Thermal Challenges in Dynamic Infrared Thermography Used for Perforator Mapping.

BACKGROUND: The aim of this study is to investigate the different approaches to thermal challenges, both cold and warm, used in dynamic infrared thermography for reconstructive surgery, and explore whether it affects the success of preoperative perforator mapping. METHODS: Literature was collected from Ovid Medline, Embase, PubMed, and Cochrane. The references of the full-text articles located from the original search were also appraised. Thirteen articles were extracted for the final qualitative analysis. A systematic review was then conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS: Thirteen articles looked at a cold challenge, which included airflow cooling, direct contact cooling, and evaporation-based cooling. Two articles investigated warm challenges. One paper used no challenge, suggesting it unnecessary with a highly sensitive camera. All cold challenges were positively supported by a high level of flap perfusion success and/or a high level of correlation with other forms of investigation. CONCLUSION: Cold challenges were overall superior to no challenge and warm challenges; however, this conclusion is limited by the small participant size, the possibility of detection bias, and poor methodology detailing. Airflow cooling-specifically, using a desktop fan to blow air for 2 minutes-was noted to likely cause the least discomfort due to a low cooling capacity yet simultaneously maintain effectiveness and allow for a uniform cooling application. Warm challenges showed less conclusive results and were restricted by lack of studies. This topic would benefit from larger scale studies that compare multiple approaches while using standardized equipment to eliminate confounding factors.

Disparities in Time to Diagnosis Among Patients With Multiple Myeloma.

BACKGROUND: Multiple myeloma (MM) is one of the most diagnosed hematologic malignancies in the United States. Despite improvements in therapy, health disparities persist among patients with MM. Here, we aim to determine whether there are disparities in time to diagnosis (TTD) among MM patients with regard to income, race/ethnicity, and gender. PATIENTS: Patients with a monoclonal protein detected in the serum and/or urine and a subsequent bone marrow biopsy confirmed diagnosis of MM were included in the study. METHODS: We extracted data on patients with MM and assessed whether the predictor variables were associated with the primary outcome of TTD, which we define as the time between detection of a monoclonal protein in the serum or urine and bone marrow biopsy diagnosis of MM. RESULTS: Compared to patients with commercial insurance, patients receiving Medicaid (HR: 0.408, 95% CI: 0.206-0.808; P = .010) and patients without insurance (HR: 0.428, 95% CI: 0.207-0.885; P = .022) were significantly more likely to have delayed TTD. TTD was also prolonged if the provider who ordered the testing for the detection of a monoclonal protein was not a hematologist (HR: 0.435, 95% CI: 0.284-0.668; P < .0001). No disparities were found with regard to race/ethnicity or gender. CONCLUSION: This study suggests there may be socioeconomic disparities in TTD among patients with MM. Interventions such as patient navigation may be useful to reduce TTD among socioeconomically disadvantaged patient populations. Further studies need to be conducted to elucidate reasons for delays.

Lessons to inform interventions to reduce racial and ethnic health disparities within hematologic malignancies.

Although racial and ethnic disparities in diagnosis, treatment, and survival have been well documented within the field of hematologic malignancies, very little work has focused on testing interventions that may reduce these disparities. The aim of this commentary is to review prior work in hematologic malignancies and explore new opportunities to develop disparity-reducing interventions by drawing from evidence-based strategies that have been successfully implemented in fields related to hematologic malignancies, including oncology and solid organ transplants. Relevant literature demonstrates that patient navigation and broader insurance coverage have been shown to reduce racial and ethnic disparities among patients with solid malignancies such as colorectal and breast cancer. Evidence-based strategies that might be most applicable to the field of hematologic malignancies include patient navigation and policy changes.

Comparison of controlled drugs and new psychoactive substances (NPS) regulations in East and Southeast Asia.

