Non-linear relationship between TyG index and the risk of prediabetes in young people: a 5-year retrospective cohort study in Chinese young adults.

Objective: Given the limited evidence on the relationship between the triglyceride-glucose (TyG) index and the risk of prediabetes among young adults, our study aimed to investigate the potential impact of the TyG index on the future development of prediabetes in young individuals. Methods: This retrospective cohort study included 125,327 healthy adults aged 20 to 45 years. We utilized Cox proportional hazards regression models, combined with cubic spline functions and smooth curve fitting, to assess the relationship between baseline TyG index and the risk of prediabetes among young adults, exploring its non-linear association. A series of sensitivity analyses and subgroup analyses were conducted to ensure the robustness of our findings. Results: After adjusting for covariates, the study found a positive correlation between the TyG index and the risk of prediabetes (HR=1.81, 95%CI: 1.54-2.13, p<0.0001). The risk of prediabetes increased progressively across quartiles of the TyG index (Q1 to Q4), with Q4 showing a significantly higher risk compared to Q1 (adjusted HR=2.33, 95% CI=1.72-3.16). Moreover, a non-linear relationship was identified between the TyG index and the risk of prediabetes, with an inflection point at 9.39. To the left of the inflection point, the HR was 2.04 (95% CI: 1.69 to 2.46), while to the right, the HR was 0.89 (95% CI: 0.48 to 1.65). Conclusion: Our study reveals a non-linear relationship and a saturation effect between the TyG index and the development of prediabetes among young individuals in China, with an inflection point at 9.39. Understanding this non-linear relationship can assist clinicians in identifying young individuals at high risk and implementing targeted interventions to reduce their risk of progressing to diabetes.

Biomimetic multi-channel nerve conduits with micro/nanostructures for rapid nerve repair.

Peripheral nervous system (PNS) injuries often lead to significant sensory and motor impairments. Traditional artificial nerve conduits, lacking anisotropic structures, have been associated with prolonged repair time and failures in nerve regeneration. This study aimed to address these challenges by developing a novel approach for rapid repair of peripheral nerve injuries (PNI). A 3D oriented fibers scaffold featuring distinct radial (RFs) and longitudinal (LFs) fibers orientations was engineered using coaxial electrospinning and gas directional foaming techniques. This scaffold was then integrated with a shape memory conduit to form a directional multi-channel nerve conduit with micro/nanostructures. The results revealed that the grooved surface of the fibers significantly improved cellular directional guidance, effectively facilitating the migration of SCs from the periphery towards the center and from the base to the apex of the scaffold. In a rat model with a 10 mm nerve defect, the ND-PLATMC/LF ND-PCL scaffold significantly enhanced nerve regeneration and motor function recovery within 4 weeks. These results suggest the potential of this innovative scaffold for efficient repair of the nerve injuries.

Protonated-chitosan sponge with procoagulation activity for hemostasis in coagulopathy.

Hemostatic materials are essential for managing acute bleeding in medical settings. Chitosan (CS) shows promise in hemostasis but its underlying mechanism remains incompletely understood. We unexpectedly discovered that certain protonated-chitosan (PCS) rapidly assembled plasma proteins to form protein membrane (PM) upon contact with platelet-poor plasma (PPP). We hypothesized that the novel observation was intricately related to the procoagulant effect of chitosan. Herein, the study aimed to elucidate the conditions necessary and mechanism for PM formation, identify the proteins within the PM and PCS's procoagulant action at the molecule levels. We confirmed that the amount of -NH3 + groups (>4.9 mmol/g) on PCS molecules played a crucial role in promoting coagulation. The -NH3 + group interacted with blood's multiple active components to exert hemostatic effects: assembling plasma proteins including coagulation factors such as FII, FV, FX, activating blood cells and promoting the secretion of coagulation-related substances (FV, ADP, etc) by platelets. Notably, the hemostatic mechanism can be extended to protonated-chitosan derivatives like quaternized, alkylated, and catechol-chitosan. In the blood clotting index (BCI) experiment, compared to other groups, PCS95 achieved the lowest BCI value (∼6 %) within 30 s. Protonated-chitosan exhibited excellent biocompatibility and antibacterial properties, with PCS95 demonstrating inhibition effectiveness of over 95 % against Escherichia coli (E.coil) and Staphylococcus aureus (S. aureus). Moreover, PCS performed enhanced hemostatic effectiveness over chitosan-based commercially agents (Celox™ and ChitoGauze®XR) in diverse bleeding models. In particular, PCS95 reduced bleeding time by 70 % in rabbit models of coagulopathy. Overall, this study investigated the coagulation mechanism of materials at the molecular level, paving the way for innovative approaches in designing new hemostatic materials.

