Drug repurposing opportunities for chronic kidney disease.

The development of targeted drugs for the early prevention and management of chronic kidney disease (CKD) is of great importance. However, the success rates and cost-effectiveness of traditional drug development approaches are extremely low. Utilizing large sample genome-wide association study data for drug repurposing has shown promise in many diseases but has not yet been explored in CKD. Herein, we investigated actionable druggable targets to improve renal function using large-scale Mendelian randomization and colocalization analyses. We combined two population-scale independent genetic datasets and validated findings with cell-type-dependent eQTL data of kidney tubular and glomerular samples. We ultimately prioritized two drug targets, opioid receptor-like 1 and F12, with potential genetic support for restoring renal function and subsequent treatment of CKD. Our findings explore the potential pathological mechanisms of CKD, bridge the gap between the molecular mechanisms of pathogenesis and clinical intervention, and provide new strategies in future clinical trials of CKD.

An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study.

Background: The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. Methods: In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. Findings: In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64-73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953-0.998) to 0.992 (0.982-1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908-1.000]) surpassed that of two junior pathologists (0.862 [0.746-0.939], P = 0.023; 0.879 [0.767-0.950], P = 0.041) by 10-12% and showed no difference to that of two senior pathologists (both 0.983 [0.908-1.000], both P > 0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P = 0.041) to the level of senior pathologists (both P > 0.99), and substantially reduced the four pathologists' slide reviewing time (-31%, P < 0.0001; -34%, P < 0.0001; -29%, P < 0.0001; and -27%, P = 0.00031). Interpretation: ProCaLNMD demonstrated high diagnostic capabilities for identifying LNM in prostate cancer, reducing the likelihood of missed diagnoses by pathologists and decreasing the slide reviewing time, highlighting its potential for clinical application. Funding: National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, the Guangdong Provincial Clinical Research Centre for Urological Diseases, and the Science and Technology Projects in Guangzhou.

Development and validation of an artificial intelligence-based model for detecting urothelial carcinoma using urine cytology images: a multicentre, diagnostic study with prospective validation.

Background: Urine cytology is an important non-invasive examination for urothelial carcinoma (UC) diagnosis and follow-up. We aimed to explore whether artificial intelligence (AI) can enhance the sensitivity of urine cytology and help avoid unnecessary endoscopy. Methods: In this multicentre diagnostic study, consecutive patients who underwent liquid-based urine cytology examinations at four hospitals in China were included for model development and validation. Patients who declined surgery and lacked associated histopathology results, those diagnosed with rare subtype tumours of the urinary tract, or had low-quality images were excluded from the study. All liquid-based cytology slides were scanned into whole-slide images (WSIs) at 40 × magnification and the WSI-labels were derived from the corresponding histopathology results. The Precision Urine Cytology AI Solution (PUCAS) was composed of three distinct stages (patch extraction, features extraction, and classification diagnosis) and was trained to identify important WSI features associated with UC diagnosis. The diagnostic sensitivity was mainly used to validate the performance of PUCAS in retrospective and prospective validation cohorts. This study is registered with the ChiCTR, ChiCTR2300073192. Findings: Between January 1, 2018 and October 31, 2022, 2641 patients were retrospectively recruited in the training cohort, and 2335 in retrospective validation cohorts; 400 eligible patients were enrolled in the prospective validation cohort between July 7, 2023 and September 15, 2023. The sensitivity of PUCAS ranged from 0.922 (95% CI: 0.811-0.978) to 1.000 (0.782-1.000) in retrospective validation cohorts, and was 0.896 (0.837-0.939) in prospective validation cohort. The PUCAS model also exhibited a good performance in detecting malignancy within atypical urothelial cells cases, with a sensitivity of over 0.84. In the recurrence detection scenario, PUCAS could reduce 57.5% of endoscopy use with a negative predictive value of 96.4%. Interpretation: PUCAS may help to improve the sensitivity of urine cytology, reduce misdiagnoses of UC, avoid unnecessary endoscopy, and reduce the clinical burden in resource-limited areas. The further validation in other countries is needed. Funding: National Natural Science Foundation of China; Key Program of the National Natural Science Foundation of China; the National Science Foundation for Distinguished Young Scholars; the Science and Technology Planning Project of Guangdong Province; the National Key Research and Development Programme of China; Guangdong Provincial Clinical Research Centre for Urological Diseases.

