Convenient Preparation of N-Acylbenzoxazines from Phenols, Nitriles, and DMSO Initiated by a Catalytic Amount of (COCl)2.

A convenient preparation method of N-acylbenzoxazines has been developed, in which phenols react with nitriles and dimethyl sulfoxide (DMSO) in the presence of a catalytic amount of (COCl)2 in CH3CN or chloroform to afford the corresponding N-acylbenzoxazines in moderate-to-good yields. DMSO acts as a source of HCHO, which is generated in situ from the decomposition of a methoxydimethylsulfonium salt. A regeneration cycle of the methoxydimethylsulfonium salt is proposed, which is initiated by a catalytic amount of (COCl)2.

Development of a sensitive and quantitative method for the identification of two major furan fatty acids in human plasma.

This article focuses on the establishment of an accurate and sensitive quantitation method for the analysis of furan fatty acids. In particular, the sensitivity of GC/MS and UPLC/ESI/MS/MS was compared for the identification and quantification of furan fatty acids. Different methylation methods were tested with respect to GC/MS analysis. Special attention needs to be paid to the methylation of furan fatty acids, as acidic catalysts might lead to the degradation of the furan ring. GC/MS analysis in full-scan mode demonstrated that the limit of quantitation was 10 µM. UPLC/ESI/MS/MS in multiple reaction monitoring mode displayed a higher detection sensitivity than GC/MS. Moreover, the identification of furan fatty acids with charge-reversal derivatization was tested in the positive mode with two widely used pyridinium salts. Significant oxidation was unexpectedly observed using N-(4-aminomethylphenyl) pyridinium as a derivatization agent. The formed 3-acyl-oxymethyl-1-methylpyridinium iodide derivatized by 2-bromo-1-methylpyridinium iodide and 3-carbinol-1-methylpyridinium iodide improved the sensitivity more than 2,000-fold compared with nonderivatization in the negative mode by UPLC/ESI/MS/MS. This charge-reversal derivatization enabled the targeted quantitation of furan fatty acids in human plasma. Thus, it is anticipated that this protocol could greatly contribute to the clarification of pathological mechanisms related to furan fatty acids and their metabolites.

Synthesis of Nitriles from Primary Amides or Aldoximes under Conditions of a Catalytic Swern Oxidation.

The preparation of nitriles from primary amides or aldoximes was achieved by using oxalyl chloride with a catalytic amount of dimethyl sulfoxide in the presence of Et3N. The reactions were complete within 1 h after addition at room temperature. A diverse range of cyano compounds were obtained in good to excellent yields, including aromatic, heteroaromatic, cyclic, and acyclic aliphatic species.

Residue and Dietary Risk Assessment of Chiral Cyflumetofen in Apple.

Ultra-performance convergence chromatography is an environmentally-friendly analytical method that uses dramatically reduced amounts of organic solvents. In addition, a robust and highly sensitive chiral separation method was developed for the novel chiral acaricide cyflumetofen by using ultra-performance convergence chromatography coupled with tandem mass spectrometry, which shows that stereoisomer recoveries determined for various apple parts ranged from 78.3% to 119.9%, with the relative standard deviations being lower than 14.0%. The half-lives of (−)-cyflumetofen and (+)-cyflumetofen obtained under 5-fold applied dosage equal to 22.13 and 22.23 days, respectively. For 1.5-fold applied dosage, the respective values were determined as 22.42 and 23.64 days, i.e., the degradation of (−)-cyflumetofen was insignificantly favored over that of its enantiomer. Importantly, cyflumetofen was unevenly distributed in apples, with its relative contents in apple peel, peduncle, and pomace equal to 50%, 22%, and 16%, respectively. The proposed method can be used to efficiently separate and quantify chiral pesticide with advantages of a shorter analysis time, greater sensitivity, and better environmental compatibility. Additionally, the consumption of apples with residue of cyflumetofen did not pose a health risk to the population if the cyflumetofen applied under satisfactory agricultural practices after the long-term dietary risk assessment.

Functionalization of N-arylglycine esters: electrocatalytic access to C-C bonds mediated by n-Bu4NI.

An efficient electrocatalytic functionalization of N-arylglycine esters is reported. The protocol proceeds in an undivided cell under constant current conditions employing the simple, cheap and readily available n-Bu4NI as the mediator. In addition, it is demonstrated that the mediated process is superior to the direct electrochemical functionalization.

