary ecological clusters (N: Module #0 and P: Module #3). Furthermore, fertilizer input thresholds for N (92-160 kg ha-1) and P (78-100 kg ha-1) significantly altered the AM fungal community, soil characteristics, and plant productivity. Our study provided a basis for reduced N and P fertilizer application and sustainable agricultural development from the aspect of soil AM fungi.

Insights into mechanism of peroxymonosufate activation by Mo single-atom catalysts: Singlet oxygen evolution and role of Mo-N coordination.

Recently, the Fenton-like reaction using peroxymonosulfate (PMS) has been acknowledged as a potential method for breaking down organic pollutants. In this study, we successfully synthesized a highly efficient and stable single atom molybdenum (Mo) catalyst dispersed on nitrogen-doped carbon (Mo-NC-0.1). This catalyst was then utilized for the first time to activate PMS and degrade bisphenol A (BPA). The Mo-NC-0.1/PMS system demonstrated the ability to completely degrade BPA within just 20 min. Scavenging tests and density functional theory (DFT) calculations have demonstrated that the primary reactive oxygen species was singlet oxygen (1O2) produced by Mo-N4 sites. The self-cycling of Mo facilitated PMS activation and the transition from a free radical activation pathway to a non-radical pathway mediated by 1O2. Simultaneously, the nearby pyridinic N served as adsorption sites to immobilize BPA and PMS molecules. The exceptionally high catalytic activity of Mo-NC-0.1 derived from its unique Mo-N coordination, which markedly reduced the distance for 1O2 to migrate to the BPA molecules. The Mo-NC-0.1/PMS system effectively reduced the acute toxicity of BPA and exhibited excellent cycling stability with minimal leaching. This study presented a new catalyst with high selectivity for 1O2 generation and provided valuable insights for the application of single atom catalysts in PMS-based AOPs.

Risks and Clinical Predictors of Hepatocellular Carcinoma in Chinese Populations: A Real-World Study of 10,359 Patients in Six Medical Centers.

Purpose: Early detection of hepatocellular carcinoma (HCC) through surveillance could reduce this cancer-associated mortality. We aimed to develop and validate algorithms using panel serum biomarkers to identify HCC in a real-world multi-center study in China. Patients and Methods: A total of 10,359 eligible subjects, including HCCs and benign liver diseases (BLDs), were recruited from six Chinese medical centers. The three nomograms were built using logistic regression and their sensitivities and specificities were carefully assessed in training and validation cohorts. HCC patients after surgical resection were followed to determine the prognostic values of these algorithms. Prospective surveillance performance was assessed in a cohort of chronic hepatitis B patients during 144 weeks follow-up. Results: Independent risk factors such as alpha-fetoprotein (AFP), lens cuinaris agglutinin-reactive fraction of AFP (AFP-L3), des-gamma-carboxy prothrombin (DCP), albumin (ALB), and total bilirubin (TBIL) obtained from train cohort were used to construct three nomograms (LAD, C-GALAD, and TAGALAD) using logistic regression. In the training and two validation cohorts, their AUCs were all over 0.900, and the higher AUCs appeared in TAGALAD and C-GALAD. Furthermore, the three nomograms could effectively stratify HCC into two groups with different survival and recurrence outcomes in follow-up validation. Notably, TAGALAD could predict HCC up to 48 weeks (AUC: 0.984) and 24 weeks (AUC: 0.900) before clinical diagnosis. Conclusion: The proposed nomograms generated from real-world Chinese populations are effective and easy-to use for HCC surveillance, diagnosis, as well as prognostic evaluation in various clinical scenarios based on data feasibility.

Large mercury release from the Greenland Ice Sheet invalidated.

The major input of mercury (Hg) to the Arctic is normally ascribed to long-range transport of anthropogenic Hg emissions. Recently, alarming concentrations of Hg in meltwater from the Greenland Ice Sheet (GrIS) were reported with bedrock as the proposed source. Reported Hg concentrations were 100 to 1000 times higher than in known freshwater systems of Greenland, calling for independent validation of the extraordinary concentrations and conclusions. Here, we present measurements of Hg at 21 glacial outlets in West Greenland showing that extreme Hg concentrations cannot be reproduced. In contrast, we find that meltwater from below the GrIS is very low in Hg, has minor implications for the global Hg budget, and pose only a very limited risk for local communities and the natural environment of Greenland.

Clinical evaluation of deep learning systems for assisting in the diagnosis of the epiretinal membrane grade in general ophthalmologists.