Identification of genomic-wide genetic links between cutaneous melanoma and obesity-related physical traits via cFDR.

BACKGROUND: Both epidemiological and clinical studies have suggested the comorbidity between cutaneous melanoma (CM) and obesity-related physical traits. However, it remains unclear about their shared genetic architecture. OBJECTIVE: To determine the shared genetic architecture between CM and obesity-related physical traits through conditional false discovery rate (cFDR) analysis. METHOD: Quantile-quantile plots were firstly built to assess the pleiotropic enrichment of shared single nucleotide polymorphisms between CM and each trait. Then, cFDR and conjunctional cFDR (ccFDR) were used to identify the shared risk loci between CM and each trait. Moreover, the functional evaluation of shared risk genes was carried out through analyses of expression quantitative trait loci (eQTL), Kyoto Encyclopedia of Genes and Genomes and gene ontology, respectively. Finally, single-cell sequence analysis was performed to locate the expression of eQTL-mapped genes in tissues. RESULTS: Successive pleiotropic enrichment was found between CM and 5 obesity-related traits or height. 24 shared risk loci were identified between CM and 13 traits except appendicular lean mass using ccFDR analysis, with 17 novel and 4 validated loci. The functions of ccFDR-identified and eQTL-mapped genes were revealed to be mainly involved in cellular senescence, proliferation, meiotic nuclear division, cell cycle, and the metabolism of lipid, cholesterol and glucose. Single-cell sequence analysis showed that keratinocytes contribute to the occurrence and aggressiveness of CM through secreting paracrine cytokines. CONCLUSION: Our findings demonstrate the significant genetic correlation between CM and obesity-related physical traits, which may provide a novel genetical basis for the pathogenesis and treatment of CM.

Leisure sedentary behaviour increases the risk of venous thromboembolism: a Mendelian randomisation study.

BACKGROUND: Venous thromboembolism (VTE) is a substantial contributor to the global burden of disease. Observational studies have suggested that leisure sedentary behaviours (LSB) are related to the risk of VTE; however, the causal role of LSB in VTE remains unclear. METHODS: Using data obtained from genome-wide association studies in the UK Biobank (N = 422,218), we identified 84, 21, and 4 single nucleotide polymorphisms (SNPs) related to sedentary television (TV) watching, computer use, and driving, respectively. These SNPs were employed as instrumental variables. Summary statistics for SNP-VTE associations was obtained from the FinnGen study (5,403 cases and 130,235 controls). Two-sample Mendelian randomisation (MR) analyses were performed using inverse-variance weighted (IVW), MR-Egger,weighted median, and weighted mode approaches. Sensitivity analyses were conducted to ensure robustness of the results. RESULTS: The main IVW approach demonstrated a positive association between the genetically predicted sedentary TV watching and the risk of VTE [odds ratio (OR):1.35, 95% confidence interval (CI):1.02-1.80, P = 0.039]. However, no significant association was observed for genetically predicted sedentary computer use or driving and VTE risk. The results from our series of sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, and MR-Pleiotropy RESidual Sum and Outlier method, further supported these findings. CONCLUSION: This study provides evidence of an association between genetically predicted sedentary TV watching and the risk of VTE. Further studies are required to elucidate the underlying causal mechanisms.

Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.

