Zn-Leaching Induced Rapid Self-Reconstruction of NiFe-Layered Double Hydroxides for Boosted Oxygen Evolution Reaction.

Optimizing the active centers through reconstruction is recognized as the key to construct high-performance oxygen evolution reaction (OER) catalysts. Herein, a simple and rapid in situ leaching strategy to promote the self-reconstruction of NiFe-layered double hydroxides (LDHs) catalysts is reported. The trace Zn dopants are introduced in advance by a facile and one-step hydrothermal method, followed by leaching over the electrochemical activation process, which can remarkably reduce the formation potential of NiFeOOH active centers to enable the deeper self-reconstruction for the formation of abundant highly active centers. Moreover, the self-restructured NiFeOOH-VZn cannot only significantly lower the dehydrogenation energy barrier for the transformation from Ni(OH)2 to NiOOH, but also decrease the free energy barrier of rate determining step for the *OH converted to *O through a deprotonation process, thus significantly boosting the OER behaviors. As a proof of concept, the obtained NiFeOOH-VZn catalyst just requires a low overpotential of 240 mV at 10 mA cm-2, and delivers robust stability at 50 mA cm-2 over 120 h, which outperforms the benchmark of noble metal RuO2 and those of most non-noble metal catalysts ever reported.

Multiple rib and vertebral fractures associated with Bordetella pertussis infection: a case report.

BACKGROUND: Pertussis is a highly contagious respiratory disease caused by the bacterium Bordetella pertussis, characterized by paroxysms of severe coughing, and predominantly affects children. We report the first case of multiple fractures in the ribs, lumbar spine, and sacrum associated with severe coughing caused by Bordetella pertussis infection in an adult. CASE PRESENTATION: A 49-year-old female presented with acute-onset chest wall pain for 3 weeks. Imaging results revealed multiple fractures in the ribs and vertebrae, as well as bilateral pleural effusion, pericardial effusion, right pneumothorax, and enlargement of the left parapharyngeal and subclavian lymph nodes. The patient's bone density scan, autoimmune antibodies, bone marrow biopsy, and sacral bone biopsy all came back normal. Imaging test results found no evidence of solid tumors or active TB infection. The patient later recalled having violent coughing prior to the onset of chest pain and several family members having similar symptoms. Her blood sample was sent to the CDC, revealing Bordetella pertussis toxin (PT) IgG titer of 110.68 IU/mL. The patient was diagnosed with pertussis and multiple stress fractures from violent coughing. Symptomatic treatments were administered, and the patient's symptoms improved. The patient was followed up 8 weeks later, she reported no more coughing or chest pain. CONCLUSIONS: Pertussis is not just a pediatric disease, but diagnosis in adults is challenging as patients may present with a myriad of confusing symptoms, such as multiple stress fractures due to violent coughing. Medical and epidemiological histories are key to reaching the correct diagnosis, which is essential for appropriate treatments to avoid further complications. Adult immunization should be suggested both for the protection of the adult population and to prevent transmission to children.

Simulation, prediction and optimization of typical heavy metals immobilization in swine manure composting by using machine learning models and genetic algorithm.

Machine learning (ML) is a novel method of data analysis with potential to overcome limitations of traditional composting experiments. In this study, four ML models (multi-layer perceptron regression, support vector regression, decision tree regression, and gradient boosting regression) were integrated with genetic algorithm to predict and optimize heavy metal immobilization during composting. Gradient boosting regression performed best among the four models for predicting both heavy metal bioavailability variations and immobilization. Gradient boosting regression-based feature importance analysis revealed that the heavy metal initial bioavailability factor, total phosphorus, and composting duration were the determinant factors for heavy metal bioavailability variations (together contributing >75%). After genetic algorithm optimization, the maximum immobilization rates of Cu, Zn, Cd, As, and Cr were 79.53, 31.30, 14.91, 46.25, and 66.27%, respectively, superior to over 90% of the measured data. These findings demonstrate the potential application of ML to risk-control for heavy metals in livestock manure composting.

