Oxymel: A systematic review of preclinical and clinical studies.

Background: Oxymel is a functional beverage with a rich historical background of use in multiple societies. Various simple and compound oxymels are prescribed in certain complementary and traditional medical systems, including traditional Persian Medicine. In recent years, numerous clinical and preclinical studies have been conducted in the pharmacy and food industry to investigate the efficacy of various oxymel formulations. This article aims to systematically review and summarize interventional studies on oxymel in both clinical research and animal models. Methods: Relevant articles were searched in Embase, MEDLINE, Web of Science Core Collection, Scopus, and Google Scholar from inception to July 2023 using the keyword "Oxymel" and its equivalents in other languages. Animal and human interventional studies were selected from the search results for review. Results: This review includes twenty studies, comprising twelve clinical trials, two case studies, and six animal studies. The most commonly reported actions of oxymel include positive effects on the cardiovascular system, as well as antioxidant and anti-inflammatory properties. Furthermore, compound oxymel formulations have demonstrated additional benefits depending on the inclusion of specific medicinal herbs. Conclusion: Based on our findings, oxymel appears to be a valuable functional food for healthy individuals and a potentially effective and safe treatment option for managing certain diseases such as asthma, obesity, and type 2 diabetes. However, further clinical trials with larger sample sizes and longer durations are needed to fully elucidate the potential side effects and benefits of both simple and compound oxymels in various disease states.

Metabolomics-Based Biosignatures of Prostate Cancer in Patients Following Radiotherapy.

Metabolomics offers new promise for research on prostate cancer (PCa) and its personalized treatment. Metabolomic profiling of radiation-treated PCa patients is particularly important to reveal their new metabolomic status, and evaluate the radiation effects. In addition, bioinformatics-integrated metabolomics-based approaches for disease profiling and assessment of therapy could help develop precision biomarkers in a context of PCa. We report mass spectrometry-based untargeted (global) serum metabolomics findings from patients with PCa (n = 55) before and after treatment with stereotactic body radiation therapy (SBRT), and intensity-modulated radiation therapy (IMRT) with SBRT, and using parsimony phylogenetic analysis. Importantly, the radiation-treated serum metabolome of patients represented a unique robust cluster on a cladogram that was distinct from the pre-RT metabolome. The altered radiation responsive serum metabolome was defined by predominant aberrations in the metabolic pathways of nitrogen, pyrimidine, purine, porphyrin, alanine, aspartate, glutamate, and glycerophospholipid. Our findings collectively suggest that global metabolomics integrated with parsimony phylogenetics offer a unique and robust systems biology analytical platform for powerful unbiased determination of radiotherapy (RT)-associated biosignatures in patients with PCa. These new observations call for future translational research for evaluation of metabolomic biomarkers in PCa prognosis specifically, and response to radiation treatment broadly. Radiation metabolomics is an emerging specialty of systems sciences and clinical medicine that warrants further research and educational initiatives.

PhyloOncology: Understanding cancer through phylogenetic analysis.

Despite decades of research and an enormity of resultant data, cancer remains a significant public health problem. New tools and fresh perspectives are needed to obtain fundamental insights, to develop better prognostic and predictive tools, and to identify improved therapeutic interventions. With increasingly common genome-scale data, one suite of algorithms and concepts with potential to shed light on cancer biology is phylogenetics, a scientific discipline used in diverse fields. From grouping subsets of cancer samples to tracing subclonal evolution during cancer progression and metastasis, the use of phylogenetics is a powerful systems biology approach. Well-developed phylogenetic applications provide fast, robust approaches to analyze high-dimensional, heterogeneous cancer data sets. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Study of Clinical Survival and Gene Expression in a Sample of Pancreatic Ductal Adenocarcinoma by Parsimony Phylogenetic Analysis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the rapidly growing forms of pancreatic cancer with a poor prognosis and less than 5% 5-year survival rate. In this study, we characterized the genetic signatures and signaling pathways related to survival from PDAC, using a parsimony phylogenetic algorithm. We applied the parsimony phylogenetic algorithm to analyze the publicly available whole-genome in silico array analysis of a gene expression data set in 25 early-stage human PDAC specimens. We explain here that the parsimony phylogenetics is an evolutionary analytical method that offers important promise to uncover clonal (driver) and nonclonal (passenger) aberrations in complex diseases. In our analysis, parsimony and statistical analyses did not identify significant correlations between survival times and gene expression values. Thus, the survival rankings did not appear to be significantly different between patients for any specific gene (p > 0.05). Also, we did not find correlation between gene expression data and tumor stage in the present data set. While the present analysis was unable to identify in this relatively small sample of patients a molecular signature associated with pancreatic cancer prognosis, we suggest that future research and analyses with the parsimony phylogenetic algorithm in larger patient samples are worthwhile, given the devastating nature of pancreatic cancer and its early diagnosis, and the need for novel data analytic approaches. The future research practices might want to place greater emphasis on phylogenetics as one of the analytical paradigms, as our findings presented here are on the cusp of this shift, especially in the current era of Big Data and innovation policies advocating for greater data sharing and reanalysis.

