Decreased plasma docosahexaenoic acid concentration in chronic obstructive pulmonary disease patients with pulmonary Hypertension: Findings from human lipidomics and transcriptomics analysis.

Oxylipins derived from polyunsaturated fatty acids (PUFAs) are important endogenous signaling molecules, but are little characterized in pulmonary hypertension (PH) due to chronic obstructive pulmonary disease (COPD). In this study, we identified novel plasma oxylipins associated with PH risk in COPD patients. The plasma oxylipin profiles of COPD patients without PH (COPD-noPH) or with PH (COPD-PH) were obtained from discovery and validation cohort, using the process of LC-MS/MS analysis. There was a significant decrease in the plasma levels of both free docosahexaenoic acid (DHA) and DHA-derived oxylipins in the COPD-PH group. The multivariable logistic regression model identified DHA and four DHA-derived oxylipins (13-HDHA, 10-HDHA, 8-HDHA and 16-HDHA) exhibited significant differences between the two groups after adjusting for sex, BMI, FEV1% predicted, and smoking status. The diagnostic value of these metabolites was further evaluated through ROC curve analysis. The transcriptome profiles in peripheral blood mononuclear cells (PBMCs) of COPD-PH patients and COPD-PH patients were detected through high-throughput sequencing. The enrichment analysis revealed that the upregulated differentially expressed genes (DEGs) were highly enriched in the interferon signaling pathway. In addition, DHA supplementation proved that DHA may inhibit the development of pH by reducing the secretion of interferons derived from PBMCs. This conjecture was further confirmed by the higher level of serum interferon-γ and interferon-α2 of COPD-PH patients than that of COPD-noPH patients. The present study highlights that decreased DHA and DHA-derived oxylipins levels are suggestive of a higher risk of pH development in COPD cases.

Five-Year Outcomes of Bioresorbable Stent Therapy for Coronary Heart Disease: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: The efficacy of bioresorbable vascular scaffolds (BVS) compared to metallic stents for the treatment of coronary heart disease remains controversial. The analysis of clinical outcomes at five years following the initial treatment has yet to be reviewed. This study sought to assess the five-year outcomes in randomized controlled trials of BVS in the treatment of coronary heart disease using a systematic review and meta-analysis. Methods: A systematic database search was conducted from their inception to June 30th, 2023 using various Medical Subject Headings (MeSH) terms including: "Coronary Disease", "Bioresorbable stent", "Randomized controlled trials". Results: After a rigorous selection process, a total of five high-quality articles were finally included in this study. Each trial demonstrated a low risk of bias. After 5 years, bioresorbable stents showed outcomes similar to conventional metal stents in terms of cardiac mortality. However, they were inferior in terms of lesion revascularization rates, in-stent thrombosis rates, target lesion failure, target vessel failure, and myocardial infarction. Conclusions: While bioresorbable stents are comparable to metallic stents in terms of cardiac mortality rates, they exhibit significant drawbacks that warrant clinical consideration.

A scientometrics analysis and visualization of refractory gastroesophageal reflux disease.

Background: Refractory gastroesophageal reflux disease (refractory GERD) is a heterogeneous disease characterized by unresponsiveness or poor efficacy to proton-pump inhibitors (PPIs). This chronic disorder substantially weakens patients' mental wellbeing and quality of life, increasing the financial burden on society. Multiple articles have been reported in this area. However, literature involving scientometric analysis of refractory GERD is absent. Therefore, it is necessary to understand the evolution of research themes and the main hotspots of refractory GERD through bibliometric methods. Methods: All documents related to refractory GERD based on the WOS Core Collection from January 2000 to November 2023 were selected for analysis. Citespace V 6.1 R6, VOSviewer V 1.6.20, and Scimago Graphica V 1.0.38 were used to perform bibliometric analysis. Results: We collected a total of 241 research articles from 36 countries and 322 institutions, contributed by over 1,000 authors. Over the last 20 years, the number of articles in this field has increased year by year, and since 2011, the number of publications has increased dramatically, with 85.89% of the papers. These countries are led by the United States and Japan. GUT had the highest number of citations and DIGESTION had the highest number of publications. Research on standardized diagnosis and management, mechanisms, novel monitoring methods, and innovative drugs and procedures for refractory GERD are the main topics and hotspots in this field. This study also found that neuroimmune interaction is closely related to refractory GERD, which may be a new direction for future mechanism research. Conclusion: Our study is the first bibliometric analysis of the global literature on refractory GERD. This research provides valuable insights for researchers, enabling them to quickly understand the research frontier and hot topics of this field.