A Case of Pernicious Anemia with Concurrent Beta-Thalassemia Minor.

Vitamin B12 is essential for various bodily functions, and its deficiency may cause hematological manifestations. We report a case of a previously healthy 65-year-old female who was admitted to our hospital with reduced sense of taste and painful tongue. The serum level of vitamin B12 was decreased. However, her complete blood count did not show any evidence of macrocytosis, instead, her mean corpuscular volume was low. Gene sequencing indicated an ß-thalassemia minor and that probably masked the megaloblastic features of vitamin B12 deficiency.

Calcium Ion-Coupled Polyphosphates with Different Degrees of Polymerization for Bleeding Control.

The development of efficient hemostatic materials is crucial for achieving rapid hemorrhage control and effective wound healing. Inorganic polyphosphate (polyP) is recognized as an effective modulator of the blood coagulation process. However, the specific effect of polyP chain length on coagulation is not yet fully understood. Furthermore, calcium ions (Ca2+) are essential for the coagulation process, promoting multiple enzyme-catalyzed reactions within the coagulation cascade. Hence, calcium ion-coupled polyphosphate powders with three different degrees of polymerization (CaPP-n, n = 20, 50, and 1500) are synthesized by an ion-exchange reaction. CaPP exhibits a crystalline phase at a low polymerization degree and transitions to an amorphous phase as the polymerization degree increases. Notably, the addition of Ca2+ enhances the wettability of polyP, and CaPP promotes hemostasis, with varying degrees of effectiveness related to chain length. CaPP-50 exhibits the most promising hemostatic performance, with the lowest blood clotting index (BCI, 12.1 ± 0.7%) and the shortest clotting time (302.0 ± 10.5 s). By combining Ca2+ with polyP of medium-chain length, CaPP-50 demonstrates an enhanced ability to accelerate the adhesion and activation of blood cells, initiate the intrinsic coagulation cascade, and form a stable blood clot, outperforming both CaPP-20 and CaPP-1500. The hemostatic efficacy of CaPP-50 is further validated using rat liver bleeding and femoral artery puncture models. CaPP-50 is proven to possess hemostatic properties comparable to those of commercial calcium-based zeolite hemostatic powder and superior to kaolin. In addition, CaPP-50 exhibits excellent biocompatibility and long-term storage stability. These results suggest that CaPP-50 has significant clinical and commercial potential as an active inorganic hemostatic agent for rapid control of bleeding.

Elevated triglyceride-glucose index associated with increased risk of diabetes in non-obese young adults: a longitudinal retrospective cohort study from multiple Asian countries.

Objective: Previous studies have confirmed a positive correlation between the Triglyceride-Glucose (TyG) index and future risk of diabetes. However, evidence of this association in non-obese young populations remains limited. This study aims to investigate the relationship between the TyG index and the future risk of diabetes among non-obese young adults. Methods: This retrospective cohort study included 113,509 non-obese young adults from China and 9,549 from Japan. The mean age was 35.73 ± 6.38 years, and 56,469 participants (45.89%) were male. The median follow-up duration was 3.38 years. The association between baseline TyG index and risk of diabetes was examined using Cox proportional hazards regression models. Non-linear relationships between the TyG index and risk of diabetes were identified using cubic splines and smoothed curve fitting in the Cox models. Sensitivity and subgroup analyses were also conducted. Results: After adjusting for covariates, the results indicated a positive correlation between the TyG index and risk of diabetes in non-obese young adults (HR=3.57, 95% CI: 2.92-4.36, P<0.0001). A non-linear relationship was observed with an inflection point at 7.3. The HR to the right of this inflection point was 3.70 (95% CI: 3.02-4.52, P<0.0001), while to the left, it was 0.34 (95% CI: 0.06-1.88, P=0.2161). The robustness of our findings was confirmed through a series of sensitivity analyses and subgroup analyses. Conclusion: This study reveals a positive and non-linear association between the TyG index and risk of diabetes among non-obese young adults. Interventions aimed at reducing the TyG index by lowering triglycerides or fasting glucose levels could substantially decrease the future likelihood of developing diabetes in this population.

Non-linear relationship between red blood cell distribution width and gastrointestinal bleeding risk in stroke patients: results from multi-center ICUs.