[Prediction of drug-target interaction based on fingerprint similarity].

Drugs play the pharmacological effects by combining with target proteins. Identification of drug-target interactions is important for discovering new functions of drugs. In this paper, the target fingerprints based on molecular substructure and the drug-target similarity based on fingerprints are proposed to a random forest-based classification method, in order to identify the drug-target interactions. Experiments on enzymes, ion channels, G protein-coupled receptors and nuclear receptors proved the effectiveness of the proposed method. In addition, the proposed method is applied to predict the interactions between ingredients and targets of traditional Chinese medicines.

Shared Manifold Regularized Joint Feature Selection for Joint Classification and Regression in Alzheimer's Disease Diagnosis.

In Alzheimer's disease (AD) diagnosis, joint feature selection for predicting disease labels (classification) and estimating cognitive scores (regression) with neuroimaging data has received increasing attention. In this paper, we propose a model named Shared Manifold regularized Joint Feature Selection (SMJFS) that performs classification and regression in a unified framework for AD diagnosis. For classification, unlike the existing works that build least squares regression models which are insufficient in the ability of extracting discriminative information for classification, we design an objective function that integrates linear discriminant analysis and subspace sparsity regularization for acquiring an informative feature subset. Furthermore, the local data relationships are learned according to the samples' transformed distances to exploit the local data structure adaptively. For regression, in contrast to previous works that overlook the correlations among cognitive scores, we learn a latent score space to capture the correlations and employ the latent space to design a regression model with l2,1 -norm regularization, facilitating the feature selection in regression task. Moreover, the missing cognitive scores can be recovered in the latent space for increasing the number of available training samples. Meanwhile, to capture the correlations between the two tasks and describe the local relationships between samples, we construct an adaptive shared graph to guide the subspace learning in classification and the latent cognitive score learning in regression simultaneously. An efficient iterative optimization algorithm is proposed to solve the optimization problem. Extensive experiments on three datasets validate the discriminability of the features selected by SMJFS.

Enhanced Multimodal Low-rank Embedding based Feature Selection Model for Multimodal Alzheimer's Disease Diagnosis.

Identification of Alzheimer's disease (AD) with multimodal neuroimaging data has been receiving increasing attention. However, the presence of numerous redundant features and corrupted neuroimages within multimodal datasets poses significant challenges for existing methods. In this paper, we propose a feature selection method named Enhanced Multimodal Low-rank Embedding (EMLE) for multimodal AD diagnosis. Unlike previous methods utilizing convex relaxations of the ℓ2,0-norm, EMLE exploits an ℓ2,γ-norm regularized projection matrix to obtain an embedding representation and select informative features jointly for each modality. The ℓ2,γ-norm, employing an upper-bounded nonconvex Minimax Concave Penalty (MCP) function to characterize sparsity, offers a superior approximation for the ℓ2,0-norm compared to other convex relaxations. Next, a similarity graph is learned based on the self-expressiveness property to increase the robustness to corrupted data. As the approximation coefficient vectors of samples from the same class should be highly correlated, an MCP function introduced norm, i.e., matrix γ-norm, is applied to constrain the rank of the graph. Furthermore, recognizing that diverse modalities should share an underlying structure related to AD, we establish a consensus graph for all modalities to unveil intrinsic structures across multiple modalities. Finally, we fuse the embedding representations of all modalities into the label space to incorporate supervisory information. The results of extensive experiments on the Alzheimer's Disease Neuroimaging Initiative datasets verify the discriminability of the features selected by EMLE.

[Treatment of acute non-displaced scaphoid fracture of wrist with syringe needle-guided percutaneous cannulated headless hollow compression screw internal fixation].