Binding characteristics of humic substances with Cu and Zn in response to inorganic mineral additives during swine manure composting.

Composting is suitable for recycling livestock manure into valuable organic fertilizer, which can improve soil quality while mitigating potential risk of heavy metal pollution. Humic substances (HS) in compost have been demonstrated to play a key role in regulating the redistribution of heavy metal fractions. However, limited direct information have been reported on how different components of HS complexes with heavy metals to affect their bioavailability during composting. In this study, sequential extraction procedures (H2O, KCl, Na4P2O7, NaOH and HNO3) were used to assess the characteristics that HS bound with Cu and Zn during composting of swine manure and straw added either 5% boron waste (BW) or 5% phosphate rock (PR). Organically complexed fraction extracted by Na4P2O7 contained only 33-41% of the Cu but most of the Zn (81-87%). During composting, initially mobile fractions of Cu and Zn (extracted by H2O or KCl) changed into more stable fractions (extracted by NaOH and HNO3), and both organic matter and fulvic acids (FA) were identified as critical factors to explain this redistribution based on redundancy analysis. Over 80% of Cu and Zn were complexed with FA of HS. However, exogenous additives (phosphate rock and boron waste) enhanced Cu conversion by promoting humification (Humic acid/Fulvic acids, HA/FA) whereas they had limited influence on Zn, due to the relatively weak binding relationship between Zn and HA.

Normotensive and hypertensive Immunoglobulin a nephropathy with ischemic renal injury: clinicopathological characteristics and prognosis.

OBJECTIVES: This study aimed to investigate the clinicopathological characteristics and prognosis of normotensive and hypertensive IgAN patients with ischemic renal injury. METHODS: A total of 344 cases of IgAN with ischemic renal injury were included in the study, including 99 normotensive IgAN patients (28.8%) and 245 hypertensive IgAN patients (71.2%). In addition, 467 IgAN patients without ischemic renal injury were included as controls, including 205 normotensive patients and 262 hypertensive patients. Clinicopathological and prognostic data were collected and analyzed. RESULTS: Compared with patients without ischemic renal injury, IgAN patients with ischemic renal injury displayed a higher proportion of hypertention, a higher proportion of ischemic glomerulosclerosis, tubular atrophy/interstitial fibrosis and vascular lesions (all p < .05). There was no significant difference in cumulative survival between the normotensive IgAN patients groups (Log-rank χ2 = 0.479; p = .489). Furthermore, ischemic renal injury was not a risk factor for end-point events in normotensive IgAN patients (HR = 1.103; 95% CI: 0.279-4.365; p = .889). There was lower cumulative survival in hypertensive IgAN patients with ischemic renal injury (Log-rank χ2 = 11.352, p = .001). Moreover, ischemic renal injury was a risk factor for end-point events in hypertensive IgAN patients (HR = 1.889; 95% CI: 1.124-3.178; p = .016). CONCLUSIONS: Ischemic renal injury can occur in normotensive IgAN patients. Although the pathological changes may not affect the long-term prognosis of normotensive IgAN patients, the prognosis for hypertensive IgAN patients remains poor. Therefore, increased attention should be paid to the clinical management of ischemic lesions in hypertensive IgAN patients.

Probing changes in humus chemical characteristics in response to biochar addition and varying bulking agents during composting: A holistic multi-evidence-based approach.