Discovery of Candidatus Nitrosomaritimum as a New Genus of Ammonia-Oxidizing Archaea Widespread in Anoxic Saltmarsh Intertidal Aquifers.

Ammonia-oxidizing archaea (AOA) are widely distributed in marine and terrestrial habitats, contributing significantly to global nitrogen and carbon cycles. However, their genomic diversity, ecological niches, and metabolic potentials in the anoxic intertidal aquifers remain poorly understood. Here, we discovered and named a novel AOA genus, Candidatus Nitrosomaritimum, from the intertidal aquifers of Yancheng Wetland, showing close metagenomic abundance to the previously acknowledged dominant Nitrosopumilus AOA. Further construction of ammonia monooxygenase-based phylogeny demonstrated the widespread distribution of Nitrosomaritimum AOA in global estuarine-coastal niches and marine sediment. Niche differentiation among sublineages of this new genus in anoxic intertidal aquifers is driven by salinity and dissolved oxygen gradients. Comparative genomics revealed that Candidatus Nitrosomaritimum has the genetic capacity to utilize urea and possesses high-affinity phosphate transporter systems (phnCDE) for surviving phosphorus-limited conditions. Additionally, it contains putative nosZ genes encoding nitrous-oxide (N2O) reductase for reducing N2O to nitrogen gas. Furthermore, we gained first genomic insights into the archaeal phylum Hydrothermarchaeota populations residing in intertidal aquifers and revealed their potential hydroxylamine-detoxification mutualism with AOA through utilizing the AOA-released extracellular hydroxylamine using hydroxylamine oxidoreductase. Together, this study unravels the overlooked role of priorly unknown but abundant AOA lineages of the newly discovered genus Candidatus Nitrosomaritimum in biological nitrogen transformation and their potential for nitrogen pollution mitigation in coastal environments.

Biomedical potentials of alginate via physical, chemical, and biological modifications.

Alginate is a linear polysaccharide with a modifiable structure and abundant functional groups, offers immense potential for tailoring diverse alginate-based materials to meet the demands of biomedical applications. Given the advancements in modification techniques, it is significant to analyze and summarize the modification of alginate by physical, chemical and biological methods. These approaches provide plentiful information on the preparation, characterization and application of alginate-based materials. Physical modification generally involves blending and physical crosslinking, while chemical modification relies on chemical reactions, mainly including acylation, sulfation, phosphorylation, carbodiimide coupling, nucleophilic substitution, graft copolymerization, terminal modification, and degradation. Chemical modified alginate contains chemically crosslinked alginate, grafted alginate and oligo-alginate. Biological modification associated with various enzymes to realize the hydrolysis or grafting. These diverse modifications hold great promise in fully harnessing the potential of alginate for its burgeoning biomedical applications in the future. In summary, this review provides a comprehensive discussion and summary of different modification methods applied to improve the properties of alginate while expanding its biomedical potentials.

Homogeneous Deposition of Zinc on N-Doped Carbon Fibers Interconnected with Sn Nanoparticles for Advanced Aqueous Zinc Batteries.