New psychoactive substances (NPS) are substances of abuse that easily evade existing controlled drug regulations. This study conducted a systematic review on controlled drug regulations and analyzed the numbers of new psychoactive substances (NPS) reported in six East and Southeast Asian countries in comparison to US and UK from 2009 to 2020. Generally, more NPS were reported in the US (551) and UK (400), compared to Japan (379), China (221), Singapore (142), South Korea (99), Malaysia (41), and Taiwan (35). Legislative mechanisms including the specific listing of individual substances, generic control of a family of substances, analogue control of similar substances, temporary bans of new substances were evaluated. In this review, countries that have adopted a combination of legislative mechanisms were able to identify higher numbers of NPS for regulatory control, such as the US, UK, Japan, Singapore, and South Korea. These findings can provide references to countries like Malaysia and Taiwan, to strengthen NPS-related regulations nationally. Countries in the East and Southeast Asian region should be encouraged to collaborate more closely and to implement additional legislative approaches most relevant to the regional NPS trends to bridge the regulatory gap and to prevent the spread of emerging NPS.

Taiwan Controlled Substances Database.

New psychoactive substances (NPS) have increasingly been illegally synthesized and used around the world in recent years. Due to the large volume and the variety of NPS, most do not have sufficient information about their addictive potential and harmful effects to human subjects. This makes it difficult to evaluate these potential substances of abuse. This study aims to build a database based on Taiwan's controlled substances, to provide quick structural and pharmacological feedback. Taiwan Controlled Substances Database (TCSD) includes the collection of controlled substances, relevant experimental and structural information, as well as computational features such as molecular fingerprints and descriptors. Two types of structural search were added: substructure search and topological fingerprint similarity search. A web framework was used to enhance accessibility and usability (https://cs2search.cmdm.tw).

Elective Laparoscopic Cholecystectomy as an Entrustable Professional Activity (EPA) for General Surgical Trainees in Australia.

INTRODUCTION: To evaluate the operation time and surgical outcomes of elective laparoscopic cholecystectomy performed by surgical trainees at different levels of training at Eastern health and hence, to establish the efficacy and safety of elective laparoscopic cholecystectomy as an Entrustable Professional Activity for surgical trainees in general surgery. OBJECTIVE: Elective laparoscopic cholecystectomies performed at our institution between January 2018 and January 2019 were included. Analyses were divided among three groups - consultants (C), fellows (F) and registrars (R). Standard technique with critical view of safety was used. RESULTS: A total of 592 patients was included, with a mean age of 54 ± 63 years old. The average operation time was 84 ± 51 minutes. Surgical education and training (SET) 2 trainees took significantly longer when compared to their SET3 and above counterparts as a primary operator (SET2: 131 ± 32 min, Reference; SET3: 78 ± 21 min, p = 0.003; SET4: 80 ± 33 min, p = 0.004; SET5: 77 ± 28 min, p = 0.003; F: 93 ± 77 min, p = 0.036; C: 85 ± 59 min; p = 0.007). Consultant primary operators took an average of 15 minutes longer to complete the operation when assisted by a SET trainee compared to the non-SET registrars (p = 0.03). The overall complication rate was 3.2% and was not significantly different among all three groups (p = 0.17). No death was recorded during the study period. The readmission and return to theatre rates were 7.8% and 0.8% respectively and were not significantly different among the groups (p-values = 0.61 and 0.69). All conversion to open were performed by the consultant primary operator. CONCLUSIONS: Elective laparoscopic cholecystectomy can be safely performed by surgical trainees at all SET levels when under appropriate supervision, although junior surgical trainees that is SET 2 took longer to complete the procedure. This operation seems to have a steep, but relatively short, learning curve and it may be broken down into various components. These components, with the addition of time, may be suitable as an Entrustable Professional Activity tool for assessing the competency of early SET trainees.

Association of Provider Perspectives on Race and Racial Health Care Disparities with Patient Perceptions of Care and Health Outcomes.