Despite the various benefits of humus, the changes in its chemical characteristics during composting in response to biochar addition and varying bulking agents remain to be further explored. In this study, three treatments were conducted, in which swine manure, bulking agent, and biochar were mixed at ratios of 4:1:0, 8:1:0, and 8:1:1. Fourier transform infrared spectroscopy (FTIR), carbon nuclear magnetic resonance spectroscopy (13C-NMR), three-dimensional excitation-emission matrix fluorescence spectroscopy (3D-EEM), and near-edge X-ray absorption fine structure (NEXAFS) were employed to characterize the chemical and structural properties of humus from multiple perspectives. The 3D-EEM spectra in this study showed a larger increase in humic acids (HAs) content (56%) and HAs to fulvic acids ratio (128%) during composting, indicating stronger humification in biochar-amended treatment. FTIR, 13C-NMR, and NEXAFS all confirmed the essential properties of HA as the core agronomic functional substance with rich aromatic and carboxyl groups, and that its aromaticity increased gradually during composting. In addition, 13C-NMR demonstrated that biochar addition and a relatively higher bulking agent ratio aided an increase in the carboxyl C proportion in HA after composting. In particular, NEXAFS revealed that biochar addition promoted the diversification of C, N, and O species in HA, with the emergence of quinone C and O-alkyl C as the main representatives. This work suggests that biochar addition and a relatively high bulking agent ratio could enhance humification and improve the agronomic function of humus.

An investigation of traffic density changes inside Wuhan during the COVID-19 epidemic with GF-2 time-series images.

In order to mitigate the spread of COVID-19, Wuhan was the first city to implement strict lockdown policy in 2020. Even though numerous researches have discussed the travel restriction between cities and provinces, few studies focus on the effect of transportation control inside the city due to the lack of the measurement and available data in Wuhan. Since the public transports have been shut down in the beginning of city lockdown, the change of traffic density is a good indicator to reflect the intracity population flow. Therefore, in this paper, we collected time-series high-resolution remote sensing images with the resolution of 1 m acquired before, during and after Wuhan lockdown by GF-2 satellite. Vehicles on the road were extracted and counted for the statistics of traffic density to reflect the changes of human transmissions in the whole period of Wuhan lockdown. Open Street Map was used to obtain observation road surfaces, and a vehicle detection method combing morphology filter and deep learning was utilized to extract vehicles with the accuracy of 62.56%. According to the experimental results, the traffic density of Wuhan dropped with the percentage higher than 80%, and even higher than 90% on main roads during city lockdown; after lockdown lift, the traffic density recovered to the normal rate. Traffic density distributions also show the obvious reduction and increase throughout the whole study area. The significant reduction and recovery of traffic density indicates that the lockdown policy in Wuhan show effectiveness in controlling human transmission inside the city, and the city returned to normal after lockdown lift.

SAAN: Similarity-Aware Attention Flow Network for Change Detection With VHR Remote Sensing Images.

Change detection (CD) is a fundamental and important task for monitoring the land surface dynamics in the earth observation field. Existing deep learning-based CD methods typically extract bi-temporal image features using a weight-sharing Siamese encoder network and identify change regions using a decoder network. These CD methods, however, still perform far from satisfactorily as we observe that 1) deep encoder layers focus on irrelevant background regions; and 2) the models' confidence in the change regions is inconsistent at different decoder stages. The first problem is because deep encoder layers cannot effectively learn from imbalanced change categories using the sole output supervision, while the second problem is attributed to the lack of explicit semantic consistency preservation. To address these issues, we design a novel similarity-aware attention flow network (SAAN). SAAN incorporates a similarity-guided attention flow module with deeply supervised similarity optimization to achieve effective change detection. Specifically, we counter the first issue by explicitly guiding deep encoder layers to discover semantic relations from bi-temporal input images using deeply supervised similarity optimization. The extracted features are optimized to be semantically similar in the unchanged regions and dissimilar in the changing regions. The second drawback can be alleviated by the proposed similarity-guided attention flow module, which incorporates similarity-guided attention modules and attention flow mechanisms to guide the model to focus on discriminative channels and regions. We evaluated the effectiveness and generalization ability of the proposed method by conducting experiments on a wide range of CD tasks. The experimental results demonstrate that our method achieves excellent performance on several CD tasks, with discriminative features and semantic consistency preserved.

Anthropogenic and climate impacts on carbon stocks of grassland ecosystems in Inner Mongolia and adjacent region.