BACKGROUND: Accurate lymph node staging is important for the diagnosis and treatment of patients with bladder cancer. We aimed to develop a lymph node metastases diagnostic model (LNMDM) on whole slide images and to assess the clinical effect of an artificial intelligence-assisted (AI) workflow. METHODS: In this retrospective, multicentre, diagnostic study in China, we included consecutive patients with bladder cancer who had radical cystectomy and pelvic lymph node dissection, and from whom whole slide images of lymph node sections were available, for model development. We excluded patients with non-bladder cancer and concurrent surgery, or low-quality images. Patients from two hospitals (Sun Yat-sen Memorial Hospital of Sun Yat-sen University and Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China) were assigned before a cutoff date to a training set and after the date to internal validation sets for each hospital. Patients from three other hospitals (the Third Affiliated Hospital of Sun Yat-sen University, Nanfang Hospital of Southern Medical University, and the Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China) were included as external validation sets. A validation subset of challenging cases from the five validation sets was used to compare performance between the LNMDM and pathologists, and two other datasets (breast cancer from the CAMELYON16 dataset and prostate cancer from the Sun Yat-sen Memorial Hospital of Sun Yat-sen University) were collected for a multi-cancer test. The primary endpoint was diagnostic sensitivity in the four prespecified groups (ie, the five validation sets, a single-lymph-node test set, the multi-cancer test set, and the subset for a performance comparison between the LNMDM and pathologists). FINDINGS: Between Jan 1, 2013 and Dec 31, 2021, 1012 patients with bladder cancer had radical cystectomy and pelvic lymph node dissection and were included (8177 images and 20 954 lymph nodes). We excluded 14 patients (165 images) with concurrent non-bladder cancer and also excluded 21 low-quality images. We included 998 patients and 7991 images (881 [88%] men; 117 [12%] women; median age 64 years [IQR 56-72]; ethnicity data not available; 268 [27%] with lymph node metastases) to develop the LNMDM. The area under the curve (AUC) for accurate diagnosis of the LNMDM ranged from 0·978 (95% CI 0·960-0·996) to 0·998 (0·996-1·000) in the five validation sets. Performance comparisons between the LNMDM and pathologists showed that the diagnostic sensitivity of the model (0·983 [95% CI 0·941-0·998]) substantially exceeded that of both junior pathologists (0·906 [0·871-0·934]) and senior pathologists (0·947 [0·919-0·968]), and that AI assistance improved sensitivity for both junior (from 0·906 without AI to 0·953 with AI) and senior (from 0·947 to 0·986) pathologists. In the multi-cancer test, the LNMDM maintained an AUC of 0·943 (95% CI 0·918-0·969) in breast cancer images and 0·922 (0·884-0·960) in prostate cancer images. In 13 patients, the LNMDM detected tumour micrometastases that had been missed by pathologists who had previously classified these patients' results as negative. Receiver operating characteristic curves showed that the LNMDM would enable pathologists to exclude 80-92% of negative slides while maintaining 100% sensitivity in clinical application. INTERPRETATION: We developed an AI-based diagnostic model that did well in detecting lymph node metastases, particularly micrometastases. The LNMDM showed substantial potential for clinical applications in improving the accuracy and efficiency of pathologists' work. FUNDING: National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, and the Guangdong Provincial Clinical Research Centre for Urological Diseases.

Machine learning-based prediction of the post-thrombotic syndrome: Model development and validation study.

Background: Prevention is highly involved in reducing the incidence of post-thrombotic syndrome (PTS). We aimed to develop accurate models with machine learning (ML) algorithms to predict whether PTS would occur within 24 months. Materials and methods: The clinical data used for model building were obtained from the Acute Venous Thrombosis: Thrombus Removal with Adjunctive Catheter-Directed Thrombolysis study and the external validation cohort was acquired from the Sun Yat-sen Memorial Hospital in China. The main outcome was defined as the occurrence of PTS events (Villalta score ≥5). Twenty-three clinical variables were included, and four ML algorithms were applied to build the models. For discrimination and calibration, F scores were used to evaluate the prediction ability of the models. The external validation cohort was divided into ten groups based on the risk estimate deciles to identify the hazard threshold. Results: In total, 555 patients with deep vein thrombosis (DVT) were included to build models using ML algorithms, and the models were further validated in a Chinese cohort comprising 117 patients. When predicting PTS within 2 years after acute DVT, logistic regression based on gradient descent and L1 regularization got the highest area under the curve (AUC) of 0.83 (95% CI:0.76-0.89) in external validation. When considering model performance in both the derivation and external validation cohorts, the eXtreme gradient boosting and gradient boosting decision tree models had similar results and presented better stability and generalization. The external validation cohort was divided into low, intermediate, and high-risk groups with the prediction probability of 0.3 and 0.4 as critical points. Conclusion: Machine learning models built for PTS had accurate prediction ability and stable generalization, which can further facilitate clinical decision-making, with potentially important implications for selecting patients who will benefit from endovascular surgery.