OBJECTIVE: To investigate the clinical efficacy of needle-guided percutaneous cannulated compression screw fixation in the treatment of acute non-displaced scaphoid fracture of wrist. METHODS: The clinic data of twenty-eight patients with acute non-displaced scaphoid fracture from January 2014 to January 2019 were analyzed retrospectively. According to the intraoperative method of placement of cannulated screw, they were divided into Guide group(16 patients)and Conventional group(12 patients). There were 13 males and 3 females in Guide group, aged from 20 to 60 years old with an average of(31.42±9.71)years old;5 patients were classified as type A2, 3 patients were classified as type B1 and 8 patients were classified as type B2 according to Herbert classification;they were treated with percutaneous cannulated compression screw fixation under the guidance of needle. There were 11 males and 1 female in Conventional group, aged from 23 to 61 years old with an average of(30.51±7.52)years old;5 patients were classified as type A2, 2 patients were classified as type B1 and 5 patients were classified as type B2 according to Herbert classification;they were treated with conventional percutaneous cannulated compression screw fixation. The operation time, screw angle relative to the longitudinal axis of the scaphoid and wrist function score were assessed and compared between the two groups. RESULTS: A total of 28 patients were followed up from 20 to 45 months with an average of (33.00±8.72) months. None of patients had intraoperative complication and incision infection. These patients returned to work gradually 2 weeks after operation, and all fractures healed within 12 weeks. The operation time in the Guide group was significantly less than that in the Conventinal group(P<0.05). Screw angle relative to the longitudinal axis of the scaphoid in the Guide group was significantly smaller than that in the Conventional group(P<0.05). There was no significant difference in Mayo wrist function scores at the last follow-up between the two groups(P>0.05). During the follow-up period, none of the 28 patients showed internal fixation displacement, arthritis, scaphoid necrosis and other complications. CONCLUSION: In the treatment of acute non-displaced scaphoid fractures, the operation time of needle-guided percutaneous cannulated headless compression screw fixation is significantly shorter than that of conventional percutaneous screw fixation, and the screw axis is easier to be parallel to the longitudinal axis of the scaphoid.

Orthogonal latent space learning with feature weighting and graph learning for multimodal Alzheimer's disease diagnosis.

Recent studies have shown that multimodal neuroimaging data provide complementary information of the brain and latent space-based methods have achieved promising results in fusing multimodal data for Alzheimer's disease (AD) diagnosis. However, most existing methods treat all features equally and adopt nonorthogonal projections to learn the latent space, which cannot retain enough discriminative information in the latent space. Besides, they usually preserve the relationships among subjects in the latent space based on the similarity graph constructed on original features for performance boosting. However, the noises and redundant features significantly corrupt the graph. To address these limitations, we propose an Orthogonal Latent space learning with Feature weighting and Graph learning (OLFG) model for multimodal AD diagnosis. Specifically, we map multiple modalities into a common latent space by orthogonal constrained projection to capture the discriminative information for AD diagnosis. Then, a feature weighting matrix is utilized to sort the importance of features in AD diagnosis adaptively. Besides, we devise a regularization term with learned graph to preserve the local structure of the data in the latent space and integrate the graph construction into the learning processing for accurately encoding the relationships among samples. Instead of constructing a similarity graph for each modality, we learn a joint graph for multiple modalities to capture the correlations among modalities. Finally, the representations in the latent space are projected into the target space to perform AD diagnosis. An alternating optimization algorithm with proved convergence is developed to solve the optimization objective. Extensive experimental results show the effectiveness of the proposed method.

Clinical evaluation of total hip arthroplasty for osteoarthropathy secondary to septic hip arthritis.

To investigate the clinical efficacy and prognosis of total hip arthroplasty (THA) in patients with osteoarthropathy secondary to septic hip arthritis. A total of 100 patients with osteoarthropathy secondary to septic hip arthritis who underwent surgery in our hospital from December 2010 to December 2021 were selected. Operative data were summarized. Moreover, preoperative and postoperative differences in Harris score, Western Ontario and McMaster Universities Osteoarthritis Index score, Visual Analogue Scale score, hip mobility were compared. Due to hospital transfer, the epidemic of COVID-2019 and other reasons, 10 patients were lost to follow-up and finally 90 patients were recorded. According to the results, the mean operation time (OT) was 1.78 ± 0.32 (hour), the mean intraoperative blood loss (BL) was 586.62 ± 31.66 (mL), the mean red blood cell (RBC) transfusion was 3.84 ± 0.75 (U), and 2 cases were positive, and 88 cases were negative for Trendelenburg sign. Postoperatively, the unequal length of the lower limbs and the Visual Analogue Scale score were significantly lower than that of the preoperative, while the Western Ontario and McMaster Universities Osteoarthritis Index score, Harris score, and hip joint range of motion were significantly higher than those of the preoperative (P < .05). At the last follow-up, all the incisions healed with no deep infections, 1 case suffered from transient sciatic nerve palsy, 2 cases had intermuscular venous thrombosis, and 2 cases who occurred hip dislocation recovered after treatment. THA surgery for osteoarthropathy secondary to septic hip arthritis has a good effect, relieving the patient's pain effectively, improving prognosis and joint mobility. For osteoarthropathy secondary to septic hip arthritis, THA may be meaningful in terms of prognosis.