Purpose: Research suggests that providers contribute to racial disparities in health outcomes. Identifying modifiable provider perspectives that are associated with decreased racial disparities will help in the design of effective educational interventions for providers. Methods: This cross-sectional study investigated the association between primary care provider (PCP) perspectives on race and racial disparities with patient outcomes. Results: Study participants included 40 PCPs (70% White, 30% racial minority) caring for 55 patients (45% White, 55% Black) with type 2 diabetes mellitus. Associations of provider perspectives on race and racial disparities with patient variables (Interpersonal Processes of Care [IPC] Survey, which measures patient's ratings of their provider's interpersonal skills; medication adherence; glycemic control) were measured using Spearman correlation coefficients. Results suggest that Black patients of providers who reported greater skill in caring for Black patients had more positive perceptions of care in three of four IPC subdomains (Spearman correlation coefficients of -0.43, 0.44, 0.46, all with p<0.05); however, Black patients of providers who believe that racial disparities are highly prevalent had more negative perceptions of care in three of four IPC subdomains (Spearman correlation coefficients of 0.38, -0.53, -0.51, all with p<0.05). These same provider characteristics had no correlation with outcomes of medication adherence and hemoglobin A1c (HbA1c) or among White patients. Conclusion: Findings suggest that Black patients of providers who felt better equipped to take care of Black patients had a better experience. Therefore, educational interventions for providers may be most effective if they focus on skill development rather than increasing awareness about racial disparities alone.

Racial differences in patient perception of interactions with providers are associated with health outcomes in type II diabetes.

OBJECTIVES: Examine the association of patient perceptions of care with hemoglobin A1c (HbA1c), medication adherence, and missed appointments in non-Hispanic Black (NHB) and White (NHW) patients with type 2 diabetes (T2DM). METHODS: We used linear and logistic regression models to analyze the association of the Interpersonal Processes of Care survey (IPC) with HbA1c, medication adherence, and missed appointments. We then examined how these associations differed by race. RESULTS: There was no overall association between IPC subdomains and HbA1c in our sample (N = 221). NHB patients perceiving their provider always explained results and medications had a HbA1c on average 0.59 (-1.13, -0.04; p = 0.04) points lower than those perceiving their provider sometimes explained results and medications. No effect was observed in NHWs. Never perceiving disrespect from office staff was associated with an average 0.67 (-1.1, -0.24; p = 0.002) point improvement in medication adherence for all patients. Never perceiving discrimination from providers was associated with a 0.44 (-0.63, -0.25; p < 0.0001) decrease in the probability of missing an appointment for NHB patients. CONCLUSIONS: These results demonstrate that particular aspects of communication in the patient-provider interaction may contribute to racial disparities in T2DM. PRACTICE IMPLICATIONS: Communication training for both providers and staff may reduce disparities in T2DM.

Smart Bedsheet for Baby Monitoring Application: Measurement and Characterization Results.

This paper describes a research collaboration with Studio 1 Labs to provide the characterization for a novel smart baby monitoring device which includes conductive fabrics. The electrical characterization of the conductive fabrics is important for designing a bedsheet that can adequately be sensitive to physiological movement. Electrical impedance spectroscopy (EIS) has been performed using the Metrohm Autolab potentiostat on a two-fabric interface. For an increase in applied weight, there was an overall decrease in impedance shown both in its real and imaginary components. A simple RC circuit model could be used to describe the system. A test bedsheet was made from a 3x3 conductive fabric matrix stitched into a cotton sheet. Conversely, an increase in resistance was observed from an increase in applied weights at the intersection points of the bedsheet. The following characterization provided useful insight into the future design of the smart bedsheet.

Human Breathomics Database.

Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database-the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw.

Mouse transient receptor potential channel type 6 selectively regulates agonist-induced platelet function.

While changes in intracellular calcium levels is a central step in platelet activation and thrombus formation, the contribution and mechanism of receptor-operated calcium entry (ROCE) via transient receptor potential channels (TRPCs) in platelets remains poorly defined. In previous studies, we have shown that TRPC6 regulates hemostasis and thrombosis, in mice. In the present studies, we employed a knockout mouse model system to characterize the role of TRPC6 in ROCE and platelet activation. It was observed that the TRPC6 deletion (Trpc6 -/- ) platelets displayed impaired elevation of intracellular calcium, i.e., defective ROCE. Moreover, these platelets also exhibited defects in a host of functional responses, namely aggregation, granule secretion, and integrin αIIbß3. Interestingly, the aforementioned defects were specific to the thromboxane receptor (TPR), as no impaired responses were observed in response to ADP or the thrombin receptor-activating peptide 4 (TRAP4). The defect in ROCE in the Trpc6 -/- was also observed with 1-oleoyl-2-acetyl-sn-glycerol (OAG). Finally, our studies also revealed that TRPC6 regulates clot retraction. Taken together, our findings demonstrate that TRPC6 directly regulates TPR-dependent ROCE and platelet function. Thus, TRPC6 may serve as a novel target for the therapeutic management of thrombotic diseases.