Currently, inhomogeneous distribution of Zn2+ on the surface of the Zn anode is still the essential reason for dendrite formation and unsatisfactory stability of zinc ion batteries. Given the merits of strong interaction between Sn and Zn, as well as a low nucleation barrier during Zn deposition, the combination of metallic Sn with carbon material is expected to improve the deposition of zinc ions and inhibit the growth of zinc dendrites by guiding the homogeneous plating/stripping of zinc on the electrode surface. In this article, zincophilic Sn nanoparticles with low nucleation barriers and strong interaction with Zn2+ were embedded into 3D N-doped carbon nanofibers using a simple electrostatic spinning technique. Accordingly, when serving as an artificial coating layer for the zinc metal anode, an ultrastable Sn@NCNFs@Zn||Sn@NCNFs@Zn symmetric cell can be achieved for over 3500 h with a low nucleation overpotential of 29.1 mV. Significantly, the full cell device assembled with the as-prepared anode and MnO2 cathode exhibits desirable electrochemical behaviors. Moreover, this simple method could be extended to other metal-carbon composites, and to ensure ease in scaling up as required. Such significant approach can provide an effective strategy for the design of high-performance zinc anodes.

Reconstructing high-resolution gridded precipitation data in the southwest China highland canyon area using an improved (MGWR) downscaling method.

High-spatiotemporal-resolution rainfall data are vital for investigating local terrestrial water cycles. Although remote-sensing satellite retrieval of precipitation products effectively reproduces spatial patterns of rainfall, it suffers from low spatial resolution. To overcome such limitations, a two-step downscaling approach is proposed here. First, 80 % of the meteorological-station data is utilized to calibrate the original Global Precipitation Measurement (GPM) data, enhancing the correlation between GPM and station data. Subsequently, utilizing elevation, slope, aspect, the normalized difference vegetation index (NDVI), wind direction, water vapor, and land surface temperature, as well as slope and aspect correction factors, as independent variables, multiscale geographically weighted regression (MGWR) and temporal lag MGWR (TL-MGWR) models were constructed. Through the aforementioned steps, downscaled monthly and daily precipitation data for the geographic region under investigation in 2022 at a spatial resolution of 0.01° were obtained. Our findings indicate that selectively employing suitable MGWR or TL-MGWR models on a monthly basis can effectively downscale monthly GPM rainfall data. The downscaled (original) monthly precipitation data exhibited a correlation of 0.94 (0.768), with a mean absolute error (MAE) of 16.233 mm/month, root-mean-square error (RMSE) of 27.106 mm/month, and bias of -0.043. Similar enhancement was likewise noted in daily precipitation, displaying a correlation coefficient of 0.863 (0.318) for downscaled (original) data, and a RMSE of 3.209 mm/day, MAE of 1.082 mm/day, and bias of -0.06. The downscaled results show a correlation increase of 0.172 monthly and 0.545 daily, with MAE reductions of 18.43 mm/month and 1.658 mm/day, RMSE reductions of 26.172 mm/month and 4.183 mm/day, and bias reductions of 82.7 % and 56.8 %. In summary, the data after downscaling, both for monthly and daily datasets, was markedly improved in accuracy. The proposed downscaling method is applicable for reconstructing high-resolution grid data in the complex terrain of the southwest China highland canyon area.

Pancreatic cancer mortality trends attributable to high fasting blood sugar over the period 1990-2019 and projections up to 2040.

Background: Pancreatic cancer (PC) is a prevalent malignancy within the digestive system, with diabetes recognized as one of its well-established risk factors. Methods: Data on PC mortality attributed to high fasting blood sugar were retrieved from the Global Burden of Disease (GBD) study 2019 online database. To assess the temporal trends of PC burden attributable to high fasting plasma glucose (HFPG), estimated annual percentage changes (EAPCs) for age-standardized death rates (ASDRs) between 1990 and 2019 were determined using a generalized linear model. Furthermore, a Bayesian age-period-cohort (BAPC) model using the integrated nested Laplacian approximation algorithm was employed to project the disease burden over the next 20 years. Results: Globally, the crude death number of PC attributable to HFPG almost tripled (from 13,065.7 in 1990 to 48,358.5 in 2019) from 1990 to 2019, and the ASDR increased from 0.36/100,000 to 0.61/100,000 with an EAPC of 2.04 (95% CI 1.91-2.16). The population aged ≥70 years accounted for nearly 60% of total deaths in 2019 and experienced a more significant increase, with the death number increasing approximately fourfold and the ASDR increasing annually by 2.65%. In regions with different sociodemographic indexes (SDIs), the highest disease burden was observed in the high-SDI region, whereas more pronounced increasing trends in ASDR were observed in the low to middle-SDI, low-SDI, and middle-SDI regions. Additionally, a significantly negative association was found between EAPCs and ASDRs of PC attributable to HFPG from 1990 to 2019. Moreover, the BAPC model predicts that ASDR and age-standardized disability-adjusted life-years (DALYs) rate for PC attributed to HFPG was projected to increase obviously for men and women from 2019 to 2040. Conclusions: The burden of PC attributed to HFPG has increased globally over the past three decades, with the elderly population and high-SDI regions carrying a relatively greater disease burden, but more adverse trends observed in low-SDI areas. Furthermore, the burden is projected to continue increasing over the next 20 years. Hence, more tailored prevention methodologies should be established to mitigate this increasing trend.