Background: The red blood cell distribution width (RDW) is closely linked to the prognosis of multiple diseases. However, the connection between RDW and gastrointestinal bleeding (GIB) in stroke patients is not well understood. This study aimed to clarify this association. Methods: This retrospective study involved 11,107 hospitalized patients from 208 hospitals in the United States, admitted between January 1, 2014, and December 31, 2015. We examined clinical data from 7,512 stroke patients in the intensive care unit (ICU). Multivariate logistic regression assessed the link between RDW and in-hospital GIB in stroke patients. Generalized additive model (GAM) and smooth curve fitting (penalty spline method) were utilized to explore the non-linear relationship between RDW and GIB in stroke patients. The inflection point was calculated using a recursive algorithm, and interactions between different variables were assessed through subgroup analyses. Results: Among the 11,107 screened stroke patients, 7,512 were included in the primary analysis, with 190 identified as having GIB. The participants had a mean age of (61.67 ± 12.42) years, and a median RDW of 13.9%. Multiple logistic analysis revealed RDW as a risk factor for in-hospital GIB in stroke patients (OR = 1.28, 95% CI 1.21, 1.36, p < 0.05). The relationship between RDW and in-hospital GIB in stroke patients was found to be non-linear. Additionally, the inflection point of RDW was 14.0%. When RDW was ≥14.0%, there was a positive association with the risk of GIB (OR: 1.24, 95% CI: 1.16, 1.33, p < 0.0001). Conversely, when RDW was <14.0%, this association was not significant (OR: 1.02, 95% CI: 0.97-1.07, p = 0.4040). Conclusion: This study showed a substantial non-linear link between RDW and the risk of GIB in stroke patients. Maintaining the patient's RDW value below 14.0% could lower the risk of in-hospital GIB.

Fine-Grained Learning Behavior-Oriented Knowledge Distillation for Graph Neural Networks.

Knowledge distillation (KD), as an effective compression technology, is used to reduce the resource consumption of graph neural networks (GNNs) and facilitate their deployment on resource-constrained devices. Numerous studies exist on GNN distillation, and however, the impacts of knowledge complexity and differences in learning behavior between teachers and students on distillation efficiency remain underexplored. We propose a KD method for fine-grained learning behavior (FLB), comprising two main components: feature knowledge decoupling (FKD) and teacher learning behavior guidance (TLBG). Specifically, FKD decouples the intermediate-layer features of the student network into two types: teacher-related features (TRFs) and downstream features (DFs), enhancing knowledge comprehension and learning efficiency by guiding the student to simultaneously focus on these features. TLBG maps the teacher model's learning behaviors to provide reliable guidance for correcting deviations in student learning. Extensive experiments across eight datasets and 12 baseline frameworks demonstrate that FLB significantly enhances the performance and robustness of student GNNs within the original framework.

Correction: Establishment of a prediction model for prehospital return of spontaneous circulation in out-of-hospital patients with cardiac arrest.

[This corrects the article on p. 508 in vol. 15, PMID: 37900904.].

A Multi-Level Relation-Aware Transformer model for occluded person re-identification.

Occluded person re-identification (Re-ID) is a challenging task, as pedestrians are often obstructed by various occlusions, such as non-pedestrian objects or non-target pedestrians. Previous methods have heavily relied on auxiliary models to obtain information in unoccluded regions, such as human pose estimation. However, these auxiliary models fall short in accounting for pedestrian occlusions, thereby leading to potential misrepresentations. In addition, some previous works learned feature representations from single images, ignoring the potential relations among samples. To address these issues, this paper introduces a Multi-Level Relation-Aware Transformer (MLRAT) model for occluded person Re-ID. This model mainly encompasses two novel modules: Patch-Level Relation-Aware (PLRA) and Sample-Level Relation-Aware (SLRA). PLRA learns fine-grained local features by modeling the structural relations between key patches, bypassing the dependency on auxiliary models. It adopts a model-free method to select key patches that have high semantic correlation with the final pedestrian representation. In particular, to alleviate the interference of occlusion, PLRA captures the structural relations among key patches via a two-layer Graph Convolution Network (GCN), effectively guiding the local feature fusion and learning. SLRA is designed to facilitate the model to learn discriminative features by modeling the relations among samples. Specifically, to mitigate noisy relations of irrelevant samples, we present a Relation-Aware Transformer (RAT) block to capture the relations among neighbors. Furthermore, to bridge the gap between training and testing phases, a self-distillation method is employed to transfer the sample-level relations captured by SLRA to the backbone. Extensive experiments are conducted on four occluded datasets, two partial datasets and two holistic datasets. The results show that the proposed MLRAT model significantly outperforms existing baselines on four occluded datasets, while maintains top performance on two partial datasets and two holistic datasets.