MTMG: A multi-task model with multi-granularity information for drug-drug interaction extraction.

Drug-drug interactions (DDIs) extraction includes identifying drug entities and interactions between drug pairs from the biomedical corpus. The discovery of potential DDIs aids in our understanding of the mechanisms underlying adverse reactions or combination therapy to improve patient safety. The manual extraction of DDIs is very time-consuming and expensive; therefore, computer-aided extraction of DDIs is vital. Many neural network-based methods have been proposed and achieved good efficiency in the extraction of DDIs over the years. However, most studies improved the performance of DDIs extraction with various external drug features while directly using golden drug entities, leading to error propagation and low universality in practical application. In this paper, we propose a new multi-task framework called MTMG, which changes DDIs extraction from a sentence-level classification task to a sequence labeling task named Drug-Specified Token Classification (DSTC). The proposed approach, MTMG, jointly trains DSTC with drug named entity recognition (DNER) and two sentence-level auxiliary tasks we designed. We aim to improve the performance of the entire DDIs extraction pipeline by better using the correlation between entities and relationships and, to the extent possible, using the information of varying granularity implied in the dataset. Experimental results show that MTMG can both improve the accuracy of DNER and DDIs extraction and outperforms state-of-the-art technique.

Improved stability of ß-carotene by encapsulation in SHMP-corn starch aerogels.

This study aimed to prepare a starch-based aerogel with microporous network structure, and to investigate its physicochemical properties after ß-carotene encapsulation. Corn starch aerogels (CSA) prepared with sodium hexametaphosphate (SHMP) as a cross-linking agent and ß-carotene encapsulation were evaluated in terms of morphology, long- and short-range molecular order, bioavailability, and stability. After encapsulating ß-carotene, the morphology of SHMP-CSA showed that the aerogels presented agglomeration, and the relative crystallinity increased from 17.2% to 22.2%. The characteristic bands of ß-carotene were not found in the FT-IR pattern, and the short-range molecular order of aerogel was decreased, proving that ß-carotene was well embedded in the aerogel. During the simulated in vitro release process, ß-carotene was almost completely released. After ultraviolet or light irradiation, the retention rate of ß-carotene was much higher than that in the control group. These results demonstrated that SHMP-CSA encapsulation could effectively improve the stability of ß-carotene.

Identification of bHLH family genes in Agaricus bisporus and transcriptional regulation of arginine catabolism-related genes by AbbHLH1 after harvest.

Basic helix-loop-helix (bHLH) transcription factors (TFs) are widely distributed in eukaryotes and play an important role in biological growth and development. The identification and functional analyses of bHLH genes/proteins in edible mushrooms (Agaricus bisporus) have yet to be reported. In the present study, we identified 10 putative bHLH members carrying the conserved bHLH domains. Phylogenetic analyses revealed that the 10 AbbHLHs were the closest to sequences of species belonging to 7 different fungal subgroups, which was supported by loop length, intron patterns, and key amino acid residues. The substantial increase after harvest and continuously elevated expression of AbbHLH1 during the development until the disruption of mushroom velum, and the preferential expression in cap and gill tissues suggest the important function of AbbHLH1 in postharvest development of A. bisporus. The relationship of arginine catabolism-related genes with the early stage of postharvest continuing development also was revealed by expression determination. Subcellular localization showed that AbbHLH1 could be localized in nucleus. Importantly, the electrophoretic mobility shift and dual-luciferase reporter assays showed that AbbHLH1 activated the promoters of AbOAT, AbSPDS, and AbSAMDC and suppressed the expression of AbARG, AbUREA, and AbODC, probably for the modulation of arginine catabolism and thus control of postharvest mushroom development. Taken together, the available data provide valuable functional insight into the role of AbbHLH proteins in postharvest mushrooms.

[Application of intermittent flap opening in L-shaped surgical incision of calcaneal fracture].