Association between enlarged perivascular spaces in basal ganglia and cerebral perfusion in elderly people.

Background and objective: Enlarged perivascular spaces in basal ganglia (BG-EPVS) are considered an imaging marker of cerebral small vessel disease (CSVD), but its pathogenesis and pathophysiological process remain unclear. While decreased cerebral perfusion is linked to other CSVD markers, the relationship between BG-EPVS and cerebral perfusion remains ambiguous. This study aimed to explore this association. Methods: Elderly individuals with severe BG-EPVS (n = 77) and age/sex-matched controls (n = 89) underwent head CT perfusion imaging. The cerebral perfusion parameters including mean transit time (MTT), time to maximum (TMAX), cerebral blood flow (CBF), and cerebral blood volume (CBV) were quantitatively measured by symmetric regions of interest plotted in the basal ganglia region. Point-biserial correlation and logistics regression analysis were performed to investigate the association between BG-EPVS and cerebral perfusion. Results: There were no significant differences in MTT, TMAX, or CBF between BG-EPVS group and control group. CBV was significantly lower in the BG-EPVS group (p = 0.035). Point-biserial correlation analysis showed a negative correlation between BG-EPVS and CBV (r = -0.198, p = 0.011). BG-EPVS group and control group as the dependent variable, binary logistics regression analysis showed that CBV was not an independent risk factor for severe BG-EPVS (p = 0.448). All enrolled patients were divided into four groups according to the interquartile interval of CBV. The ordered logistic regression analysis showed severe BG-EPVS was an independent risk factor for decreased CBV after adjusting for confounding factors (OR = 2.142, 95%CI: 1.211-3.788, p = 0.009). Conclusion: Severe BG-EPVS is an independent risk factor for decreased CBV in the elderly, however, the formation of BG-EPVS is not solely dependent on changes in CBV in this region. This finding provides information about the pathophysiological consequence caused by severe BG-EPVS.

Reversible modulation of superconductivity in thin-film NbSe2 via plasmon coupling.

In recent years, lightwave has stood out as an ultrafast, non-contact control knob for developing compact superconducting circuitry. However, the modulation efficiency is limited by the low photoresponse of superconductors. Plasmons, with the advantages of strong light-matter interaction, present a promising route to overcome the limitations. Here we achieve effective modulation of superconductivity in thin-film NbSe2 via near-field coupling to plasmons in gold nanoparticles. Upon resonant plasmon excitation, the superconductivity of NbSe2 is substantially suppressed. The modulation factor exceeds 40% at a photon flux of 9.36 × 1013 s-1mm-2, and the effect is significantly diminished for thicker NbSe2 samples. Our observations can be theoretically interpreted by invoking the non-equilibrium electron distribution in NbSe2 driven by the plasmon-associated evanescent field. Finally, a reversible plasmon-driven superconducting switch is realized in this system. These findings highlight plasmonic tailoring of quantum states as an innovative strategy for superconducting electronics.

Enhanced Selectivity in Microdroplet-Mediated Enzyme Catalysis.