Up to date, most studies reported that degradation is worsened in the grassland ecosystems of Inner Mongolia and adjacent regions as a result of intensified grazing. This seems to be scientific when considering the total forage or total above-ground biomass as a degradation indicator, but it does not hold true in terms of soil organic carbon density (SOCD). In this study, we quantified the changes of grassland ecosystem carbon stock in Inner Mongolia and adjacent regions from the 1980s to 2000s and identified the major drivers influencing these variations, using the National Grassland Resource Inventory and Soil Survey Dataset in 1980s and the Inventory data during 2002 to 2009 covering 624 sampling plots concerned vegetal traits and edaphic properties across the study region. The result indicated that the above-, below-ground and total vegetation biomass declined from the 1980s to 2000s by ∼ 10 %. However, total forage production increased by 6.72 % when considering livestock intake. SOCD remained stable despite a 67 % increase in grazing intensity. A generalized linear model (GLIM) analysis suggested that an increase in grazing intensity from the 1980s to 2000s could only explain 1.04 % of the total biomass change, while changes in precipitation and temperature explained 17.7 % (p < 0.05) of total vegetation biomass (TVB) change. Meanwhile, SOCD change during 1980s - 2000s could be explained 10.08 % by the soil texture (p < 0.05) and <1.6 % by changes in climate and livestock. This implies that the impacts of climate change on grassland biomass are more significant than those of grazing utilization, and SOCD was resistant to both climate change and intensified grazing. Overall, intensified grazing did not result in significant negative impacts on the grassland carbon stocks in the study region during the 1980s and 2000s. The grassland ecosystems possess a mechanism to adjust their root-shoot ratio, enabling them to maintain resilience against grazing utilization.

Blind identification of active landslides in urban areas: a new set of comprehensive criteria.

More than 70% of catastrophic landslides were previously unknown and brought tremendous losses to human life and property in urban regions; therefore, there is an urgent need for early identification of active landslides to eliminate landslide risk at the early stage. However, early identification of landslides has always been a worldwide challenge due to high concealment, steep topography, inaccessible location, and sudden onset. This work suggests a new set of comprehensive criteria for the early identification of landslides by integrating surface deformation, geological, topographic, geomorphological, and disaster-failure features. This set of criteria is universally applicable with no use of the prior knowledge of landslide locations (blind identification) and is successfully validated by a field survey. This work selects the Xuecheng region, a hard-hit area of landslides, as the study area and employs multisource data (seismic, geological, topographic, meteorological, SAR, and optical remote sensing data) and time-series InSAR technology to identify active landslides and reveal their deformation rules. Some new viewpoints are suggested. (1) The new comprehensive criteria synthesize the surface deformation, disaster-controlling, and disaster-inducing characteristics and achieve relatively high accuracy by field validation. (2) Forty-seven active landslides are identified in Xuecheng with no use of the prior knowledge of landslides. The soft rocks or soft-hard interbeddings, tectonic movement, fluvial undercutting and eroding, precipitation, earthquakes, and human engineering activity control or induce the development of these active landslides. (3) Two giant landslides that significantly threaten human lives and properties and exhibit different movement modes are selected to highlight the deformation rules of active landslides under the coupled action of poor lithologic condition, tectonic movement, river erosion, precipitation, and human engineering activity. The suggested new criteria can be applied to other landslide hard-hit urban regions and contribute to the timely and effective prevention and control of catastrophic landslides, reduction of enormous disaster losses, and rational management of the environment.

The dynamic TRß/IGH CDR3 repertoire features in patients with liver transplantation.