BACKGROUND: Epiretinal membrane (ERM) is a common age-related retinal disease detected by optical coherence tomography (OCT), with a prevalence of 34.1% among people over 60 years old. This study aims to develop artificial intelligence (AI) systems to assist in the diagnosis of ERM grade using OCT images and to clinically evaluate the potential benefits and risks of our AI systems with a comparative experiment. METHODS: A segmentation deep learning (DL) model that segments retinal features associated with ERM severity and a classification DL model that grades the severity of ERM were developed based on an OCT dataset obtained from three hospitals. A comparative experiment was conducted to compare the performance of four general ophthalmologists with and without assistance from the AI in diagnosing ERM severity. RESULTS: The segmentation network had a pixel accuracy (PA) of 0.980 and a mean intersection over union (MIoU) of 0.873, while the six-classification network had a total accuracy of 81.3%. The diagnostic accuracy scores of the four ophthalmologists increased with AI assistance from 81.7%, 80.7%, 78.0%, and 80.7% to 87.7%, 86.7%, 89.0%, and 91.3%, respectively, while the corresponding time expenditures were reduced. The specific results of the study as well as the misinterpretations of the AI systems were analysed. CONCLUSION: Through our comparative experiment, the AI systems proved to be valuable references for medical diagnosis and demonstrated the potential to accelerate clinical workflows. Systematic efforts are needed to ensure the safe and rapid integration of AI systems into ophthalmic practice.

Green through finance: The impact of monetary policy uncertainty on inclusive green growth.

For high-quality development, inclusive green growth (IGG) is a crucial strategic option. Given the deceleration in economic growth, monetary policy has several obligations, including stabilizing growth, changing structure, and mitigating risks. However, frequent revisions of monetary policy may diminish its regulatory efficacy due to resulting uncertainty. Accordingly, this study reveals the mechanism of the impact of monetary policy uncertainty (MPU) on IGG. Research suggests that MPU significantly inhibits IGG in the region, as demonstrated by robustness tests. Mechanism test reveal that MPU inhibits IGG by reducing green finance, ecological innovation, media attention, and employment levels. These four transmission mechanisms all show a masking effect. Additionally, further tests show that under different levels of green finance, ecological innovation, media attention, and employment, the impact of MPU on IGG is nonlinear. Heterogeneity analyses also indicate that the inhibition of MPU is weaker in cities with high scientific and technological progress and local fiscal expenditure. Finally, quantile regression demonstrates that the restraining effect of MPU diminishes before rising. This study contributes to the advancement of MPU research, provides a solid foundation for formulating, modifying, and executing monetary policy, and serves as a valuable resource for promoting IGG.

The Sapria himalayana genome provides new insights into the lifestyle of endoparasitic plants.

BACKGROUND: Sapria himalayana (Rafflesiaceae) is an endoparasitic plant characterized by a greatly reduced vegetative body and giant flowers; however, the mechanisms underlying its special lifestyle and greatly altered plant form remain unknown. To illustrate the evolution and adaptation of S. himalayasna, we report its de novo assembled genome and key insights into the molecular basis of its floral development, flowering time, fatty acid biosynthesis, and defense responses. RESULTS: The genome of S. himalayana is ~ 1.92 Gb with 13,670 protein-coding genes, indicating remarkable gene loss (~ 54%), especially genes involved in photosynthesis, plant body, nutrients, and defense response. Genes specifying floral organ identity and controlling organ size were identified in S. himalayana and Rafflesia cantleyi, and showed analogous spatiotemporal expression patterns in both plant species. Although the plastid genome had been lost, plastids likely biosynthesize essential fatty acids and amino acids (aromatic amino acids and lysine). A set of credible and functional horizontal gene transfer (HGT) events (involving genes and mRNAs) were identified in the nuclear and mitochondrial genomes of S. himalayana, most of which were under purifying selection. Convergent HGTs in Cuscuta, Orobanchaceae, and S. himalayana were mainly expressed at the parasite-host interface. Together, these results suggest that HGTs act as a bridge between the parasite and host, assisting the parasite in acquiring nutrients from the host. CONCLUSIONS: Our results provide new insights into the flower development process and endoparasitic lifestyle of Rafflesiaceae plants. The amount of gene loss in S. himalayana is consistent with the degree of reduction in its body plan. HGT events are common among endoparasites and play an important role in their lifestyle adaptation.

MSHF: A Multi-Source Heterogeneous Fundus (MSHF) Dataset for Image Quality Assessment.

Image quality assessment (IQA) is significant for current techniques of image-based computer-aided diagnosis, and fundus imaging is the chief modality for screening and diagnosing ophthalmic diseases. However, most of the existing IQA datasets are single-center datasets, disregarding the type of imaging device, eye condition, and imaging environment. In this paper, we collected a multi-source heterogeneous fundus (MSHF) database. The MSHF dataset consisted of 1302 high-resolution normal and pathologic images from color fundus photography (CFP), images of healthy volunteers taken with a portable camera, and ultrawide-field (UWF) images of diabetic retinopathy patients. Dataset diversity was visualized with a spatial scatter plot. Image quality was determined by three ophthalmologists according to its illumination, clarity, contrast and overall quality. To the best of our knowledge, this is one of the largest fundus IQA datasets and we believe this work will be beneficial to the construction of a standardized medical image database.

