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Abstract Objective To evaluate the accuracy of Type B2 based on narrow-band imaging-magnifying endoscopy (NBI-ME) in judging invasion depth of superficial esophageal squamous cell carcinoma (SESCC) and analyze potential influencing factors. Method Data from 113 patients where Type B2 was observed by magnifying endoscopy and confirmed by postoperative pathology as SESCC at the First Affiliated Hospital of Fujian Medical University and Fujian Provincial Hospital from January 2015 to April 2024 were retrospectively analyzed. Patients were divided into correct prediction and incorrect prediction groups according to the postoperative pathological results, and the prediction accuracy was calculated. The incorrect prediction group was further divided into overestimation and underestimation groups to identify the influential factors for overprediction and underprediction, respectively. The independent influential factors for the prediction were assessed using multivariate Cox logistic regression analysis. Results B2-narrow (Type B2 area ≤ 5 mm) (p

Abstract Background The dirigent (DIR) genes encode proteins that act as crucial regulators of plant lignin biosynthesis. In Solanaceae species, members of the DIR gene family are intricately related to plant growth and development, playing a key role in responding to various biotic and abiotic stresses. It will be of great application significance to analyze the DIR gene family and expression profile under various pathogen stresses in Solanaceae species. Results A total of 57 tobacco NtDIRs and 33 potato StDIRs were identified based on their respective genome sequences. Phylogenetic analysis of DIR genes in tobacco, potato, eggplant and Arabidopsis thaliana revealed three distinct subgroups (DIR-a, DIR-b/d and DIR-e). Gene structure and conserved motif analysis showed that a high degree of conservation in both exon/intron organization and protein motifs among tobacco and potato DIR genes, especially within members of the same subfamily. Total 8 pairs of tandem duplication genes (3 pairs in tobacco, 5 pairs in potato) and 13 pairs of segmental duplication genes (6 pairs in tobacco, 7 pairs in potato) were identified based on the analysis of gene duplication events. Cis-regulatory elements of the DIR promoters participated in hormone response, stress responses, circadian control, endosperm expression, and meristem expression. Transcriptomic data analysis under biotic stress revealed diverse response patterns among DIR gene family members to pathogens, indicating their functional divergence. After 96 h post-inoculation with Ralstonia solanacearum L. (Ras), tobacco seedlings exhibited typical symptoms of tobacco bacterial wilt. The qRT-PCR analysis of 11 selected NtDIR genes displayed differential expression pattern in response to the bacterial pathogen Ras infection. Using line 392278 of potato as material, typical symptoms of potato late blight manifested on the seedling leaves under Phytophthora infestans infection. The qRT-PCR analysis of 5 selected StDIR genes showed up-regulation in response to pathogen infection. Notably, three clustered genes (NtDIR2, NtDIR4, StDIR3) exhibited a robust response to pathogen infection, highlighting their essential roles in disease resistance. Conclusion The genome-wide identification, evolutionary analysis, and expression profiling of DIR genes in response to various pathogen infection in tobacco and potato have provided valuable insights into the roles of these genes under various stress conditions. Our results could provide a basis for further functional analysis of the DIR gene family under pathogen infection conditions.

Background and aimTo date, the association between glucocorticoid use and the risk of pancreatitis remains controversial. The aim of this study was the investigation of this possible relationship.MethodsWe carried out a two-sample Mendelian randomization (MR) analysis using GWAS data from European ancestry, East Asian descendants and the FinnGen Biobank Consortium to evaluate this potential causal relationship. Genetic variants associated with glucocorticoid use were selected based on genome-wide significance (p < 5×10-8).ResultsOur MR analysis of European ancestry data revealed no significant causal relationship between glucocorticoid use and AP (IVW: OR=1.084, 95% CI= 0.945-1.242, P=0.249; MR-Egger: OR=1.049, 95% CI= 0.686-1.603, P=0.828; weighted median: OR=1.026, 95% CI= 0.863-1.219, P=0.775) or CP (IVW: OR=1.027, 95% CI= 0.850-1.240, P=0.785; MR-Egger: OR= 1.625, 95% CI= 0.913-2.890, P= 0.111; weighted median: OR= 1.176, 95% CI= 0.909-1.523, P= 0.218). Sensitivity analyses, including MR-Egger and MR-PRESSO, indicated no evidence of pleiotropy or heterogeneity, confirming the robustness of our findings. Multivariable MR analysis adjusted for alcohol consumption, BMI, cholelithiasis and C-reactive protein levels supported these findings. Replicated analysis was performed on datasets from the FinnGen Biobank Consortium and East Asian descendants, and similar results were obtained.ConclusionsThis MR analysis suggests that there is no causal association between glucocorticoid use and the risk of pancreatitis.

