Development of a luciferase-based Gram-positive bacterial reporter system for the characterization of antimicrobial agents.

Mechanistic investigations are of paramount importance in elucidating the modes of action of antibiotics and facilitating the discovery of novel drugs. We reported a luciferase-based reporter system using bacterial cells to unveil mechanisms of antimicrobials targeting transcription and translation. The reporter gene Nluc encoding NanoLuciferase (NanoLuc) was integrated into the genome of the Gram-positive model organism, Bacillus subtilis, to generate a reporter strain BS2019. Cellular transcription and translation levels were assessed by quantifying the amount of Nluc mRNA as well as the luminescence catalyzed by the enzyme NanoLuc. We validated this system using three known inhibitors of transcription (rifampicin), translation (chloramphenicol), and cell wall synthesis (ampicillin). The B. subtilis reporter strain BS2019 successfully revealed a decline in Nluc expression by rifampicin and NanoLuc enzyme activity by chloramphenicol, while ampicillin produced no observable effect. The assay was employed to characterize a previously discovered bacterial transcription inhibitor, CUHK242, with known antimicrobial activity against drug-resistant Staphylococcus aureus. Production of Nluc mRNA in our reporter BS2019 was suppressed in the presence of CUHK242, demonstrating the usefulness of the construct, which provides a simple way to study the mechanism of potential antibiotic candidates at early stages of drug discovery. The reporter system can also be modified by adopting different promoters and reporter genes to extend its scope of contribution to other fields of work. IMPORTANCE: Discovering new classes of antibiotics is desperately needed to combat the emergence of multidrug-resistant pathogens. To facilitate the drug discovery process, a simple cell-based assay for mechanistic studies is essential to characterize antimicrobial candidates. In this work, we developed a luciferase-based reporter system to quantify the transcriptional and translational effects of potential compounds and validated our system using two currently marketed drugs. Reporter strains generated in this study provide readily available means for identifying bacterial transcription inhibitors as prospective novel antibacterials. We also provided a series of plasmids for characterizing promoters under various conditions such as stress.

Development and validation of 10-year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning-based methods.

AIM: To develop 10-year cardiovascular disease (CVD) risk prediction models in Chinese patients with type 2 diabetes mellitus (T2DM) managed in primary care using machine learning (ML) methods. METHODS: In this 10-year population-based retrospective cohort study, 141 516 Chinese T2DM patients aged 18 years or above, without history of CVD or end-stage renal disease and managed in public primary care clinics in 2008, were included and followed up until December 2017. Two-thirds of the patients were randomly selected to develop sex-specific CVD risk prediction models. The remaining one-third of patients were used as the validation sample to evaluate the discrimination and calibration of the models. ML-based methods were applied to missing data imputation, predictor selection, risk prediction modelling, model interpretation, and model evaluation. Cox regression was used to develop the statistical models in parallel for comparison. RESULTS: During a median follow-up of 9.75 years, 32 445 patients (22.9%) developed CVD. Age, T2DM duration, urine albumin-to-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), systolic blood pressure variability and glycated haemoglobin (HbA1c) variability were the most important predictors. ML models also identified nonlinear effects of several predictors, particularly the U-shaped effects of eGFR and body mass index. The ML models showed a Harrell's C statistic of >0.80 and good calibration. The ML models performed significantly better than the Cox regression models in CVD risk prediction and achieved better risk stratification for individual patients. CONCLUSION: Using routinely available predictors and ML-based algorithms, this study established 10-year CVD risk prediction models for Chinese T2DM patients in primary care. The findings highlight the importance of renal function indicators, and variability in both blood pressure and HbA1c as CVD predictors, which deserve more clinical attention. The derived risk prediction tools have the potential to support clinical decision making and encourage patients towards self-care, subject to further research confirming the models' feasibility, acceptability and applicability at the point of care.

Sulfonamidyl derivatives of sigmacidin: Protein-protein interaction inhibitors targeting bacterial RNA polymerase and sigma factor interaction exhibiting antimicrobial activity against antibiotic-resistant bacteria.