China's Other Medical Systems: Recognizing Uyghur, Tibetan, and Mongolian Traditional Medicines.

BACKGROUND: Traditional Chinese medicine, as it is understood and adopted by those with a growing interest in complementary and alternative practices to biomedicine, is often used as an umbrella term for traditional medical practices from regions within and bordering the People's Republic of China. However, there are multiple distinct medical traditions in China, including that of the Uyghurs, Tibetans, and Mongolians. OBJECTIVE: It is important to recognize the commonalities and differences of these unique systems of medicine practiced by the 3 different cultures among China's borders. METHODS: Through an in-depth analysis of the individual beliefs and theories that form the foundation of each system, we trace the origins of the concepts that were synthesized into the Uyghur, Tibetan, and Mongolian medical systems. Furthermore, we compare diagnostic techniques and contrast treatment modalities among the 3 systems. DISCUSSION: We discuss humoral theory, constitution theory, elemental theory, organ theory, and yin and yang theory. We find that imbalance is the common cause of disease or illness, but the conditions and external factors that explain such imbalances differ among the Uyghur, Tibetan, and Mongolian systems. Through these comparisons, we seek to highlight the unique beliefs, practices, and treatments utilized by these cultures. CONCLUSION: The features and attributes, while not exclusive to each population, are nonetheless uniquely synthesized by each system and thus demonstrate the distinct nature of Uyghur, Tibetan, and Mongolian medical systems.

Computational Tools for Parsimony Phylogenetic Analysis of Omics Data.

High-throughput assays from genomics, proteomics, metabolomics, and next generation sequencing produce massive omics datasets that are challenging to analyze in biological or clinical contexts. Thus far, there is no publicly available program for converting quantitative omics data into input formats to be used in off-the-shelf robust phylogenetic programs. To the best of our knowledge, this is the first report on creation of two Windows-based programs, OmicsTract and SynpExtractor, to address this gap. We note, as a way of introduction and development of these programs, that one particularly useful bioinformatics inferential modeling is the phylogenetic cladogram. Cladograms are multidimensional tools that show the relatedness between subgroups of healthy and diseased individuals and the latter's shared aberrations; they also reveal some characteristics of a disease that would not otherwise be apparent by other analytical methods. The OmicsTract and SynpExtractor were written for the respective tasks of (1) accommodating advanced phylogenetic parsimony analysis (through standard programs of MIX [from PHYLIP] and TNT), and (2) extracting shared aberrations at the cladogram nodes. OmicsTract converts comma-delimited data tables through assigning each data point into a binary value ("0" for normal states and "1" for abnormal states) then outputs the converted data tables into the proper input file formats for MIX or with embedded commands for TNT. SynapExtractor uses outfiles from MIX and TNT to extract the shared aberrations of each node of the cladogram, matching them with identifying labels from the dataset and exporting them into a comma-delimited file. Labels may be gene identifiers in gene-expression datasets or m/z values in mass spectrometry datasets. By automating these steps, OmicsTract and SynpExtractor offer a veritable opportunity for rapid and standardized phylogenetic analyses of omics data; their model can also be extended to next generation sequencing (NGS) data. We make OmicsTract and SynpExtractor publicly and freely available for non-commercial use in order to strengthen and build capacity for the phylogenetic paradigm of omics analysis.