OBJECTIVE: At present, little is known about the immune mechanism of liver transplantation caused by decompensated cirrhosis. Lymphocytes play an essential important role in the immune rejection of liver transplantation. In this study, we aimed to comprehensively analyze changes in complementary determinant 3 (CDR3) repertoire of T cell receptor ß chain (TRß) and immunoglobulin heavy chain (IGH) in liver transplantation patients and healthy controls (HC). METHODS: High-throughput sequencing technology was used to study the characteristics of TRß/IGH CDR3 repertoire, and identify the amino acid sequences of TRß and IGH associated with liver transplantation patients and HC. RESULTS: We found that some TRß and IGH CDR3 repertoire characteristics differed between liver transplant patients and HC. The diversity of TRß CDR3 increased in the liver transplantation group. First and seven days after live transplantation patients showed a lower degree of T cell clone amplification compared to the HC group. The CDR3 repertoire of the TRß/IGH chain was certainly biased in the use of some V, D, and J gene segments, TRß/IGH V-J combined frequency was also skewed and TRß CDR3 clonotypes were shared at a higher degree in the liver transplantation patients. Importantly, one amino acid sequence in the decompensated cirrhosis group was significantly higher than that in the healthy group. It should be noted that the frequency of some CDR3 sequences is closely correlated with the different stages of liver transplantation, and these sequences may play a key role in liver transplantation. CONCLUSION: Based on the above results, we can better understand the dynamic changes of TCß/IGH CDR3 repertoire in patients during liver transplantation.

Predictive prognostic value of glomerular C3 deposition in IgA nephropathy.

BACKGROUND: IgAN is the most common primary glomerulonephritis worldwide. However, the pathogenesis of IgAN remains unknown. Currently, there is evidence that C3 deposition plays a role in disease development. This study aimed to investigate clinical, pathological features, and prognosis of adult IgAN patients with C3 deposition, as well as explore the role of complement activation in disease progression. METHODS: A total of 821 patients with biopsy-proven IgAN were included in this study. Patients were divided into three different groups according to their C3 deposition intensity. Clinical and pathological characteristics were compared between groups. Logistic analysis was used to estimate the relationship between C3 deposition and the Oxford scoring system. Univariate and multivariate Cox proportional hazard regression models were used to analyze the effect of the presence of C3 deposits on the prognosis of patients with IgA nephropathy. Kaplan-Meier survival analysis was used to evaluate the cumulative incidence of renal progression between groups. RESULTS: Patients with C3 deposition exhibited more severe clinical and pathological features and had a higher score according to the Oxford scoring system. With the increasing intensity of C3 deposition, patients present more hematuria, crescents, heavier interstitial inflammatory cell infiltration and a higher score on segmental sclerosis lesions. Logistic regression identified a positive relationship between C3 deposition and histopathology. Univariate and multivariate Cox regression indicated that C3 deposition was an independent risk factor for IgAN severity. The Kaplan-Meier survival curves indicated that patients with positive C3 deposition had a worse prognosis compared to those without C3 deposition. CONCLUSIONS: Patients with positive glomerular C3 deposition presented with more severe clinical and histopathological characteristics and a higher score on the Oxford scoring system. With the increasing intensity of C3 deposition, IgAN patients were more likely to present with high level of microscopic hematuria, fibrous crescents, interstitial inflammatory cell infiltration, and a higher score on segmental sclerosis lesions. C3 deposition at the time of renal biopsy is likely an independent risk factor for IgA nephropathy severity and progression.

Development and validation of risk prediction models for large for gestational age infants using logistic regression and two machine learning algorithms.

BACKGROUND: Large for gestational age (LGA) is one of the adverse outcomes during pregnancy that endangers the life and health of mothers and offspring. We aimed to establish prediction models for LGA at late pregnancy. METHODS: Data were obtained from an established Chinese pregnant women cohort of 1285 pregnant women. LGA was diagnosed as >90th percentile of birth weight distribution of Chinese corresponding to gestational age of the same-sex newborns. Women with gestational diabetes mellitus (GDM) were classified into three subtypes according to the indexes of insulin sensitivity and insulin secretion. Models were established by logistic regression and decision tree/random forest algorithms, and validated by the data. RESULTS: A total of 139 newborns were diagnosed as LGA after birth. The area under the curve (AUC) for the training set is 0.760 (95% confidence interval [CI] 0.706-0.815), and 0.748 (95% CI 0.659-0.837) for the internal validation set of the logistic regression model, which consisted of eight commonly used clinical indicators (including lipid profile) and GDM subtypes. For the prediction models established by the two machine learning algorithms, which included all the variables, the training set and the internal validation set had AUCs of 0.813 (95% CI 0.786-0.839) and 0.779 (95% CI 0.735-0.824) for the decision tree model, and 0.854 (95% CI 0.831-0.877) and 0.808 (95% CI 0.766-0.850) for the random forest model. CONCLUSION: We established and validated three LGA risk prediction models to screen out the pregnant women with high risk of LGA at the early stage of the third trimester, which showed good prediction power and could guide early prevention strategies.