Causal relationship between 14 site-specific cancers and venous thromboembolism.

Background: It has been observed that cancer and venous thromboembolism (VTE) are associated, but anticancer therapy may violate the causality. Therefore, this study aimed to elucidate the causal relationship of various cancers to VTE using Mendelian randomization (MR). Methods: Three MR methods were used to estimate causal effects: Inverse variance weighted (IVW), MR-Egger and weighted median. Sensitivity analyses included Cochran's Q-test, MR-Egger intercept test and MR-PRESSO. Gene ontology enrichment analysis was performed to elucidate the underlying mechanisms of VTE development in cancer patients. Results: The primary IVW approach showed that non-Hodgkin's lymphoma (NHL) might increase the risk of VTE (odds ratio [OR]: 1.20, 95% confidence interval [95% CI]: 1.00-1.44, p = 0.045), while melanoma possibly reduced the risk of VTE (OR: 0.89, 95% CI: 0.82-0.97, p = 0.006), although there was no significance after adjustment for multiple testing. No association was observed between VTE risk and other site-specific cancers. Gene ontology enrichment analysis revealed that vitamin D played an important role in the development of VTE in cancer patients. Conclusions: Our findings suggested that genetically predicted NHL was associated with higher VTE risk, whereas melanoma had lower VTE risk compared with other site-specific cancers. Moreover, this study suggested that anticancer therapy and increased extensive examination might play a more important role in VTE development than the nature of cancer.

Association between anion gap and mortality of aortic aneurysm in intensive care unit after open surgery.

BACKGROUND: There has not been a well-accepted prognostic model to predict the mortality of aortic aneurysm patients in intensive care unit after open surgery repair. Otherwise, our previous study found that anion gap was a prognosis factor for aortic aneurysm patients. Therefore, we wanted to investigate the relationship between anion gap and mortality of aortic aneurysm patients in intensive care unit after open surgery repair. METHODS: From Medical Information Mart for Intensive Care III, data of aortic aneurysm patients in intensive care unit after open surgery were enrolled. The primary clinical outcome was defined as death in intensive care unit. Univariate analysis was conducted to compare the baseline data in different groups stratified by clinical outcome or by anion gap level. Restricted cubic spline was drawn to find out the association between anion gap level and mortality. Subgroup analysis was then conducted to show the association in different level and was presented as frost plot. Multivariate regression models were built based on anion gap and were adjusted by admission information, severity score, complication, operation and laboratory indicators. Receiver operating characteristic curves were drawn to compare the prognosis ability of anion gap and simplified acute physiology score II. Decision curve analysis was finally conducted to indicate the net benefit of the models. RESULTS: A total of 405 aortic aneurysm patients were enrolled in this study and the in-intensive-care-unit (in-ICU) mortality was 6.9%. Univariate analysis showed that elevated anion gap was associated with high mortality (P value < 0.001), and restricted cubic spline analysis showed the positive correlation between anion gap and mortality. Receiver operating characteristic curve showed that the mortality predictive ability of anion gap approached that of simplified acute physiology score II and even performed better in predicting in-hospital mortality (P value < 0.05). Moreover, models based on anion gap showed that 1 mEq/L increase of anion gap improved up to 42.3% (95% confidence interval 28.5-59.8%) risk of death. CONCLUSIONS: The level of serum anion gap was an important prognosis factor for aortic aneurysm mortality in intensive care unit after open surgery.

Development of SAB model for predicting mortality in intensive care unit after aortic aneurysm surgery.