Natural enzymes with enhanced catalytic activity and selectivity have long been studied by tuning the microenvironment around the active site, but how to modulate the active-site electric field in a simple fashion remains challenging. Here, we demonstrate that microdroplets as a simple yet versatile reactor can enhance the electric field at the active site of an enzyme. By using horseradish peroxidase as a model, improved selectivity in microdroplet-mediated enzyme catalysis can be obtained. Quantum mechanical/molecular dynamics calculations and vibrational Stark spectroscopy reveal that the electric field at the microdroplet interface can influence the electrostatic preorganization and orientation of the enzyme to enhance its internal electric field. As a result, the free energies of the substrate and heme can be tuned by the internal electric field, thereby changing its catalytic reaction pathway for a classical substrate, 3,3',5,5'-tetramethylbenzidine, and enabling selective C-N additions for specific substrates. This finding provides a green, simple, and effective way to modulate enzyme-catalyzed reactions and holds promise for a broad spectrum of biosensing and biosynthesis applications.

[Recent advances in protein precipitation-based methods for drug-target screening].

Drug targets are biological macromolecules that bind drug molecules in vivo. Therefore, the system-wide identification of drug targets plays a vital role in fully understanding the mechanism of drug action, efficacy, and side effects. The unbiased screening of drug targets may accelerate the process of drug discovery and candidate screening. Mass spectrometry is a key tool for large-scale protein identification and accurate quantification owing to its high acquisition speed, resolution, and sensitivity. Mass spectrometry-based proteomics has been widely used for drug-target screening. It can systematically identify the protein-target landscape of a drug and elucidate drug-protein interactions. Commonly used drug-target characterization methods, such as labeling-based affinity enrichment, require the chemical derivatization of drug molecules, which is not only time-consuming but may also affect the affinity of the drug towards its targets. Furthermore, the spatial effects of the derivatization groups may block interactions between the drug and its targets. Considering the disadvantages of affinity-enrichment methods, strategies that do not require chemical derivatization have received widespread attention. Proteins may undergo denaturation, unfolding, and precipitation under different conditions such as high temperatures, extreme pH, denaturants, and mechanical stress. Binding to small-molecule drugs may alter the folding balance of target proteins. The conformational stability of target proteins can be stabilized by binding with drugs, and protein-drug complexes are more resistant than free proteins to the precipitation induced by different conditions. Based on this mechanism, various large-scale drug-target identification methods using protein precipitation have been developed by combining proteomics and mass spectrometry analysis, including thermal proteome profiling and solvent-, mechanical stress-, and pH-induced protein precipitation. These methods have been successfully applied to the characterization of small-molecule drug targets. In this review, we describe the protein precipitation-based methods used for the high-throughput discovery of drug targets and elucidation of the interactions between drugs and proteins in the past decade. We also summarize the characteristics of each method and discuss their application potential in drug-efficacy evaluation and drug discovery.

Brain Age Estimation from Overnight Sleep Electroencephalography with Multi-Flow Sequence Learning.

Purpose: This study aims to improve brain age estimation by developing a novel deep learning model utilizing overnight electroencephalography (EEG) data. Methods: We address limitations in current brain age prediction methods by proposing a model trained and evaluated on multiple cohort data, covering a broad age range. The model employs a one-dimensional Swin Transformer to efficiently extract complex patterns from sleep EEG signals and a convolutional neural network with attentional mechanisms to summarize sleep structural features. A multi-flow learning-based framework attentively merges these two features, employing sleep structural information to direct and augment the EEG features. A post-prediction model is designed to integrate the age-related features throughout the night. Furthermore, we propose a DecadeCE loss function to address the problem of an uneven age distribution. Results: We utilized 18,767 polysomnograms (PSGs) from 13,616 subjects to develop and evaluate the proposed model. The model achieves a mean absolute error (MAE) of 4.19 and a correlation of 0.97 on the mixed-cohort test set, and an MAE of 6.18 years and a correlation of 0.78 on an independent test set. Our brain age estimation work reduced the error by more than 1 year compared to other studies that also used EEG, achieving the level of neuroimaging. The estimated brain age index demonstrated longitudinal sensitivity and exhibited a significant increase of 1.27 years in individuals with psychiatric or neurological disorders relative to healthy individuals. Conclusion: The multi-flow deep learning model proposed in this study, based on overnight EEG, represents a more accurate approach for estimating brain age. The utilization of overnight sleep EEG for the prediction of brain age is both cost-effective and adept at capturing dynamic changes. These findings demonstrate the potential of EEG in predicting brain age, presenting a noninvasive and accessible method for assessing brain aging.