Investigation of a Thromboxane A2 Receptor-Based Vaccine for Managing Thrombogenesis.

BACKGROUND: Despite the well-established role for the thromboxane A2 receptor (TPR) in the development of thrombotic disorders, none of the antagonists developed to date has been approved for clinical use. To this end, we have previously shown that an antibody targeted against TPR's ligand-binding domain inhibits platelet activation and thrombus formation, without exerting any effects on hemostasis. Thus, the goal of the present studies is to design a novel TPR-based vaccine, demonstrate its ability to trigger an immune response, and characterize its antiplatelet and antithrombotic activity. METHODS AND RESULTS: We used a mouse keyhole limpet hemocyanin/peptide-based vaccination approach rationalized over the TPR ligand-binding domain (ie, the C-terminus of the second extracellular loop). The biological activity of this vaccine was assessed in the context of platelets and thrombotic diseases, and using a host of in vitro and in vivo platelet function experiments. Our results revealed that the TPR C-terminus of the second extracellular loop vaccine, in mice: (1) triggered an immune response, which resulted in the development of a C-terminus of the second extracellular loop antibody; (2) did not affect expression of major platelet integrins (eg, glycoprotein IIb-IIIa); (3) selectively inhibited TPR-mediated platelet aggregation, platelet-leukocyte aggregation, integrin glycoprotein IIb-IIIa activation, as well as dense and α granule release; (4) significantly prolonged thrombus formation; and (5) did so without impairing physiological hemostasis. CONCLUSIONS: Collectively, our findings shed light on TPR's structural biological features, and demonstrate that the C-terminus of the second extracellular loop domain may define a new therapeutic target and a TPR vaccine-based approach that should have therapeutic applications.

The acquisition of simple associations as observed in color-word contingency learning.

Three experiments investigated the learning of simple associations in a color-word contingency task. Participants responded manually to the print colors of 3 words, with each word associated strongly to 1 of the 3 colors and weakly to the other 2 colors. Despite the words being irrelevant, response times to high-contingency stimuli and to low-contingency stimuli quickly diverged. This high-low difference remained quite constant over successive blocks of trials, evidence of stable contingency learning. Inclusion of a baseline condition-an item having no color-word contingency-permitted separation of the contingency learning effect into 2 components: a cost due to low contingency and a benefit due to high contingency. Both cost and benefit were quick to acquire, quick to extinguish, and quick to reacquire. The color-word contingency task provides a simple way to directly study the learning of associations. (PsycINFO Database Record

An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm.

The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure elucidation (CASE) strategies seek to automatically propose a list of possible chemical structures in mixtures by utilizing chromatographic and spectroscopic methods. However, current CASE tools still cannot automatically solve structures for experienced natural product chemists. Here, we formulated the structural elucidation of natural products in a mixture as a computational problem by extending a list of scaffolds using a weighted side chain list after analyzing a collection of 243,130 natural products and designed an efficient algorithm to precisely identify the chemical structures. The complexity of such a problem is NP-complete. A dynamic programming (DP) algorithm can solve this NP-complete problem in pseudo-polynomial time after converting floating point molecular weights into integers. However, the running time of the DP algorithm degrades exponentially as the precision of the mass spectrometry experiment grows. To ideally solve in polynomial time, we proposed a novel iterative DP algorithm that can quickly recognize the chemical structures of natural products. By utilizing this algorithm to elucidate the structures of four natural products that were experimentally and structurally determined, the algorithm can search the exact solutions, and the time performance was shown to be in polynomial time for average cases. The proposed method improved the speed of the structural elucidation of natural products and helped broaden the spectrum of available compounds that could be applied as new drug candidates. A web service built for structural elucidation studies is freely accessible via the following link ( http://csccp.cmdm.tw/ ).