RNA polymerase is an essential enzyme involved in bacterial transcription, playing a crucial role in RNA synthesis. However, it requires the association with sigma factors to initiate this process. In our previous work, we utilized a structure-based drug discovery approach to create benzoyl and benzyl benzoic acid compounds. These compounds were designed based on the amino acid residues within the key binding site of sigma factors, which are crucial for their interaction with RNA polymerase. By inhibiting bacterial transcription, these compounds exhibited notable antimicrobial activity, and we coined them as sigmacidins to highlight their resemblance to sigma factors and the benzoic acid structure. In this study, we further modified the compound scaffolds and developed a series of sulfonamidyl benzoic acid derivatives. These derivatives displayed potent antimicrobial activity, with minimum inhibitory concentrations (MICs) as low as 1 µg/mL, demonstrating their efficacy against bacteria. Furthermore, these compounds demonstrated low cytotoxicity, indicating their potential as safe antimicrobial agents. To ascertain their mechanism of action in interfering with bacterial transcription, we conducted biochemical and cellular assays. Overall, this study showcases the effectiveness of sulfonamidyl benzoic acid derivatives as antimicrobial agents by targeting protein-protein interactions involving RNA polymerase and sigma factors. Their strong antimicrobial activity and low cytotoxicity implicate their potential in combating antibiotic-resistant bacteria.

Copper-Catalyzed Synthesis of Functionalized Aryl Sulfonamides from Sodium Sulfinates in Green Solvents.

Functionalized aryl sulfonamides are important building blocks in the pharmaceutical industry. A one-step synthesis catalyzed by a copper salt was developed using stable solid commodity chemicals in sulfolane or, alternatively, in green solvents such as γ-valerolactone, iPrOAc, or nBuOAc with acetic acid. The method tolerated diverse functional groups commonly presented in current medicines and drug intermediates. The mechanistic study showed a radical coupling pathway between the sulfonyl and anilinium radicals through the use of K2S2O8 and copper catalyst, respectively.

Prediction models and nomograms for 10-year risk of end-stage renal disease in Chinese type 2 diabetes mellitus patients in primary care.

AIMS: To develop and validate 10-year risk prediction models, nomograms and charts for end-stage renal disease (ESRD) in Chinese patients with type 2 diabetes mellitus (T2DM) in primary care, in order to guide individualized treatment. MATERIALS AND METHODS: This was a 10-year population-based observational cohort study. A total of 141 516 Chinese T2DM patients without history of cardiovascular disease or ESRD who were managed in public primary care clinics in 2008 were included and followed up until December 2017. Two-thirds of these patients were randomly selected to develop sex-specific ESRD risk prediction models using Cox regressions. The validity and accuracy of the models were tested on the remaining third of patients using Harrell's C-index. We selected variables based on their clinical and statistical importance to construct the nomograms and charts. RESULTS: The median follow-up period was 9.75 years. The cumulative incidence of ESRD was 6.0% (men: 6.1%, women: 5.9%). Age, diabetes duration, systolic blood pressure (SBP), SBP variability, diastolic blood pressure, triglycerides, glycated haemoglobin (HbA1c), HbA1c variability, urine albumin to creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) were significant predictors for both sexes. Smoking and total cholesterol to HDL cholesterol ratio were additional significant predictors for men and women, respectively. The models showed Harrell's C-statistics of 0.889/0.889 (women/men). Age, eGFR, UACR, SBP and HbA1c were selected for both sexes to develop nomograms and charts. CONCLUSIONS: Using routinely available variables, the 10-year ESRD risk of Chinese T2DM patients in primary care can be predicted with approximately 90% accuracy. We have developed different tools to facilitate routine ESRD risk prediction in primary care, so that individualized care can be provided to prevent or delay ESRD in T2DM patients.

Efficacy of MaZiRenWan, a Chinese Herbal Medicine, in Patients With Functional Constipation in a Randomized Controlled Trial.

BACKGROUND & AIMS: The Chinese herbal medicine, MaZiRenWan (MZRW), has been used for more than 2000 years to treat constipation, but it has not been tested in a randomized controlled trial. We performed a trial to evaluate the efficacy and safety of MZRW, compared with the stimulant laxative senna or placebo, for patients with functional constipation (FC). METHODS: We performed a double-blind, double-dummy, trial of 291 patients with FC based on Rome III criteria, seen at 8 clinics in Hong Kong from June 2013 through August 2015. Patients were observed for 2 weeks and then assigned randomly (1:1:1) to groups given MZRW (7.5 g, twice daily), senna (15 mg daily), or placebo for 8 weeks. Patients were then followed for 8 weeks and evaluated at baseline and weeks 4, 8 (end of treatment), and 16 (end of follow up). Participants recorded information on stool form and frequency, feeling of complete evacuation, and research medication taken. Data on individual bowel symptoms, global symptom improvement, and adverse events were collected. A complete response was defined as an increase ≥1 complete spontaneous bowel movement (CSBM)/week from baseline (the primary outcome). Secondary outcomes included response during the follow-up period, colonic transit, individual and global symptom assessments, quality of life measured with 36-item short form Chinese version, and adverse events. RESULTS: Although there was no statistically significant difference in proportions of patients with a complete response to MZRW (68%) vs. senna (57.7%) (P = .14) at week 8, there was a statistically significant difference vs. placebo (33.0%) (P < .005). At the 16-week timepoint (after the 8-week follow-up period), 47.4% of patients had a complete response to MZRW, 20.6% had a complete response to senna, and 17.5% had a complete response to placebo (P < .005 for MZRW vs. placebo). The group that received MZRW group also had significant increases in colonic transit and reduced severity of constipation, straining, incomplete evacuation, and global constipation symptoms compared with the groups that received placebo or senna in (P < .05 for all comparisons). CONCLUSIONS: In a randomized controlled trial of 291 patients with FC, we found MZRW to be well-tolerated and effective in increasing CSBM/week. MZRW did not appear to be more effective than senna and might be considered as an alternative to this drug. ClincialTrials.gov no: NCT01695850.

Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol.

INTRODUCTION: Diabetes mellitus (DM) is a major disease burden worldwide because it is associated with disabling and lethal complications. DM complication risk assessment and stratification is key to cost-effective management and tertiary prevention for patients with diabetes in primary care. Existing risk prediction functions were found to be inaccurate in Chinese patients with diabetes in primary care. This study aims to develop 10-year risk prediction models for total cardiovascular diseases (CVD) and all-cause mortality among Chinese patients with DM in primary care. METHODS AND ANALYSIS: A 10-year cohort study on a population-based primary care cohort of Chinese patients with diabetes, who were receiving care in the Hospital Authority General Outpatient Clinic on or before 1 January 2008, were identified from the clinical management system database of the Hospital Authority. All patients with complete baseline risk factors will be included and followed from 1 January 2008 to 31 December 2017 for the development and validation of prediction models. The analyses will be carried out separately for men and women. Two-thirds of subjects will be randomly selected as the training sample for model development. Cox regressions will be used to develop 10-year risk prediction models of total CVD and all-cause mortality. The validity of models will be tested on the remaining one-third of subjects by Harrell's C-statistics and calibration plot. Risk prediction models for diabetic complications specific to Chinese patients in primary care will enable accurate risk stratification, prioritisation of resources and more cost-effective interventions for patients with DM in primary care. ETHICS AND DISSEMINATION: The study was approved by the Institutional Review Board of the University of Hong Kong-the Hospital Authority Hong Kong West Cluster (reference number: UW 15-258). TRIAL REGISTRATION NUMBER: NCT03299010; Pre-results.

Chinese herbal medicine (Ma Zi Ren Wan) for functional constipation: study protocol for a prospective, double-blinded, double-dummy, randomized controlled trial.

BACKGROUND: Functional constipation is a common clinical complaint. Although the effectiveness of Ma Zi Ren Wan for alleviating functional constipation symptoms has been proven in a previous randomized placebo-controlled study, further evidence is needed to make clinical recommendations about Chinese herbal medicine. In particular, a comparison with conventional western medicine for functional constipation patients is needed. METHODS/DESIGN: This is a prospective, double-blinded, double dummy, randomized, controlled trial. After a 2-week run-in period, eligible patients (Rome III) with excessive traditional Chinese medicine syndrome will randomly be assigned to the Chinese medicine arm (Ma Zi Ren Wan and western medicine placebo), western medicine arm (senna and Chinese medicine placebo) or placebo arm (Chinese medicine placebo and western medicine placebo). Patients will undergo an 8-week treatment and an 8-week follow-up. The primary outcome is the responder rate for complete spontaneous bowel movement (CSBM) during treatment. Patients with a mean increase of CSBM ≧1/week in comparison with their baselines are defined as responders. The secondary outcomes include responder rate during follow-up, changes of colonic transit as measured with radio-opaque markers, individual and global symptom assessments, and reported adverse effects. DISCUSSION: This study is the first study to compare a Chinese Herbal Medicine (Ma Zi Ren Wan) with a laxative that is commonly used in the clinical practice of western medicine, and with a placebo. This study will complete the investigation of Ma Zi Ren Wan for functional constipation, and should, therefore, suggest recommendations for clinical practice. Furthermore, the process of first conducting a systematic review, then implementing a dose determination study followed by a placebo-control trial, and finally, comparing traditional Chinese medicine with an active conventional medicine in a controlled trial can be a reference to other researches on Chinese medicine interventions in the future. TRIAL REGISTRATION: NCT01695850.