Analyzing heterogeneous complexity in complementary and alternative medicine research: a systems biology solution via parsimony phylogenetics.

Systems biology offers cutting-edge tools for the study of complementary and alternative medicine (CAM). The advent of 'omics' techniques and the resulting avalanche of scientific data have introduced an unprecedented level of complexity and heterogeneous data to biomedical research, leading to the development of novel research approaches. Statistical averaging has its limitations and is unsuitable for the analysis of heterogeneity, as it masks diversity by homogenizing otherwise heterogeneous populations. Unfortunately, most researchers are unaware of alternative methods of analysis capable of accounting for individual variability. This paper describes a systems biology solution to data complexity through the application of parsimony phylogenetic analysis. Maximum parsimony (MP) provides a data-based modeling paradigm that will permit a priori stratification of the study cohort(s), better assessment of early diagnosis, prognosis, and treatment efficacy within each stratum, and a method that could be used to explore, identify and describe complex human patterning.

Acupuncture at ST36 prevents chronic stress-induced increases in neuropeptide Y in rat.

Chronic stress, as seen in post-traumatic stress disorder, can exacerbate existing diseases. Electroacupuncture (EA) has been proposed to treat chronic stress, although information on its efficacy or mechanism(s) of action is limited. While many factors contribute to the chronic stress response, the sympathetic peptide, neuropeptide Y (NPY), has been shown to be elevated in chronic stress and is hypothesized to contribute to the physiological stress response. Our objective was to determine if EA at acupuncture point stomach 36 (ST(36)) is effective in mitigating cold stress-induced increase in NPY in rats. Both pretreatment and concomitant treatment with EA ST(36) effectively suppressed peripheral and central NPY after 14 d of cold stress (P < 0.05). The effect was specific, as NPY in Sham-EA rats was not different than observed in stress-only rats. Additionally, the effect of EA ST(36) was long-lasting, as NPY levels remained suppressed despite early cessation of EA ST(36), while exposure to cold stress was continued. In the paraventricular nucleus (PVN), it was notable that changes in NPY mirrored plasma NPY levels, and that the significant elevation in PVN Y1 receptor observed with stress was also prevented with EA ST(36). The findings indicate that EA ST(36) is effective in preventing one of the sympathetic pathways stimulated during chronic stress, and thus may be a useful adjunct therapy in stress-related disorders.

The EPI bioassay identifies natural compounds with estrogenic activity that are potent inhibitors of androgenic pathways in human prostate stromal and epithelial cells.

The reactive stromal phenotype is an important factor for prostate cancer progression and may be a new target for treatment and prevention. A new high efficiency preclinical protocol, the EPI bioassay, reflects the interaction of endocrine, paracrine and immune, (EPI) factors on induced androgen metabolism in human prostate reactive stroma. The bioassay is based on co-culturing human primary prostate stromal cells and LAPC-4 prostatic adenocarcinoma cells in a downscaled format of 96-well-plates for testing multiple doses of multiple target compounds. Metabolism of dehydroepiandrosterone (DHEA) with or without TGFß1-induced stimulation (D+T) of the reactive stroma phenotype was assessed by increased testosterone in the media and PSA production of the epithelial prostate cancer cells. Using the non-metabolizable androgen R1881, effects from direct androgen action were distinguished from stromal androgen production from DHEA. Stromal cell androgenic bioactivity was confirmed using conditioned media from D+T-treated stromal cell monocultures in an androgen-inducible AR screening assay. We further showed that both agonists to estrogen receptor (ER), DPN (ERß) and PPT (ERα), as well as estrogenic natural compounds including soy isoflavones attenuated D+T-induced PSA production. Studies with the pure ER agonists showed that activating either ERα or ERß could inhibit both D+T-mediated and R1881-mediated PSA production with the D+T effect being more pronounced. In conclusion, natural compounds with estrogenic activity and pure ER agonists are very potent inhibitors of stromal conversion of DHEA to androgenic metabolites. More studies are needed to characterize the mechanisms involved in estrogenic modulation of the endocrine-immune-paracrine balance of the prostate microenvironment.