NP-StructurePredictor: Prediction of Unknown Natural Products in Plant Mixtures.

Identification of the individual chemical constituents of a mixture, especially solutions extracted from medicinal plants, is a time-consuming task. The identification results are often limited by challenges such as the development of separation methods and the availability of known reference standards. A novel structure elucidation system, NP-StructurePredictor, is presented and used to accelerate the process of identifying chemical structures in a mixture based on a branch and bound algorithm combined with a large collection of natural product databases. NP-StructurePredictor requires only targeted molecular weights calculated from a list of m/z values from liquid chromatography-mass spectrometry (LC-MS) experiments as input information to predict the chemical structures of individual components matching the weights in a mixture. NP-StructurePredictor also provides the predicted structures with statistically calculated probabilities so that the most likely chemical structures of the natural products and their analogs can be proposed accordingly. Four data sets consisting of different Chinese herbs with mixtures containing known compounds were selected for validation studies, and all their components were correctly identified and highly predicted using NP-StructurePredictor. NP-StructurePredictor demonstrated its applicability for predicting the chemical structures of novel compounds by returning highly accurate results from four different validation case studies.

G.A.M.E.: GPU-accelerated mixture elucidator.

GPU acceleration is useful in solving complex chemical information problems. Identifying unknown structures from the mass spectra of natural product mixtures has been a desirable yet unresolved issue in metabolomics. However, this elucidation process has been hampered by complex experimental data and the inability of instruments to completely separate different compounds. Fortunately, with current high-resolution mass spectrometry, one feasible strategy is to define this problem as extending a scaffold database with sidechains of different probabilities to match the high-resolution mass obtained from a high-resolution mass spectrum. By introducing a dynamic programming (DP) algorithm, it is possible to solve this NP-complete problem in pseudo-polynomial time. However, the running time of the DP algorithm grows by orders of magnitude as the number of mass decimal digits increases, thus limiting the boost in structural prediction capabilities. By harnessing the heavily parallel architecture of modern GPUs, we designed a "compute unified device architecture" (CUDA)-based GPU-accelerated mixture elucidator (G.A.M.E.) that considerably improves the performance of the DP, allowing up to five decimal digits for input mass data. As exemplified by four testing datasets with verified constitutions from natural products, G.A.M.E. allows for efficient and automatic structural elucidation of unknown mixtures for practical procedures. Graphical abstract .

Web Server for Peak Detection, Baseline Correction, and Alignment in Two-Dimensional Gas Chromatography Mass Spectrometry-Based Metabolomics Data.

Two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) is superior for chromatographic separation and provides great sensitivity for complex biological fluid analysis in metabolomics. However, GC×GC/TOF-MS data processing is currently limited to vendor software and typically requires several preprocessing steps. In this work, we implement a web-based platform, which we call GC2MS, to facilitate the application of recent advances in GC×GC/TOF-MS, especially for metabolomics studies. The core processing workflow of GC2MS consists of blob/peak detection, baseline correction, and blob alignment. GC2MS treats GC×GC/TOF-MS data as pictures and clusters the pixels as blobs according to the brightness of each pixel to generate a blob table. GC2MS then aligns the blobs of two GC×GC/TOF-MS data sets according to their distance and similarity. The blob distance and similarity are the Euclidean distance of the first and second retention times of two blobs and the Pearson's correlation coefficient of the two mass spectra, respectively. GC2MS also directly corrects the raw data baseline. The analytical performance of GC2MS was evaluated using GC×GC/TOF-MS data sets of Angelica sinensis compounds acquired under different experimental conditions and of human plasma samples. The results show that GC2MS is an easy-to-use tool for detecting peaks and correcting baselines, and GC2MS is able to align GC×GC/TOF-MS data sets acquired under different experimental conditions. GC2MS is freely accessible at http://gc2ms.web.cmdm.tw .

Mutagenicity in a Molecule: Identification of Core Structural Features of Mutagenicity Using a Scaffold Analysis.