BACKGROUND: Aortic aneurysm (AA) patients after vascular surgery are at high risk of death, some of them need intensive care. Our aim was to develop a simplified model with baseline data within 24 hours of intensive care unit (ICU) admission to early predict mortality. METHODS: Univariate analysis and least absolute shrinkage and selection operator were used to select important variables, which were then taken into logistic regression to fit the model. Discrimination and validation were used to evaluate the performance of the model. Bootstrap method was conducted to perform internal validation. Finally, decision clinical analysis curve was used to test the clinical usefulness of the model. RESULTS: We obtained baseline data of 482 AA patients from Medical Information Mart for Intensive Care III database, 33 (6.8%) of whom died in ICU. Our final model contained three variables and was called SAB model based on initials of three items [Sepsis, Anion gap, Bicarbonate (SAB)]. Area under the curve of SAB was 0.904 (95% CI: 0.841-0.967) while brier score was 0.043 (95% CI: 0.028-0.057). After internal validation, corrected area under the curve was 0.898 and brier score was 0.045, which showed good prediction ability of SAB model. The model can be assessed on https://vascularmodel.shinyapps.io/AorticAneurysm/. CONCLUSIONS: SAB model derived in this study can be easily used to predict in-ICU mortality of AA patients after surgery precisely.

Prognostic nomogram for 30-day mortality of deep vein thrombosis patients in intensive care unit.

BACKGROUND: We aimed to use the Medical Information Mart for Intensive Care III database to build a nomogram to identify 30-day mortality risk of deep vein thrombosis (DVT) patients in intensive care unit (ICU). METHODS: Stepwise logistic regression and logistic regression with least absolute shrinkage and selection operator (LASSO) were used to fit two prediction models. Bootstrap method was used to perform internal validation. RESULTS: We obtained baseline data of 535 DVT patients, 91 (17%) of whom died within 30 days. The discriminations of two new models were better than traditional scores. Compared with simplified acute physiology score II (SAPSII), the predictive abilities of two new models were improved (Net reclassification improvement [NRI] > 0; Integrated discrimination improvement [IDI] > 0; P < 0.05). The Brier scores of two new models in training set were 0.091 and 0.108. After internal validation, corrected area under the curves for two models were 0.850 and 0.830, while corrected Brier scores were 0.108 and 0.114. The more concise model was chosen to make the nomogram. CONCLUSIONS: The nomogram developed by logistic regression with LASSO model can provide an accurate prognosis for DVT patients in ICU.

A retrospective analysis of risk factors associated with catheter-related thrombosis: a single-center study.

BACKGROUND: Catheter-related thrombosis may lead to catheter infections and failure, further deep venous thrombosis, and pulmonary embolism. Recognizing the risk factors for catheter-related thrombosis is extremely important to inform the development of catheter care guidelines. METHODS: Data were collected from a total of 1,532 patients who had undergone venous catheterization, including indwelling catheterization from 19 March 2019 to 30 March 2019 in the Sun Yat-sen Memorial Hospital. The factors for which data were to be collected included the patients' physical characteristics, catheter-related factors, and catheter care-related factors. Logistic regression analysis, the chi-squared test, Fisher's exact test, and the t-test were used to analyze the data. RESULTS: Of the 1,532 patients studied, 28 developed intraductal thrombi, and of the factors analyzed, malignancy, a catheterization history, a history of thrombophilia, surgery during the week before catheterization, the catheterization duration, and anticoagulant therapy were significant risk factors associated with catheter-related thrombosis (all p < 0.05). There were no significant associations between the catheter brand, the number of lumens, the insertion direction, or the factors associated with catheter care and catheter-related thrombosis (all p > 0.05). CONCLUSION: Our study incorporated clear and systematic risk factors associated with catheter-related thrombosis. Malignancy, history of thrombophilia, history of catheterization, surgery during the week before catheterization, and catheterization duration were associated with increased risks of catheter-related thrombosis. Prophylactic anticoagulation was effective for preventing and treating catheter-related thrombosis.

Waist circumference increases risk of coronary heart disease: Evidence from a Mendelian randomization study.