Mathematical model of potential distribution in a pinned photodiode of an indirect time of flight CMOS image sensor.

This paper focuses on the rapid charge transfer of lock-in pixels in time of flight 3D image sensors. Through the principal analysis, a mathematical model of potential distribution in a pinned photodiode (PPD) in different comb shapes is established. Based on this model, the influence of different comb shapes on the accelerating electric field in PPD is analyzed. The semiconductor device simulation tool SPECTRA is applied to verify the effectiveness of the model, and the simulation results are analyzed and discussed. When the width of comb tooth is in narrow and medium range, the potential changes more obviously with the increase of comb tooth angle α, whereas the potential becomes stable even if the comb tooth angle α increases sharply with the wide comb tooth width. The proposed mathematical model contributes to instructing the design of pixel transferring electrons rapidly and resolving image lag.

Investigation of nirmatrelvir epimerization occurred in analytical sample solution by using high resolution LC-MSn, NMR, and hydrogen/deuterium exchange study.

During the related substances testing of nirmatrelvir, an unknown peak was observed and the level of the peak increased over time during the storage of the sample solution. By using a strategy including LC-PDA/UV-MSn analysis, the degradant was rapidly identified as an epimer of nirmatrelvir, a solution degradation product that is caused by the trace amount of alkaline impurities leaching from the glass HPLC vials. In addition, by using hydrogen/deuterium exchange NMR spectroscopy analysis, the epimerization position was determined to be the carbon α to the adjacent cyano group. Further investigation indicated that the occurrence of the solution degradation can be suppressed when the glass HPLC vials were replaced by plastic HPLC or mass spectrometric grade vials.

Mask configurable readout circuit architecture for an ultra-high-resolution CMOS image sensor: publisher's note.

This publisher's note reports a correction in Appl. Opt.61, 2565 (2022)APOPAI0003-693510.1364/AO.453904.

Molecular Mechanism of the Role of Apigenin in the Treatment of Hyperlipidemia: A Network Pharmacology Approach.

The therapeutic effect of apigenin (APG) on hyperlipidemia was investigated using network pharmacology combined with molecular docking strategy, and the potential targets of APG in the treatment of hyperlipidemia were explored. Genetic Ontology Biological Process (GOBP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis of common targets were performed. Then, molecular docking was used to predict the binding mode of APG to the target. Finally, Sprague Dawley rats were used to establish a hyperlipidemia model. The expression levels of insulin (INS) and vascular endothelial growth factor A (VEGFA) mRNA in each group were detected by quantitative reverse transcription-polymerase chain reaction. Network pharmacological studies revealed that the role of APG in the treatment of hyperlipidemia was through the regulation of INS, VEGFA, tumor necrosis factor, epidermal growth factor receptor, matrix metalloprotein 9, and other targets, as well as through the regulation of the hypoxia-inducible factor 1 (HIF-1) signaling pathway, fluid shear stress, and atherosclerosis signaling pathways, vascular permeability; APG also participated in the regulation of glucose metabolism and lipid metabolism, and acted on vascular endothelial cells, and regulated vascular tone. Molecular docking showed that APG binds to the target with good efficiency. Experiments showed that after APG treatment, the expression levels of INS and VEGFA mRNA in the model group were significantly decreased (p<0.01). In conclusion, APG has multiple targets and affects pathways involved in the treatment of hyperlipidemia by regulating the HIF-1 signaling pathway, fluid shear stress, and the atherosclerosis pathway.

Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning.

BACKGROUND/AIMS: Fundus fluorescein angiography (FFA) is an important technique to evaluate diabetic retinopathy (DR) and other retinal diseases. The interpretation of FFA images is complex and time-consuming, and the ability of diagnosis is uneven among different ophthalmologists. The aim of the study is to develop a clinically usable multilevel classification deep learning model for FFA images, including prediagnosis assessment and lesion classification. METHODS: A total of 15 599 FFA images of 1558 eyes from 845 patients diagnosed with DR were collected and annotated. Three convolutional neural network (CNN) models were trained to generate the label of image quality, location, laterality of eye, phase and five lesions. Performance of the models was evaluated by accuracy, F-1 score, the area under the curve and human-machine comparison. The images with false positive and false negative results were analysed in detail. RESULTS: Compared with LeNet-5 and VGG16, ResNet18 got the best result, achieving an accuracy of 80.79%-93.34% for prediagnosis assessment and an accuracy of 63.67%-88.88% for lesion detection. The human-machine comparison showed that the CNN had similar accuracy with junior ophthalmologists. The false positive and false negative analysis indicated a direction of improvement. CONCLUSION: This is the first study to do automated standardised labelling on FFA images. Our model is able to be applied in clinical practice, and will make great contributions to the development of intelligent diagnosis of FFA images.