A combined model of serum neutrophil extracellular traps, CD8+ T cells, and tumor proportion score provides better prediction of PD-1 inhibitor efficacy in patients with NSCLC.

Immune checkpoint inhibitors provide a definite survival benefit for patients with driver-negative advanced non-small cell lung cancer (NSCLC), but predictors of efficacy are still lacking. There may be a relationship between immune inflammatory state and tumor immune response. We explored the relationship of serum neutrophil extracellular traps (NETs) with infiltrating cells in the tumor tissues of patients with NSCLC as well as their relationship with the therapeutic efficacy of programmed cell death protein 1 (PD-1) inhibitors. Serum myeloperoxidase (MPO)-double-stranded DNA (dsDNA) was detected as a marker of NET serum concentration. T cells were detected by immunohistochemical staining, and neutrophils were counted by MPO immunofluorescence staining. Of the 31 patients with NSCLC, a longer progression-free survival after PD-1 inhibitor treatment was associated with higher levels of CD3+ T cells, a lower neutrophil : CD3+-T-cell ratio (NEU/CD3+) and lower neutrophil : CD8+-T-cell ratio (NEU/CD8+) in tumor tissues. Patients with higher serum NETs were more likely to develop progressive disease after treatment (P = 0.003) and to have immune-related adverse events (IrAEs) as well as higher NEU/CD3+ and NEU/CD8+. The combined model of serum NETs, CD8+ T cells, and tumor proportion score (TPS) significantly improved the prediction of PD-1 inhibitor efficacy [P = 0.033; area under the curve (AUC) = 0.881]. Our results indicate that serum NETs are effective predictors of PD-1 inhibitor response and reflect the tissue neutrophil-to-lymphocyte ratio and IrAE levels. The combined model of serum NETs, CD8+ T cells, and TPS is a powerful tool for predicting the efficacy of PD-1 inhibitor treatment in patients with NSCLC.

Efficient dissolution of cellulose in slow-cooling alkaline systems and interacting modes between alkali and urea at the molecular level.

The dissolution of microcrystalline cellulose (MCC) in a urea-NaOH system is beneficial for its mechanical processing. The apparent MCC solubility was greatly improved to 14 wt% under a slow-cooling condition with a cooling rate of -0.3 °C/min. The cooling curve or thermal history played a crucial role in the dissolution process. An exotherm (-54.7 ± 3 J/g MCC) was detected by DSC only under the slow-cooling condition, and the cryogenic dissolution of MCC was attributed to the exothermic interaction between MCC and solvent. More importantly, the low cooling rate promoted the dissolution of MCC by providing enough time for the diffusion of OH- and urea into MCC granules at higher temperatures. The Raman spectral data showed that the intramolecularly and intermolecularly hydrogen bonds in cellulose were cleaved by NaOH and urea, respectively. XPS and solid-state 13C NMR results showed that hydrogen bonds were generated after dissolution, and a dual-hydrogen-bond binding mode between urea and cellulose was confirmed by DFT calculations. Both the decrease of enthalpy and increase of entropy dominated the spontaneity of MCC dissolution, and that is the reason for the indispensability of cryogenic environment. The high apparent solubility of MCC in the slow-cooling process and the dissolution mechanism are beneficial for the studies on cellulose modification and mechanical processing.

Non-linear relationship between pulse pressure and the risk of prediabetes: a 5-year cohort study in Chinese adults.