Endometriosis gene expression heterogeneity and biosignature: a phylogenetic analysis.

Endometriosis is a multifactorial disease with poorly understood etiology, and reflecting an evolutionary nature where genetic alterations accumulate throughout pathogenesis. Our objective was to characterize the heterogeneous pathological process using parsimony phylogenetics. Gene expression microarray data of ovarian endometriosis obtained from NCBI database were polarized and coded into derived (abnormal) and ancestral (normal) states. Such alterations are referred to as synapomorphies in a phylogenetic sense (or biomarkers). Subsequent gene linkage was modeled by Genomatix BiblioSphere Pathway software. A list of clonally shared derived (abnormal) expressions revealed the pattern of heterogeneity among specimens. In addition, it has identified disruptions within the major regulatory pathways including those involved in cell proliferation, steroidogenesis, angiogenesis, cytoskeletal organization and integrity, and tumorigenesis, as well as cell adhesion and migration. Furthermore, the analysis supported the potential central involvement of ESR2 in the initiation of endometriosis. The pathogenesis mapping showed that eutopic and ectopic lesions have different molecular biosignatures.

Stress biomarkers in medical students participating in a mind body medicine skills program.

Georgetown University School of Medicine offers an elective Mind-Body Medicine Skills (MBMS) course to medical students to promote self-care and self-awareness. Participating medical students reported better management of academic stress and well-being than non-participants. In this study, we sought to assess the stress-reducing effects of MBMS by measuring physiological changes in first-year medical students. Saliva samples were collected before (January, time 1 (T1)-pre-intervention) and upon completion of the course (May, time 2 (T2p)-post-intervention), as well as from non-participating medical students (May, time 2 (T2c)-control). The T2p and T2c collections coincided with the period of final examinations. Cortisol, dehydroepiandrosterone-sulfate (DHEA-S), testosterone and secretory immunoglobulin A (sIgA) were measured. The mean morning salivary cortisol at T2p was 97% of the mean at baseline T1 which was significantly lower than for T2c (2.4) (95% confidence interval (CI) 0.57-1.60, P = .001); DHEA-S showed similar pattern as cortisol where the T2p levels were significantly lower than T2c (P < .001) in both morning and evening collections. Testosterone ratio at T2p (0.85) was also lower than T2c (1.6) (95% CI 0.53-1.3, P = .01). sIgA levels were not statistically different. On direct comparison, the T2c and T2p means were significantly different for all cortisol, DHEA-S and testosterone values. Participants maintained their hormonal balance within the normal range throughout the academic semester while the control group showed significantly increased levels, probably exacerbated by the end of the semester exam stress. To our knowledge, this is the first study to assess the physiologic benefits of a MBMS program in medical students.

Biomarkers in the age of omics: time for a systems biology approach.

Limitations to biomarker discovery are not only technical or bioinformatic but conceptual as well. In our attempt to offer a solution, we are highlighting three issues that we think are limiting progress in biomarkers discovery. First, the confusion stemming from the imposition of a pathology-type immunohistochemical marker (IHCM) concept on omics data without fully understanding the characteristics and limitations of IHCMs as applied in clinical pathology. Second, the lack of serious consideration for the scope of disease heterogeneity. Third, the refusal of the biomedical community to borrow from other biological disciplines their well established methods for dealing with heterogeneity. Therefore, real progress in biomarker discovery will be attained when we recognize that an omics biomarker cannot be assigned and validated without a priori data modeling and subtyping of the disease itself to reveal the extent of its heterogeneity, and its omics' clonal aberrations (drivers) underlying its subtypes and pathways' diversity. To further support our viewpoints, we are contributing a novel a systems biology method such as parsimony phylogenetic approach for disease modeling prior to biomarker circumscription. As an analytical approach that has been successfully used for a half of a century in other biological disciplines, parsimony phylogenetics simultaneously achieves several objectives: it provides disease modeling in a hierarchical phylogenetic classification, identifies biomarkers as the shared derived expressions or mutations--synapomorphies, constructs the omics profiles of specimens based on the most parsimonious arrangement of their heterogeneous data, and permits network profiling of affected signaling pathways as the biosignature of disease classes.