Immobilization pathways of heavy metals in composting: Interactions of microbial community and functional gene under varying C/N ratios and bulking agents.

Excessive heavy metals (HMs) in livestock manure due to additives over-use limits its recycling through composting. However, few studies have investigated the interactive influence of microbial communities, functional genes, and environmental factors in HM immobilization during composting. Therefore, treatments with different C/N ratios (15:1, 20:1, 25:1) and bulking agents (maize straw, green waste, vinasse) were conducted to explore the HMs immobilization pathways using structural equation model (SEM). Results confirmed the promoting effect of C/N ratio of 20:1 and vinasse on microbial diversity, thus leading to greater HMs immobilization rate. Meanwhile, the dominant microbial phyla of Cu/Zn, Cd, As, and Cr were identified as Proteobacteria, Firmicutes, Chytridiomycota, and Bacteroidota, respectively. Moreover, the significant correlation between functional genes (copC, mt, cbh1, aoxB, yieF) and HMs illustrated potential immobilization effects of metal-binding proteins on Cu and Zn, humus complexation on Zn, and oxidase/reductase on As/Cr. Finally, SEM indicated that the redistribution of Cu, Zn, As, and Cr fractions was interactively influenced by environmental factors (organic matter, pH, electrical conductivity, and total phosphorus), microbial communities, and functional genes, while Cd was directly regulated by organic matter and total phosphorus. These results may provide a deeper understanding of HM immobilization pathways during swine manure composting.

Molecular Typing of Gastric Cancer Based on Invasion-Related Genes and Prognosis-Related Features.

Background: This study aimed to construct a prognostic stratification system for gastric cancer (GC) using tumour invasion-related genes to more accurately predict the clinical prognosis of GC. Methodology: Tumour invasion-related genes were downloaded from CancerSEA, and their expression data in the TCGA-STAD dataset were used to cluster samples via non-negative matrix factorisation (NMF). Differentially expressed genes (DEGs) between subtypes were identified using the limma package. KEGG pathway and GO functional enrichment analyses were conducted using the WebGestaltR package (v0.4.2). The immune scores of molecular subtypes were evaluated using the R package ESTIMATE, MCPcounter and the ssGSEA function of the GSVA package. Univariate, multivariate and lasso regression analyses of DEGs were performed using the coxph function of the survival package and the glmnet package to construct a RiskScore model. The robustness of the model was validated using internal and external datasets, and a nomogram was constructed based on the model. Results: Based on 97 tumour invasion-related genes, 353 GC samples from TCGA were categorised into two subtypes, thereby indicating the presence of inter-subtype differences in prognosis. A total of 569 DEGs were identified between the two subtypes; of which, four genes were selected to construct the risk model. This four-gene signature was robust and exhibited stable predictive performance in different platform datasets (GSE26942 and GSE66229), indicating that the established model performed better than other existing models. Conclusion: A prognostic stratification system based on a four-gene signature was developed with a desirable area under the curve in the training and independent validation sets. Therefore, the use of this system as a molecular diagnostic test is recommended to assess the prognostic risk of patients with GC.

Effects of typical sludge treatment on microplastics in China-Characteristics, abundance and micro-morphological evidence.