High-performance Piezoelectric Two-dimensional Covalent Organic Frameworks.

Organic piezoelectric nanogenerators (PENGs) are attractive in harvesting mechanical energy for various self-powering systems. However, their practical applications are severely restricted by their low output open circuit voltage. To address this issue, herein, we prepared two two-dimensional (2D) covalent organic frameworks (COFs, CityU-13 and CityU-14), functionalized with fluorinated alkyl chains for PENGs. The piezoelectricity of both COFs was evidenced by switchable polarization, characteristic butterfly amplitude loops, phase hysteresis loops, conspicuous surface potentials and high piezoelectric coefficient value (d33). The PENGs fabricated with COFs displayed highest output open circuit voltages (60 V for CityU-13 and 50 V for CityU-14) and delivered satisfactory short circuit current with an excellent stability of over 600 seconds. The superior open circuit voltages of CityU-13 and CityU-14 rank in top 1 and 2 among all reported organic materials-based PENGs.

ABE-ultramax for high-efficiency biallelic adenine base editing in zebrafish.

Advancements in CRISPR technology, particularly the development of base editors, revolutionize genetic variant research. When combined with model organisms like zebrafish, base editors significantly accelerate and refine in vivo analysis of genetic variations. However, base editors are restricted by protospacer adjacent motif (PAM) sequences and specific editing windows, hindering their applicability to a broad spectrum of genetic variants. Additionally, base editors can introduce unintended mutations and often exhibit reduced efficiency in living organisms compared to cultured cell lines. Here, we engineer a suite of adenine base editors (ABEs) called ABE-Ultramax (Umax), demonstrating high editing efficiency and low rates of insertions and deletions (indels) in zebrafish. The ABE-Umax suite of editors includes ABEs with shifted, narrowed, or broadened editing windows, reduced bystander mutation frequency, and highly flexible PAM sequence requirements. These advancements have the potential to address previous challenges in disease modeling and advance gene therapy applications.

High systemic inflammatory response index (SIRI) is an independent risk factor for poor outcome in IgA nephropathy patients.

BACKGROUND: The systemic inflammatory response index (SIRI), a straightforward and easily accessible measure of inflammation and prognosis, has drawn more attention lately. It is unknown, however, if SIRI is important for IgA nephropathy (IgAN) patients' outcomes. To better clarify these concerns, we conducted this investigation. METHOD: This retrospective study involved 981 patients with biopsy-confirmed IgAN from West China Hospital of Sichuan University between 2008 and 2019. The patients were divided into two groups based on the SIRI's optimal cut-off value calculated by the X-tile: the low SIRI group (SIRI ≤ 0.63, n = 312) and the high SIRI group (SIRI > 0.63, n = 669). Basic clinical characteristics at the time of renal biopsy were evaluated, and the relationship between SIRI and the combined endpoint was analyzed. We also used the Cox proportional hazard model and Kaplan‒Meier curve to evaluate the renal prognosis of IgAN. RESULTS: A total of 981 IgAN patients were included. During a median follow-up period of 56.7 months (36.8-80.4 months), 122 patients progressed to the combined endpoint (12.4%). Patients were divided into a low SIRI group (SIRI ≤ 0.63, n = 312) and a high SIRI group (SIRI > 0.63, n = 669) according to the optimal cut-off value of the systemic inflammatory response index (SIRI). Further analysis showed that a higher SIRI value was significantly associated with the risk of IgAN patients reaching the composite endpoint (HR 1.62, 95% CI 1.02-2.56, p = 0.041). CONCLUSION: High SIRI is a significant and independent risk factor for renal disease progression in IgAN patients.

Evaluating the Usability of mHealth Apps: An Evaluation Model Based on Task Analysis Methods and Eye Movement Data.