Genome-wide identification and expression analysis of the glutamate receptor gene family in sweet potato and its two diploid relatives.

Plant glutamate receptor (GLR) homologs are crucial calcium channels that play an important role in plant development, signal transduction, and response to biotic and abiotic stresses. However, the GLR gene family has not yet been thoroughly and systematically studied in sweet potato. In this study, a total of 37 GLR genes were identified in the cultivated hexaploid sweet potato (Ipomoea batatas), and 32 GLR genes were discovered in each of the two diploid relatives (Ipomoea trifida and Ipomoea triloba) for the first time. Based on their evolutionary relationships to those of Arabidopsis, these GLRs were split into five subgroups. We then conducted comprehensive analysis to explore their physiological properties, protein interaction networks, promoter cis-elements, chromosomal placement, gene structure, and expression patterns. The results indicate that the homologous GLRs of the cultivated hexaploid sweet potato and its two relatives are different. These variations are reflected in their functions related to plant growth, hormonal crosstalk, development of tuberous roots, resistance to root rot, and responses to abiotic stress factors, all of which are governed by specific individual GLR genes. This study offers a comprehensive analysis of GLR genes in sweet potato and its two diploid relatives. It also provides a theoretical basis for future research into their regulatory mechanisms, significantly influencing the field of molecular breeding in sweet potatoes.

Clinical application of transcranial magnetic stimulation in multiple sclerosis.

Multiple sclerosis (MS) is a common chronic, autoimmune-mediated inflammatory and neurodegenerative disease of the central nervous system. The treatment of MS has enormous progress with disease-modifying drugs, but the complexity of the disease course and the clinical symptoms of MS requires personalized treatment and disease management, including non-pharmacological treatment. Transcranial magnetic stimulation (TMS) is a painless and non-invasive brain stimulation technique, which has been widely used in neurological diseases. In this review, we mainly focus on the progress of physiological assessment and treatment of TMS in MS.

A supramolecular self-assembled nanomaterial for synergistic therapy of immunosuppressive tumor.

Triple negative breast cancer (TNBC) is an immunosuppressive "cold" tumor that lacks immune cell infiltration and activation, resulting in a poor response to immune checkpoint blockade (ICB) therapies. In addition, TNBC is poorly responsive to targeted therapies due to the absence of efficient molecular targets. A strategy that can block molecular signal transduction, stimulate immunogenicity, and activate the immune response is a promising approach to achieve ideal clinical benefit. Herein, we designed and synthesized an aggregation-induced emission luminogen (AIEgen)-conjugated self-assembling peptide that targets epidermal growth factor receptor (EGFR), named TPA-FFG-LA. TPA-FFG-LA peptides form nanoassemblies on the surface of EGFR-positive TNBC cells and are internalized into cells through endocytosis, which inhibit EGFR signaling transduction and provoke lysosomal membrane permeabilization (LMP). Upon light irradiation, the aggregated AIEgens produce massive reactive oxygen species (ROS) to exacerbate LMP and trigger immunogenic cell death (ICD), resulting in elimination of residual EGFR-negative tumor cells and exerting long-term antitumor effects. The in vitro and in vivo experiments verified that TPA-FFG-LA nanoassemblies suppress tumor growth, provoke immune cell activation and infiltration, and cause EGFR degradation and LMP. These results suggest that the combination of supramolecular assembly induced molecular targeting effects and lysosome dysfunction with ICD-stimulated immune activation is a plausible strategy for the efficient therapy of immunosuppressive TNBC.

An Activatable Near-Infrared Afterglow Theranostic Prodrug with Self-Sustainable Magnification Effect of Immunogenic Cell Death.

Herein, we report an activatable near-infrared (NIR) afterglow theranostic prodrug that circumvents high background noise interference caused by external light excitation. The prodrug can release hydroxycamptothecin (HCPT) in response to the high intratumoral peroxynitrite level associated with immunogenic cell death (ICD), and synchronously activate afterglow signal to monitor the drug release process and cold-to-hot tumor transformation. The prodrug itself is an ICD inducer achieved by photodynamic therapy (PDT). PDT initiates ICD and recruits first-arrived neutrophils to secrete peroxynitrite to trigger HCPT release. Intriguingly, we demonstrate that HCPT can significantly amplify PDT-mediated ICD process. The prodrug thus shows a self-sustainable ICD magnification effect by establishing an "ICD-HCPT release-amplified ICD" cycling loop. In vivo studies demonstrate that the prodrug can eradicate existing tumors and prevent further tumor recurrence through antitumor immune response.