Microplastics (MPs) are emerging pollutants that are enriched in sludge. They enter soil through sludge soil amendment, landfill, and discard, which will cause inescapable environmental pollution risks. Sludge treatment technology commonly used in China include anaerobic digestion (AD), thermal drying (TD), thermal hydrolysis (TH) and aerobic composting (AC). In this study, characteristics of MPs in sewage sludge from four representative large cities in China (Zhengzhou, Chongqing, Guangzhou, and Guilin) were analyzed. Effects of four representative sludge treatment technology on sludge MPs were also studied. In addition, the amount of MPs input to soil from sludge in China was estimated. The abundance range of sludge MPs of representative cities in China was 1448-11,125 n∙kg-1 DW. Previous studies indicate that this abundance range is low among other domestic cities and is close to that of European countries. MPs were predominantly fiber-shaped, accounting for 46.66%; 56.5% MPs were white and transparent, and 62.5% were polypropylene and polyethylene. The abundance of MPs in the sludge increased after TH, indicating that MPs broke into smaller particles. However, the other three treatment methods had no significant influence on the abundance of MPs. Scanning electron microscopy analysis showed that the micro-morphology of sludge MPs surface were rougher after AD, and MPs cracked following TD and TH. Furthermore, broken edges were more blurred after TH, and surfaces of MPs were damaged and eroded after AC. The input quantities of MPs in sludge to soil was deduced to be 1013 particles per year. These results are important for controlling the potential risk of sludge MPs in China.

IgA nephropathy with acute kidney disease: Characteristics, prognosis, and causes.

BACKGROUND: The clinical manifestations and prognosis of IgA nephropathy (IgAN) are diverse. Some patients may present with kidney dysfunction lasting shorter than 3 months and meet the acute kidney disease (AKD) criteria. This study aimed to investigate the clinicopathological features, causes and prognosis of newly diagnosed cases of IgAN with AKD. METHODS: 1320 IgAN patients diagnosed via kidney biopsy between January 2012 and June 2018 were included in this retrospective study, with a median follow-up period of 35 months. We analyzed the clinicopathological, etiological variables, as well as short-term and long-term prognosis. The main outcome was a composite event of 40% decline in eGFR, kidney failure or death. RESULTS: Incidence of AKD was 8.8% in the newly diagnosed IgAN patients, and was found to be an independent risk factor affecting the short-term (HR, 7.1; 95% CI, 2.3-22.2; P = 0.001) and long-term (HR, 1.8; 95% CI, 1.2-2.6; P = 0.006) prognosis, respectively. The most common cause of AKD was malignant hypertension-related AKD (MHT-AKD; 24.1%), followed by hematuria-related AKD (H-AKD; 12.9%), nephrotoxic-drug-exposure-related AKD (NTDE-AKD; 12.1%) and crescents-related AKD (C-AKD; 11.2%). The patients in AKD group had more severe clinicopathological characteristics and poor short-term and long-term prognosis than non-AKD group. In subgroup analysis, the MHT-AKD had the worst 5 years survival rate, followed by NTDE-AKD and C-AKD, whereas H-AKD had the best survival rate. CONCLUSIONS: AKD is not rare among IgAN patients, and is an independent risk factor for short-term and long-term prognosis. IgAN patients with AKD resulting from different causes have different prognosis.

Association between the blood manganese (Mn) and hemoglobin in patients undergoing maintenance hemodialysis.