With advances in the development and application of Ames mutagenicity in silico prediction tools, the International Conference on Harmonisation (ICH) has amended its M7 guideline to reflect the use of such prediction models for the detection of mutagenic activity in early drug safety evaluation processes. Since current Ames mutagenicity prediction tools only focus on functional group alerts or side chain modifications of an analog series, these tools are unable to identify mutagenicity derived from core structures or specific scaffolds of a compound. In this study, a large collection of 6512 compounds are used to perform scaffold tree analysis. By relating different scaffolds on constructed scaffold trees with Ames mutagenicity, four major and one minor novel mutagenic groups of scaffold are identified. The recognized mutagenic groups of scaffold can serve as a guide for medicinal chemists to prevent the development of potentially mutagenic therapeutic agents in early drug design or development phases, by modifying the core structures of mutagenic compounds to form non-mutagenic compounds. In addition, five series of substructures are provided as recommendations, for direct modification of potentially mutagenic scaffolds to decrease associated mutagenic activities.

Synthesis and inhibitory effects of novel pyrimido-pyrrolo-quinoxalinedione analogues targeting nucleoproteins of influenza A virus H1N1.

The influenza nucleoprotein (NP) is a single-strand RNA-binding protein and the core of the influenza ribonucleoprotein (RNP) particle that serves many critical functions for influenza replication. NP has been considered as a promising anti-influenza target. A new class of anti-influenza compounds, nucleozin and analogues were reported recently in several laboratories to inhibit the synthesis of influenza macromolecules and prevent the cytoplasmic trafficking of the influenza RNP. In this study, pyrimido-pyrrolo-quinoxalinedione (PPQ) analogues as a new class of novel anti-influenza agents are reported. Compound PPQ-581 was identified as a potential anti-influenza lead with EC50 value of 1 µM for preventing virus-induced cytopathic effects. PPQ produces similar anti-influenza effects as nucleozin does in influenza-infected cells. Treatment with PPQ at the beginning of H1N1 infection inhibited viral protein synthesis, while treatment at later times blocked the RNP nuclear export and the appearance of cytoplasmic RNP aggregation. PPQ resistant H1N1 (WSN) viruses were isolated and found to have a NPS377G mutation. Recombinant WSN carrying the S377G NP is resistant to PPQ in anti-influenza and RNA polymerase assays. The WSN virus with the NPS377G mutation also is devoid of the PPQ-mediated RNP nuclear retention and cytoplasmic aggregation. The NPS377G expressing WSN virus is not resistant to the reported NP inhibitors nucleozin. Similarly, the nucleozin resistant WSN viruses are not resistant to PPQ, suggesting that PPQ targets a different site from the nucleozin-binding site. Our results also suggest that NP can be targeted through various binding sites to interrupt the crucial RNP trafficking, resulting in influenza replication inhibition.

Rule-Based Prediction Models of Cytochrome P450 Inhibition.

Hepatotoxicity, drug-induced liver injury, and competitive Cytochrome P-450 (CYP) isozyme binding are serious problems associated with drug use. It would be favorable to avoid or to understand potential CYP inhibition at the developmental stages. However, current in silico CYP prediction models or available public prediction servers can provide only yes/no classification results for just one or a few CYP enzymes. In this study, we utilized a rule-based C5.0 algorithm with different descriptors, including PaDEL, Mold(2), and PubChem fingerprints, to construct rule-based inhibition prediction models for five major CYP enzymes-CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4-that account for 90% of drug oxidation or hydrolysis. We also developed a rational sampling algorithm for the selection of compounds in the training data set, to enhance the performance of these CYP prediction models. The optimized models include several improved features. First, the final models significantly outperformed all of the currently available models. Second, the final models can also be used for rapid virtual screening of a large set of compounds due to their ruleset-based nature. Moreover, such rule-based prediction models can provide rulesets for structural features related to the five major CYP enzymes. The five most significant rules for CYP inhibition were identified for each CYP enzymes and discussed. An example was chosen for each of the five CYP enzymes to demonstrate how rule-based models can be used to gain insights into structural features that correspond with CYP inhibitions. A newer version of the freely accessible CYP prediction server, CypRules, is presented here as a result of the aforementioned improvements.