The E3 enzyme in the UPS pathway is a crucial factor for inhibiting substrate specificity. In Solanaceae, the U-box E3 ubiquitin ligase has a complex relationship with plant growth and development, and plays a pivotal role in responding to various biotic and abiotic stresses. The analysis of the U-box gene family in Solanaceae and its expression profile under different stresses holds significant implications. A total of 116 tobacco NtU-boxs and 56 eggplant SmU-boxs were identified based on their respective genome sequences. Phylogenetic analysis of U-box genes in tobacco, eggplant, tomato, Arabidopsis, pepper, and potato revealed five distinct subgroups (I-V). Gene structure and protein motifs analysis found a high degree of conservation in both exon/intron organization and protein motifs among tobacco and eggplant U-box genes especially the members within the same subfamily. A total of 15 pairs of segmental duplication and 1 gene pair of tandem duplication were identified in tobacco based on the analysis of gene duplication events, while 10 pairs of segmental duplication in eggplant. It is speculated that segmental duplication events are the primary driver for the expansion of the U-box gene family in both tobacco and eggplant. The promoters of NtU-box and SmU-box genes contained cis-regulatory elements associated with cellular development, phytohormones, environment stress, and photoresponsive elements. Transcriptomic data analysis shows that the expression levels of the tobacco and eggplant U-box genes in different tissues and various abiotic stress conditions. Using cultivar Hongda of tobacco and cultivar Yanzhi of eggplant as materials, qRT-PCR analysis has revealed that 15 selected NtU-box genes and 8 SmU-box may play important roles in response to pathogen Ras invasion both in tobacco and eggplant.

Abstract Background Alcohol dehydrogenases (ADHs) are the crucial enzymes that can convert ethanol into acetaldehyde. In tobacco, members of ADH gene family are involved in various stresses tolerance reactions, lipid metabolism and pathways related to plant development. It will be of great application significance to analyze the ADH gene family and expression profile under various stresses in tobacco. Results A total of 53 ADH genes were identified in tobacco (Nicotiana tabacum L.) genome and were grouped into 6 subfamilies based on phylogenetic analysis. Gene structure (exon/intron) and protein motifs were highly conserved among the NtADH genes, especially the members within the same subfamily. A total of 5 gene pairs of tandem duplication, and 3 gene pairs of segmental duplication were identified based on the analysis of gene duplication events. Cis-regulatory elements of the NtADH promoters participated in cell development, plant hormones, environmental stress, and light responsiveness. The analysis of expression profile showed that NtADH genes were widely expressed in topping stress and leaf senescence. However, the expression patterns of different members appeared to be diverse. The qRT-PCR analysis of 13 NtADH genes displayed their differential expression pattern in response to the bacterial pathogen Ralstonia solanacearum L. infection. Metabolomics analysis revealed that NtADH genes were primarily associated with carbohydrate metabolism, and moreover, four NtADH genes (NtADH20/24/48/51) were notably involved in the pathway of alpha-linolenic acid metabolism which related to the up-regulation of 9-hydroxy-12-oxo-10(E), 15(Z)-octadecadienoic acid and 9-hydroxy-12-oxo-15(Z)-octadecenoic acid. Conclusion The genome-wide identification, evolutionary analysis, expression profiling, and exploration of related metabolites and metabolic pathways associated with NtADH genes have yielded valuable insights into the roles of these genes in response to various stresses. Our results could provide a basis for functional analysis of NtADH gene family under stressful conditions.

In order to improve stability and antibacterial property, a novel super-hydrophilic partially reduced graphene oxide membrane was prepared by interfacial polymerization of piperazine and partially reduced graphene oxide as aqueous solution and trimesoyl chloride as organic solution. Fourier transform infrared spectroscopy, scanning electron microscope, and contact angle measurement were conducted to probe the morphology and properties of the membranes. The modified membrane possessed super-hydrophilicity, improved durability and swelling resistance. The optimized membrane had a molecular weight cut off of about 674 Da and possessed a pure water permeability of 49.86 L·m−2·h−1·MPa−1. The retention order of salts was Na2SO4 > MgSO4 > MgCl2 > Na2CO3 > CaCl2 > NaCl, while the rejection for four kinds of pharmaceuticals followed the order of ibuprofen (92%) > carbamazepine (87%) > amlodipine (80%) > atenolol (76%), indicating that the negatively charged membrane could improve the retention performance by the electrostatic repulsive effect. Moreover, the enhanced antibacterial performance of membrane attributed to the dual effects of the super-hydrophilicity and the tea polyphenols antibacterial material loading, which may alter the charge distribution on and within the membrane, leading to loss of cell viability. HIGHLIGHTS Polyamide NF membrane prepared with partially reduced graphene oxide.; Dopamine was used to reduce graphene oxide and stabilize the partially reduced graphene oxide.; The membrane had highly hydrophilic and stability.; Improved removal efficiency to both divalent ions and negatively charged pharmaceuticals.; Enhanced the antibacterial performance by the addition of tea polyphenols.;