OBJECTIVE: To explore clinical effect of intermittent flap opening technique in L-shaped incision of calcaneal fracture. METHODS: From January 2017 to January 2019, 48 patients with Sanders typeⅡ to Ⅳ calcaneal fractures were treated by open reduction and internal fixation. According to different flap opening techniques, the patients were divided into control group and observation group, 24 patients in each group. In observation group, there were 17 males and 7 females, aged from 20 to 60 years old with an average of(45.12±9.56) years old;7 patients were typeⅡ, 10 patients were type Ⅲ and 7 patients were type Ⅳ according to Sanders classification;3 patients were C0, 16 patients were C1 and 5 patients were C2 according to Tscherne-Gotzen soft-tissue assessment;treated with intermittent flap technique. In control group, there were 19 males and 5 females aged from 20 to 60 years old with an average of (47.32±10.67) years old;7 patients were typeⅡ, 11 patients were type Ⅲ and 6 patients were type Ⅳ according to Sanders classification;2 patients were C0, 18 patients were C1 and 4 patients were C2 according to Tschemc-Gotzen soft-tissue assessment;treated with static flap opening technique. Operation time, flap retraction time, changes of Böhler angle and Gissane angle before and after operation at 3 days, and occurrence of incision complications were observed and compared between two groups. RESULTS: All patients were followed up from 3 to 6 months with an average of(4.52±1.01) months. There were no significant differences in operation time, changes of Böhler angle and Gissane angle before and after operation at 3 days between the two groups(P>0.05);there was statistical difference in flap retraction time between two groups(P<0.05). Occurrence of incision complications in observation group was significantly lower than that in control group (P<0.05). CONCLUSION: Intermittent flap opening technique is superior to static opening technique in reducing incision complications of lateral "L" approach of calcaneus. Single Kirschner wire opening does not affect the exposure, reduction and fixation of fracture during operation.

Effects of Tai Chi Chuan on Cognitive Function in Adults 60 Years or Older With Type 2 Diabetes and Mild Cognitive Impairment in China: A Randomized Clinical Trial.

Importance: Type 2 diabetes (T2D) is associated with the progression of cognitive dysfunction. Physical activity benefits cognition, but no evidence from randomized clinical trials has shown whether tai chi chuan has better long-term benefits than fitness walking in cognitive function for patients with T2D and mild cognitive impairment (MCI). Objective: To compare the effectiveness of tai chi chuan, a mind-body exercise, for improving cognitive function in older adults with T2D and MCI, with fitness walking. Design, Setting, and Participants: This randomized clinical trial was conducted between June 1, 2020, and February 28, 2022, at 4 sites in China. Participants included 328 adults (aged ≥60 years) with a clinical diagnosis of T2D and MCI. Interventions: Participants were randomized in a 1:1:1 ratio to a tai chi chuan group, a fitness walking group, or a control group. The tai chi chuan group received 24-form simplified tai chi chuan. The fitness walking group received fitness walking training. Both exercise groups took the training for 60 min/session, 3 times/wk, for 24 weeks in a supervised setting. All 3 groups were provided with a 30-minute diabetes self-management education session, once every 4 weeks for 24 weeks. The participants were followed up for 36 weeks. Main Outcomes and Measures: The primary outcome was the global cognitive function measured at 36 weeks by the Montreal Cognitive Assessment (MoCA). Secondary outcomes included MoCA at 24 weeks and other cognitive subdomain measures and blood metabolic indices at 24 and 36 weeks. Results: A total of 328 participants (mean [SD] age, 67.55 [5.02] years; mean [SD] T2D duration, 10.48 [6.81] years; 167 [50.9%] women) were randomized to the tai chi chuan group (n = 107), fitness walking group (n = 110), or control group (n = 111) and included in the intention-to-treat analysis. At 36 weeks, the tai chi chuan group showed improved MoCA scores compared with the fitness walking group (mean [SD], 24.67 [2.72] vs 23.84 [3.17]; between-group mean difference, 0.84 [95% CI, 0.02-1.66]; P = .046) in the intention-to-treat analysis. The per-protocol analysis data set and subgroup analysis at 36 weeks showed similar results. Based on the generalized linear models, the treatment effects were similar in each group after adjusting for self-reported dietary calories and physical activity. There were 37 nonserious adverse events (tai chi chuan group, 8; fitness walking group, 13; control group, 16) unrelated to the study with no statistically significant difference among the 3 groups (P = .26). Conclusions and Relevance: In this randomized clinical trial including older adults with T2D and MCI, tai chi chuan was more effective than fitness walking in improving global cognitive function. The findings support a long-term benefit, suggesting the potential clinical use of tai chi chuan as an exercise intervention to improve cognitive function for older adults with T2D and MCI. Trial Registration: ClinicalTrials.gov Identifier: NCT04416841.