Previous research has established a strong link between pulse pressure (PP) and diabetes, but there is limited investigation into the connection between PP and prediabetes. This study aims to explore the potential association between PP and prediabetes. A retrospective cohort study encompassed 202,320 Chinese adults who underwent health check-ups between 2010 and 2016. Prediabetes was defined in accordance with the World Health Organization criteria, indicating impaired fasting glucose, with fasting blood glucose levels ranging from 6.1 to 6.9 mmol/L. To assess the PP-prediabetes relationship, we employed Cox regression analysis, sensitivity analysis, and subgroup analysis. Cox proportional hazards regression, coupled with cubic spline functions and smooth curve fitting, helped elucidate the non-linear PP-prediabetes relationship. Upon adjusting for confounding factors, we observed a positive association between PP and prediabetes (HR 1.15, 95% CI 1.11-1.18, P < 0.0001). Participants in the fourth quartile (PP ≥ 51 mmHg) had a 73% higher likelihood of developing prediabetes compared to those in the first quartile (PP < 36 mmHg) (HR 1.73, 95% CI 1.52-1.97, P < 0.0001). Moreover, the relationship between PP and prediabetes was non-linear. A two-piece Cox proportional hazards regression model identified an inflection point at 40 mmHg for PP (P for log-likelihood ratio test = 0.047). Sensitivity and subgroup analyses corroborated the robustness of our findings. Our study reveals a non-linear correlation between PP and prediabetes, signifying an increased risk of prediabetes when PP levels exceed 40 mmHg. This discovery has significant clinical implications for early prediabetes prevention and intervention, ultimately contributing to improved patient outcomes and quality of life.

Elevated platelet count is associated with decreased mortality from hemorrhagic stroke in hospital: a multi-center retrospective cohort study.

This study aimed to investigate the relationship between platelet count (PC) and mortality in patients with hemorrhagic stroke (HS). The research reviewed data from 10,466 patients hospitalized in 208 hospitals in the United States from January 1, 2014, to December 31, 2015. Of these, 3262 HS patients were included in the primary analysis for those admitted to the intensive care unit (ICU). The average age of these patients was 67.05 years, with 52.79% being male. The median PC was (221.67 ± 73.78) × 109/L. Multivariate logistic regression analysis revealed that PC was a protective factor for mortality in HS patients (OR = 0.98, 95% CI 0.97-1.00, P < 0.05). Additionally, a non-linear association between PC and mortality in HS patients was found using a generalized additive model (GAM) and smooth curve fitting (penalty spline method). For the first time, a recursive algorithm identified the inflection point of platelet count as 194 × 109/L. On the left side of the inflection point, for every increase of 10 units in platelet count, the mortality rate of HS patients decreases by 10%. The study demonstrates a non-linear relationship between PC and the risk of mortality in HS patients. A platelet counts higher than the inflection point (194 × 109/L) may be a significant intervention to reduce mortality in HS patients.

Defluorination of perfluorooctanoic acid and perfluorooctane sulfonic acid by heterogeneous catalytic system of Fe-Al2O3/O3: Synergistic oxidation effects and defluorination mechanism.

In this study, catalytic ozonation by Fe-Al2O3 was used to investigate the defluorination of PFOA and PFOS, assessing the effects of different experimental conditions on the defluorination efficiency of the system. The oxidation mechanism of the Fe-Al2O3/O3 system and the specific degradation and defluorination mechanisms for PFOA and PFOS were determined. Results showed that compared to the single O3 system, the defluorination rates of PFOA and PFOS increased by 2.32- and 5.92-fold using the Fe-Al2O3/O3 system under optimal experimental conditions. Mechanistic analysis indicated that in Fe-Al2O3, the variable valence iron (Fe) and functional groups containing C and O served as important reaction sites during the catalytic process. The co-existence of 1O2, OH, O2- and high-valence Fe(IV) constituted a synergistic oxidation system consisting of free radicals and non-radicals, promoting the degradation and defluorination of PFOA and PFOS. DFT theoretical calculations and the analysis of intermediate degradation products suggested that the degradation pathways of PFOA and PFOS involved Kolbe decarboxylation, desulfonation, alcoholization and intramolecular cyclization reactions. The degradation and defluorination pathways of PFOA and PFOS consisted of the stepwise removal of -CF2-, with PFOS exhibiting a higher defluorination rate than PFOA due to its susceptibility to electrophilic attack. This study provides a theoretical basis for the development of heterogeneous catalytic ozonation systems for PFOA and PFOS treatment.

Serum calcium is associated with sudden cardiac arrest in stroke patients from ICU: a multicenter retrospective study based on the eICU collaborative research database.

This primary objective of our study was to investigate the relationship between serum calcium levels and the occurrence of sudden cardiac arrest (SCA) in stroke patients. We analyzed the clinical data of 10,423 acute stroke patients admitted to the intensive care unit. The association between serum calcium and SCA following an acute stroke was assessed through multivariate logistic regression. We explored the non-linear connection between serum calcium levels and SCA in stroke patients using a generalized additive model and smooth curve fitting. Our study uncovered that serum calcium serves as an independent risk factor for sudden cardiac arrest in stroke patients. Notably, we observed that the relationship between serum calcium levels upon admission and the occurrence of SCA in stroke patients within the hospital was non-linear. Furthermore, we identified inflection points in serum calcium levels at 8.2 and 10.4 mg/dL. These findings emphasize a non-linear relationship between serum calcium levels and the risk of SCA in stroke patients. Maintaining serum calcium within the range of 8.2-10.4 mg/dL could lead to a significant reduction in the incidence of cardiac arrest among stroke patients.