In order to improve the stability of nanofiltration membrane in separation and purification, a novel polyelectrolyte multilayer nanofiltration membrane was facilely prepared by co-deposition of polydopamine (PDA) and polyethyleneimine (PEI) on the polyethersulfone (PES) ultrafiltration membrane substrate, followed by immersing graphene oxide (GO) solution, and crosslinking PDA. The modified surfaces were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM), water contact angle, their saline flux and ability to reject salt and dye were determined. The results also exhibited salt rejection ability as Na2SO4 > K2SO4 > MgSO4 > NaCl > KCl > MgCl2, suggesting the higher rejection of divalent anion. Also, the retention order of the dye by the GO modified membrane is DY86 > DB19 > AG27 > DY142 > DB56 > AR151 > VB5, indicating that the GO modified membrane has better rejection of negatively charged dyes as well as higher molecular weight dyes. Ethanol and hypochlorite resistance tests under different pH conditions showed the membranes coated GO enhanced stability in regard to salt rejection properties. Significantly, the anti-biological test confirmed the growth rate of microalgae on the GO introduced membrane was decreased greatly due to enhanced stability and lower roughness. HIGHLIGHTS This work has successfully prepared the (PDA@PEI/GO/PDA)/PES membrane by dip coating and chemical crosslinking.; The membrane has a good effect on the removal of divalent ions and better rejection of negatively charged dyes as well as higher molecular weight dyes.; The obtained membrane has high stability and excellent anti-biological pollution performance.;

Aspergillus flavus is an opportunistic pathogenic fungus for both plant and animal that produces carcinogenic toxins termed aflatoxins (AFs). To identify possible genetic targets to reduce AF contamination, in this study, we have characterized a novel A. flavus Set3, and it shares sequence homology with the yeast protein Set3. The set3 deletion mutants present no difference in growth rate but alterations in asexual development and secondary metabolite production when compared to the A. flavus wild type. Specifically, deletion of set3 gene decreases conidiophore formation and conidial production through downregulating expression of brlA and abaA genes. In addition, normal levels of set3 are required for sclerotial development and expression of sclerotia-related genes nsdC and sclR. Further analyses demonstrated that Set3 negatively regulates AF production as well as the concomitant expression of genes in the AF gene cluster. Importantly, our results also display that A. flavus Set3 is involved in crop kernel colonization. Taking together, these results reveal that a novel Set3 plays crucial roles in morphological development, secondary metabolism, and fungal virulence in A. flavus.

The Community Land Model version 4 with carbon and nitrogen components is coupled with data assimilation research testbed to assimilate remotely sensed leaf area index (LAI), to analyze the improvement in model performance for simulating land surface variables and land–atmospheric exchange fluxes. The results demonstrate that assimilation effectively addresses the issue of significant overestimation of LAI values, particularly noticeable in regions characterized by low latitudes and dense vegetation coverage. At a global scale, the disparities between simulated and assimilated LAI relative to observational data, are measured at 0.90 and −0.07, representing 54.1% and 3.9% of the observed values, respectively. The root mean square difference (RMSD) for assimilated LAI is 1.61 comparing with the simulated LAI of 1.85. Assimilating LAI globally leads to a noteworthy 1% reduction in the mean relative difference of the global average 2-m air temperature (T2m) and a concurrent decrease of 0.15 °C in RMSD. However, at the global level, the assimilation of LAI does not yield a significant enhancement in the modeling capability of heat fluxes, although modeling capability of sensible heat (HS) slightly outperforms latent heat. Improvements in land surface variables after assimilation show significant variations at regional scales due to factors such as vegetation coverage and climatic conditions. Overall, in regions characterized by periodic changes in vegetation, such as forested areas in Western Eurasian Continent (region 5), the enhancements in T2m and HS after assimilating LAI are particularly notable, with mean relative difference reduced by 7% and 20%, respectively.