BACKGROUND AND AIMS: Manganese (Mn) and iron metabolism are closely related. Iron metabolism disorders often lead to anemia in patients undergoing maintenance hemodialysis (MHD). Here, we aimed to investigate the relationship between blood Mn and hemoglobin (Hb) in patients undergoing MHD. METHODS: Patients undergoing MHD in September 2019 were included in a cross-sectional study. Clinical and demographic data and blood samples were collected before hemodialysis sessions, and blood levels of Mn were measured by inductively coupled plasma mass spectrometry. Both multivariable linear and binary logistic regression analyses were performed to study the relationship between the blood Mn and Hb. RESULTS: A total of 144 patients undergoing MHD were enrolled in the study. The patients had a mean age of 64.33 ± 13.39 years, median vintage of 33.50 (16.25-57.50) months. Among them, 66 were females (45.8%). The median blood Mn level was 13.55 µg/L (IQR:9.92-17.48). Ninety-nine patients were anemic (68.8%). The mean Hb level was 99.83 ± 19.68 g/L. The patient group with high blood Mn had a high proportion of females, and these patients had high levels of RBC, hemoglobin, Hct, UIBC, serum TCHOL, and serum LDL, yet short dialysis vintage, low prevalence of anemia, low levels of serum ferritin, serum iron, and TSAT. Following adjustment for confounding factors, we found that low blood Mn level was independently associated with lower Hb level and anemia in patients undergoing MHD by multivariate linear and multivariate binary logistic regression, respectively, in different models. CONCLUSION: Whilst our study showed that high levels of blood Mn were independently associated with high hemoglobin in patients undergoing MHD, further multicenter studies with large sample sizes are still required.

Efficacy and safety of hypoglycemic agents on gestational diabetes mellitus in women: A Bayesian network analysis of randomized controlled trials.

Objective: To compare the efficacy and safety of metformin, glyburide, and insulin for GDM, we conducted a subgroup analysis of outcomes for women with GDM according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) diagnostic criteria. Methods: We searched the NCBI, Embase, and Web of Science databases from inception to March 2022. Randomized controlled trials (RCTs) that compared the outcomes of hypoglycemic agents in women with GDM were included. Bayesian network analysis was employed. Results: A total of 29 RCTs were included. Metformin was estimated to lead to a slight improvement in total gestational weight gain (WMD - 1.24 kg, 95% CI -2.38, -0.09), a risk of unmet treatment target in the sensitivity analysis (OR 34.50, 95% CI 1.18-791.37) than insulin. The estimated effect of metformin showed improvements in birth weight than insulin (WMD - 102.58 g, 95% CI -180.45 to -25.49) and glyburide (WMD - 137.84 g, 95% CI -255.31 to -25.45), for hypoglycemia within 1 h of birth than insulin (OR 0.65, 95% CI 0.47 to 0.84). The improvement in the estimated effect of metformin for hypoglycemia within 1 h of birth still existed when compared with glyburide (OR 0.41, 95% CI 0.26 to 0.66), whether in the IADPSG group (OR 0.33, 95% CI 0.12 to 0.92) or not (OR 0.43, 95% CI 0.20 to 0.98). Conclusion: Metformin is beneficial for GDM women to control total GWG compared with insulin, regulate fetal birth weight more than insulin and glyburide, and increase the risk of unmet treatment targets compared with insulin. Compared to metformin, glyburide is associated with neonatal hypoglycemia.

Development and Validation of Risk Prediction Models for Gestational Diabetes Mellitus Using Four Different Methods.

Gestational diabetes mellitus (GDM), a common perinatal disease, is related to increased risks of maternal and neonatal adverse perinatal outcomes. We aimed to establish GDM risk prediction models that can be widely used in the first trimester using four different methods, including a score-scaled model derived from a meta-analysis using 42 studies, a logistic regression model, and two machine learning models (decision tree and random forest algorithms). The score-scaled model (seven variables) was established via a meta-analysis and a stratified cohort of 1075 Chinese pregnant women from the Northwest Women's and Children's Hospital (NWCH) and showed an area under the curve (AUC) of 0.772. The logistic regression model (seven variables) was established and validated using the above cohort and showed AUCs of 0.799 and 0.834 for the training and validation sets, respectively. Another two models were established using the decision tree (DT) and random forest (RF) algorithms and showed corresponding AUCs of 0.825 and 0.823 for the training set, and 0.816 and 0.827 for the validation set. The validation of the developed models suggested good performance in a cohort derived from another period. The score-scaled GDM prediction model, the logistic regression GDM prediction model, and the two machine learning GDM prediction models could be employed to identify pregnant women with a high risk of GDM using common clinical indicators, and interventions can be sought promptly.