Predicting in-hospital outcomes of patients with acute kidney injury.

Acute kidney injury (AKI) is prevalent and a leading cause of in-hospital death worldwide. Early prediction of AKI-related clinical events and timely intervention for high-risk patients could improve outcomes. We develop a deep learning model based on a nationwide multicenter cooperative network across China that includes 7,084,339 hospitalized patients, to dynamically predict the risk of in-hospital death (primary outcome) and dialysis (secondary outcome) for patients who developed AKI during hospitalization. A total of 137,084 eligible patients with AKI constitute the analysis set. In the derivation cohort, the area under the receiver operator curve (AUROC) for 24-h, 48-h, 72-h, and 7-day death are 95·05%, 94·23%, 93·53%, and 93·09%, respectively. For dialysis outcome, the AUROC of each time span are 88·32%, 83·31%, 83·20%, and 77·99%, respectively. The predictive performance is consistent in both internal and external validation cohorts. The model can predict important outcomes of patients with AKI, which could be helpful for the early management of AKI.

The influence of a single water molecule on the reaction of BrO + HONO.

Quantum chemical computations and transition state theory are employed to systematically research the influence of a single molecule water on the BrO + HONO reaction. Two distinct reactions, namely BrO + trans-HONO and BrO + cis-HONO are explored for the reaction in the absence of water, which is mainly decided by the configuration of HONO. With introduction a single water molecule to the reaction, the rate coefficient of the channel starting from BrO + cis-HONO and BrO + trans-HONO are 2.43 × 10-19 and 5.22 × 10-22 cm3 molecule-1 s-1, which is larger than the reaction in the absence of water. For further comprehend the impact of water on the BrO + HONO reaction, it is necessary to compute the effective rate coefficient by taking into account the concentration of water. The water-assisted effective rate coefficients for the BrO + HONO reaction are smaller than that the reaction in the absence of water. The reaction of BrO with cis-HONO is feasible both in absence and existence of water.

Multi-Attribute Discriminative Representation Learning for Prediction of Adverse Drug-Drug Interaction.

Adverse drug-drug interaction (ADDI) is a significant life-threatening issue, posing a leading cause of hospitalizations and deaths in healthcare systems. This paper proposes a unified Multi-Attribute Discriminative Representation Learning (MADRL) model for ADDI prediction. Unlike the existing works that equally treat features of each attribute without discrimination and do not consider the underlying relationship among drugs, we first develop a regularized optimization problem based on CUR matrix decomposition for joint representative drug and discriminative feature selection such that the selected drugs and features can well approximate the original feature spaces and the critical factors discriminative to ADDIs can be properly explored. Different from the existing models that ignore the consistent and unique properties among attributes, a Generative Adversarial Network (GAN) framework is then designed to capture the inter-attribute shared and intra-attribute specific representations of adverse drug pairs for exploiting their consensus and complementary information in ADDI prediction. Meanwhile, MADRL is compatible with any kind of attributes and capable of exploring their respective effects on ADDI prediction. An iterative algorithm based on the alternating direction method of multipliers is developed for optimization. Experiments on publicly available dataset demonstrate the effectiveness of MADRL when compared with eleven baselines and its six variants.

The influence of (H2O)1-2 in the HOBr + HO2 gas-phase reaction.

The HOBr + HO2 reaction in the absence of water has three different channels for the abstraction of H to generate the corresponding products. The dominant channel is the generation of BrO + H2O2. The introduction of water molecules influences this dominant reaction via the way the reactants interact with the water molecules. The addition of water molecules decreases the energy barrier and increases the rate coefficient of the reaction. Interestingly, water works as a catalyst and we obtain BrO + H2O2, like in the reaction without water, or the water works as a reactant and we obtain products other than BrO + H2O2. The rate coefficients of the HOBr + HO2 reaction in the presence of water are calculated to be faster than the reaction in the absence of water. However, other pathways in the presence of water are slower than the reaction in the absence of water. The water-assisted effective rate coefficients for the HOBr + HO2 reaction are also larger than those for the reaction in the absence of water. The influence of a water dimer is not as important when compared with one water molecule. In summary, a single water molecule has a positive catalytic influence in enhancing the HOBr + HO2 reaction.