Advancements in information technology have facilitated the emergence of mHealth apps as crucial tools for health management and chronic disease prevention. This research work focuses on mHealth apps for the management of diabetes by patients on their own. Given that China has the highest number of diabetes patients in the world, with 141 million people and a prevalence rate of 12.8% (mentioned in the Global Overview of Diabetes), the development of a usability research methodology to assess and validate the user-friendliness of apps is necessary. This study describes a usability evaluation model that combines task analysis methods and eye movement data. A blood glucose recording application was designed to be evaluated. The evaluation was designed based on the model, and the feasibility of the model was demonstrated by comparing the usability of the blood glucose logging application before and after a prototype modification based on the improvement suggestions derived from the evaluation. Tests showed that an improvement plan based on error logs and post-task questionnaires for task analysis improves interaction usability by about 24%, in addition to an improvement plan based on eye movement data analysis for hotspot movement acceleration that improves information access usability by about 15%. The results demonstrate that this study presents a usability evaluation model for mHealth apps that enables the effective evaluation of the usability of mHealth apps.

The clinical and pathological evaluation of patients with immunoglobulin A nephropathy by diffusion tensor imaging and intravoxel incoherent motion diffusion-weighted imaging.

OBJECTIVES: To explore the efficacy of diffuse magnetic resonance imaging (MRI) for identifying clinicopathological changes in immunoglobulin A nephropathy (IgAN) patients. METHODS: The study enrolled IgAN patients and healthy volunteers. IgAN patients were divided into Group 1 [estimated glomerular filtration rate (eGFR) ≥ 90 mL/min/1.73 m2], Group 2 (60 ≤ eGFR < 90 mL/min/1.73 m2), and Group 3 (eGFR < 60 mL/min/1.73 m2). Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion tensor imaging (DTI) were performed via 3.0 T magnetic resonance. Diffuse MRI, clinical, and pathological indicators were collected and analysed. P < .05 was considered statistically significant. RESULTS: Forty-six IgAN patients and twenty-seven volunteers were enrolled. The apparent diffusion coefficient, diffusion coefficient (D), perfusion fraction (f), and fractional anisotropy (FA) were significantly different among IgAN subgroups and controls. These parameters were positively correlated with eGFR and negatively with creatinine, and inversely correlated with glomerular sclerosis, interstitial fibrosis, and tubular atrophy (all P < .05). They had significantly high area under the curve (AUC) for distinguishing IgAN patients from controls, while FA had the highest AUC in identifying Group 1 IgAN patients from volunteers. CONCLUSIONS: DTI and IVIM-DWI had the advantage of evaluating clinical and pathological changes in IgAN patients. DTI was superior at distinguishing early IgAN patients and might be a noninvasive marker for screening early IgAN patients from healthy individuals. ADVANCES IN KNOWLEDGE: DTI and IVIM-DWI could evaluate clinical and pathological changes and correlated with Oxford classification in IgAN patients. They could also identify IgAN patients from healthy populations, while DTI had superiority in differentiating early IgAN patients.

Heterologous expression and characterization of two delta glutathione S-transferases genes involved in imidacloprid metabolism in Grapholita molesta.

Glutathione S-transferases (GSTs) are multifunctional enzymes, and insect GSTs play a pivotal role in the metabolism of insecticides. Grapholita molesta is a worldwide pest that causes substantial economic losses to the fruit industry. However, it remains unclear how imidacloprid, a commonly used insecticide in orchards, is metabolized by G. molesta. In the present study, the synergist diethyl maleate (DEM), which inhibits the GST activity, exhibited a 22-fold synergistic ratio against imidacloprid. Two new GST genes, GmGSTD2 (OR096251) and GmGSTD3 (OR096252), were identified and successfully cloned, showing the highest expression in the Malpighian tubes. Knockdown of GmGSTD2 and GmGSTD3 by RNA interference, increased the mortality of G. molesta from 28% to 47% following imidacloprid treatment. Both recombinant GmGSTD2 and GmGSTD3 proteins exhibited 1-chloro-2,4-dinitrobenzene (CDNB) activity and could be inhibited by imidacloprid in vitro, with maximum inhibition was 60% for GmGSTD2 and 80% for GmGSTD3. These results suggested that GSTs participate in the metabolism of imidacloprid with GmGSTD2 and GmGSTD3 playing key roles in this process.