In recent years, the issue of air pollution has garnered significant public attention globally, with a particular emphasis on the challenge of atmospheric fine particulate matter (PM2.5) pollution. The efficient and precise simulation of changes in pollutant concentrations, as well as their spatial and temporal distribution, is essential for effectively addressing the air pollution issue. In this paper, the WRF-Chem model is used to simulate the meteorological elements including temperature (T), relative humidity (RH), wind speed (WS), and pressure (P), and the concentrations of PM2.5 and PM10 atmospheric pollutants in December 2020 in Xuzhou City. Simultaneously, the ADMS-Urban model was employed to conduct a higher spatial resolution study of PM2.5 concentrations during the heavy pollution days of 11–12 December 2020 in Xuzhou City. The study shows that the WRF-Chem model can simulate the meteorological conditions of the study time period better, and the correlation coefficients (R) of pressure, temperature, wind speed, and relative humidity are 0.99, 0.87, 0.75, and 0.70, respectively. The WRF-Chem model can accurately simulate the PM2.5 concentration on clean days (R of 0.66), but the simulation of polluted days is not satisfactory. Therefore, the ADMS-Urban model was chosen to simulate the PM2.5 concentration on polluted days in the center of Xuzhou City. The ADMS-Urban model can simulate the distribution characteristics and concentration changes of PM2.5 around roads and buildings in the center of Xuzhou City. Comparing the simulation results of the two models, it was found that the two models have their own advantages in PM2.5 concentration simulation, and how to better couple the two models is the next research direction.

Lakes play a crucial role in the global water cycle and significantly contribute to enhancing regional ecological environments and simulating economic growth. In this study, based on the data from the Landsat TM 4-5, Landsat 7 ETM SLC-off, and Landsat 8-9 OLI/TIRS C2 L2 satellites, the surface area of Qinghai Lake is obtained by using the Normalized Difference Water Index (NDWI) method. Additionally, leveraging the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation land surface reanalysis dataset (ERA5-Land), we analyzed the interplay between lake area and related climate factors by using the Noise Assisted–Multivariate Empirical Mode Decomposition (NA-MEMD) and wavelet coherence analysis method. The surface area of Qinghai Lake showed an overall expansion trend from 1986 to 2022, with an expansion rate of 2.89 km2/a. Precipitation, temperature, and evapotranspiration (ET) also showed an increasing trend, with the largest increasing trend in autumn, summer, and summer, respectively. The area of Qinghai Lake did not demonstrate distinct periodic patterns from 1986 to 2022, in contrast to the marked 8–16 month oscillations observed in precipitation, temperature, and ET. In the phase of lake area expansion between 2008 and 2016, changes in the lake’s surface area were observed to trail behind variations in precipitation and temperature by approximately three months. Furthermore, the shift in ET was found to lag behind alterations in the lake area, displaying a delay of 3–6 months.

Near-surface NO2 (NS-NO2) is closely related to human health and the atmospheric environment. While top-down approaches have been widely applied to estimate NS-NO2 using satellite-based NO2 column measurements, there still exist significant defects, resulting in a low overall fit and significant amount of bias. This article combines GOME-2B and OMI satellite data to estimate daily NS-NO2 with a spatial resolution of 0.1° × 0.1° from 2014 to 2018 over Mainland China, using a machine learning method. The estimated result has four important characteristics. First, the sample-based cross validation with surface observations shows a good result with R2 = 0.80 and RMSE = 9.0 μg/m3. Second, the underestimation in high concentration areas and overestimation in low concentration areas are both reduced, compared with the case of using OMI data alone. Third, the estimated NS-NO2 is consistent with surface observations in spatial distribution, and successfully represent both inter-annual changes and seasonal characteristics. Furthermore, the population-weighted NO2-based estimated dataset shows a significant decline of pollution exposure levels from 2014 to 2018.

This paper reports a comparative experiment using remote sensing underlying surface data (ESACCI) and Community Land Model underlying surface data (CLM_LS) to analyze the uncertainty of land surface types in land–atmosphere interaction. The results showed that the global distribution of ESACCI cropland is larger than that of CLM_LS, and there is a great degree of difference in some regions, which can reach more than 50% regionally. Furthermore, the changes of the underlying surface conditions can be transmitted to the model results through the data itself, resulting in the uncertainty of the surface energy balance, surface micro-meteorological elements, and surface water balance simulated by the model, which further affects the climate simulation effect.