BACKGROUND: This study investigated whether expanding waist circumference (WC) is causally associated with an elevated risk of coronary heart disease (CHD), using a two-sample Mendelian randomization (MR) study through integrating summarized data from genome-wide association study. METHODS: The data included in this analysis were mainly from the Genetic Investigation of ANthropometric Traits (GIANT), Consortium and Coronary Artery Disease Genome wide Replication, and Meta-analysis plus the Coronary Artery Disease (C4D) Genetics (CARDIoGRAMplusC4D) Consortium. Three statistical approaches, inverse-variance weighted (IVW), weighted median, and MR-Egger regression method were conducted to assess the casual relationship. The exposure was WC, measured by 46 single-nucleotide polymorphisms from GIANT and the outcome was the risk of CHD. Then, we used the genetic data from Neale Lab and TAG to infer whether WC causally affected the established risk factors of CHD. RESULTS: The IVW method presented that genetically predicted WC was positively casually associated with CHD (odds ratio [OR]: 1.57, 95% CI = 1.33-1.84; p = 4.81e-08), which was consistent with the result of weighted median and MR-Egger regression. MR-Egger regression indicated that there was no directional horizontal pleiotropy to violate the MR assumption. Additionally, expanded WC was also associated with higher risk of hypertension and diabetes, higher cholesterol, more smoking intensity, and decreased frequency of physical activity. CONCLUSION: Our analysis provided strong evidence to indicate a causal relationship between WC and increased risk of CHD.

Kinetic isotope effects implicate two electrophilic oxidants in cytochrome p450-catalyzed hydroxylations.

Intramolecular kinetic isotope effects (KIEs) were determined for cytochrome P450-catalyzed hydroxylation reactions of methyl-dideuterated trans-2-phenylcyclopropylmethane-d2 (1-d2), which gives two products from oxidation of the methyl group, trans-2-phenylcyclopropylmethanol (2) and 1-phenyl-3-buten-1ol (3). In oxidations of each enantiomer of 1-d2 with three P450 enzymes (CYP2B1, CYPDelta2E1, and CYPDelta2E1 T303A), the apparent intramolecular KIEs were different for products 2 and 3 in all cases and different for each enzyme-substrate combination. In oxidations of each enantiomer of undeuterated 1-d0 and trideuteriomethyl 1-d3 by CYP2B1 and CYPDelta2E1, the ratio of products 2/3 decreased for 1-d3 in comparison to 1-d0 in all cases. The results require multiple pathways for P450-catalyzed hydroxylation and are consistent with the "two-oxidants" model, where hydroxylation is effected by both the hydroperoxy-iron species and the iron-oxo species. The results are not consistent with predictions of the "two-states" model for P450-catalyzed hydroxylations, where oxidations occur from a low-spin state and a high-spin state of iron-oxo.

Evaluation of norcarane as a probe for radicals in cytochome p450- and soluble methane monooxygenase-catalyzed hydroxylation reactions.

Norcarane was employed as a mechanistic probe in oxidations catalyzed by hepatic cytochome P450 enzymes and by the soluble methane monooxygenase (sMMO) enzyme from Methylococcuscapsulatus (Bath). In all cases, the major oxidation products (>75%) were endo- and exo-2-norcaranol. Small amounts of 3-norcaranols, 2-norcaranone, and 3-norcaranone also formed. In addition, the rearrangement products (2-cyclohexenyl)methanol and 3-cycloheptenol were detected in the reactions, the former possibly arising from a radical intermediate and the latter ascribed to a cationic intermediate. The formation of the cation-derived rearrangement product is consistent with one or more reaction pathways and is in accord with the results of previous probe studies with the same enzymes. The appearance of the putative radical-derived rearrangement product is in conflict with other mechanistic probe results with the same enzymes. The unique implication of a discrete radical intermediate in hydroxylations of norcarane may be the consequence of a minor reaction pathway for the enzymes that is not manifest in reactions with other probes. Alternatively, it might reflect a previously unappreciated reactivity of norcaranyl cationic intermediates, which can convert to (2-cyclohexenyl)methanol. We conclude that generalizations regarding the intermediacy of radicals in P450 and sMMO enzyme-catalyzed hydroxylations based on the norcarane results should be considered hypothetical until the origin of the unanticipated results can be determined.