Learning From Human Educational Wisdom: A Student-Centered Knowledge Distillation Method.

Existing studies on knowledge distillation typically focus on teacher-centered methods, in which the teacher network is trained according to its own standards before transferring the learned knowledge to a student one. However, due to differences in network structure between the teacher and the student, the knowledge learned by the former may not be desired by the latter. Inspired by human educational wisdom, this paper proposes a Student-Centered Distillation (SCD) method that enables the teacher network to adjust its knowledge transfer according to the student network's needs. We implemented SCD based on various human educational wisdom, e.g., the teacher network identified and learned the knowledge desired by the student network on the validation set, and then transferred it to the latter through the training set. To address the problems of current deficiency knowledge, hard sample learning and knowledge forgetting faced by a student network in the learning process, we introduce and improve Proportional-Integral-Derivative (PID) algorithms from automation fields to make them effective in identifying the current knowledge required by the student network. Furthermore, we propose a curriculum learning-based fuzzy strategy and apply it to the proposed PID control algorithm, such that the student network in SCD can actively pay attention to the learning of challenging samples after with certain knowledge. The overall performance of SCD is verified in multiple tasks by comparing it with state-of-the-art ones. Experimental results show that our student-centered distillation method outperforms existing teacher-centered ones.

Teacher-student complementary sample contrastive distillation.

Knowledge distillation (KD) is a widely adopted model compression technique for improving the performance of compact student models, by utilizing the "dark knowledge" of a large teacher model. However, previous studies have not adequately investigated the effectiveness of supervision from the teacher model, and overconfident predictions in the student model may degrade its performance. In this work, we propose a novel framework, Teacher-Student Complementary Sample Contrastive Distillation (TSCSCD), that alleviate these challenges. TSCSCD consists of three key components: Contrastive Sample Hardness (CSH), Supervision Signal Correction (SSC), and Student Self-Learning (SSL). Specifically, CSH evaluates the teacher's supervision for each sample by comparing the predictions of two compact models, one distilled from the teacher and the other trained from scratch. SSC corrects weak supervision according to CSH, while SSL employs integrated learning among multi-classifiers to regularize overconfident predictions. Extensive experiments on four real-world datasets demonstrate that TSCSCD outperforms recent state-of-the-art knowledge distillation techniques.

Feasibility of low-intensity ultrasound treatment with hydroxylamine to accelerate the initiation of partial nitrification and allow operation under intermittent aeration.

Partial nitrification is a key aspect of efficient nitrogen removal, although practically it suffers from long start-up cycles and unstable long-term operational performance. To address these drawbacks, this study investigated the effect of low intensity ultrasound treatment combined with hydroxylamine (NH2OH) on the performance of partial nitrification. Results show that compared with the control group, low-intensity ultrasound treatment (0.10 W/mL, 15 min) combined with NH2OH (5 mg/L) reduced the time required for partial nitrification initiation by 6 days, increasing the nitrite accumulation rate (NAR) and ammonia nitrogen removal rate (NRR) by 20.4% and 6.7%, respectively, achieving 96.48% NRR. Mechanistic analysis showed that NH2OH enhanced ammonia oxidation, inhibited nitrite-oxidizing bacteria (NOB) activity and shortened the time required for partial nitrification initiation. Furthermore, ultrasonication combined with NH2OH dosing stimulated EPS (extracellular polymeric substances) secretion, increased carbonyl, hydroxyl and amine functional group abundances and enhanced mass transfer. In addition, 16S rRNA gene sequencing results showed that ultrasonication-sensitive Nitrospira disappeared from the ultrasound + NH2OH system, while Nitrosomonas gradually became the dominant group. Collectively, the results of this study provide valuable insight into the enhancement of partial nitrification start-up during the process of wastewater nitrogen removal.

Erratum: CXCL12-mediated monocyte transmigration into brain perivascular space leads to neuroinflammation and memory deficit in neuropathic pain: Erratum.

[This corrects the article DOI: 10.7150/thno.44364.].