Molecular mechanisms mediating the effect of mono-(2-ethylhexyl) phthalate on hormone-stimulated steroidogenesis in MA-10 mouse tumor Leydig cells.

Di-(2-ethylhexyl) phthalate, a widely used plasticizer, and its active metabolite, mono-(2-ethylhexyl) phthalate (MEHP), have been shown to exert adverse effects on the reproductive tract in developing and adult animals. As yet, however, the molecular mechanisms by which they act are uncertain. In the present study, we address the molecular and cellular mechanisms underlying the effects of MEHP on basal and human chorionic gonadotropin (hCG)-stimulated steroid production by MA-10 Leydig cells, using a systems biology approach. MEHP induced dose-dependent decreases in hCG-stimulated steroid formation. Changes in mRNA and protein expression in cells treated with increasing concentrations of MEHP in the presence or absence of hCG were measured by gene microarray and protein high-throughput immunoblotting analyses, respectively. Expression profiling indicated that low concentrations of MEHP induced the expression of a number of genes that also were expressed after hCG stimulation. Cross-comparisons between the hCG and MEHP treatments revealed two genes, Anxa1 and AR1. We suggest that these genes may be involved in a new self-regulatory mechanism of steroidogenesis. The MEHP-induced decreases in hCG-stimulated steroid formation were paralleled by increases in reactive oxygen species generation, with the latter mediated by the Cyp1a1 gene and its network. A model for the mechanism of MEHP action on MA-10 Leydig cell steroidogenesis is proposed.

Algorithmic assessment of vaccine-induced selective pressure and its implications on future vaccine candidates.

Posttrial assessment of a vaccine's selective pressure on infecting strains may be realized through a bioinformatic tool such as parsimony phylogenetic analysis. Following a failed gonococcal pilus vaccine trial of Neisseria gonorrhoeae, we conducted a phylogenetic analysis of pilin DNA and predicted peptide sequences from clinical isolates to assess the extent of the vaccine's effect on the type of field strains that the volunteers contracted. Amplified pilin DNA sequences from infected vaccinees, placebo recipients, and vaccine specimens were phylogenetically analyzed. Cladograms show that the vaccine peptides have diverged substantially from their paternal isolate by clustering distantly from each other. Pilin genes of the field clinical isolates were heterogeneous, and their peptides produced clades comprised of vaccinated and placebo recipients' strains indicating that the pilus vaccine did not exert any significant selective pressure on gonorrhea field strains. Furthermore, sequences of the semivariable and hypervariable regions pointed out heterotachous rates of mutation and substitution.

Using Basic Science to Develop an Innovative Program in Complementary and Alternative Medicine.

The growing interest in Complementary and Alternative Medicine (CAM) and the increasing incorporation of its modalities in the United States' healthcare system have exposed a number of problems in the field. These include a shortage of qualified CAM providers, scarcity of evidence-based research, lack of trained scientists in the field, and the ubiquitous marketing of frequently uncontrolled CAM products. Thus, the development of a comprehensive and scientifically sound educational infrastructure has become a crucial initial step in redirecting these adverse trends.With support from the NIH-sponsored curricular CAM initiative, faculty from the department of physiology and biophysics at Georgetown University developed a M.S. program in CAM in 2003. This unique, first of its kind, science-based graduate program offers a master's degree (MS) in physiology with an emphasis on CAM. The CAM-MS degree in physiology is designed to enable students to critically assess various CAM modalities, apply scientific rigor, and carry out evidence-based CAM research. The curriculum includes core science courses and CAM-related classes. Additionally, in order to emphasize the application of academic knowledge and further strengthen problem-solving skills, the students complete an eight-week summer practicum in a professional CAM-related environment.Here, we report on our innovative and interdisciplinary CAM graduate program where creative teaching is implemented by basic scientists and enhanced by the application of their disciplines in tandem with the clinical expertise of CAM practitioners in the community. Thus, the faculty in the Department of Physiology & Biophysics is developing emerging cross disciplinary areas of study and interest in order to prepare new generations of future physicians, health professionals, educators, and researchers capable of objectively assessing the safety and efficacy of various CAM modalities, and introducing scientific rigor to much needed research into the various aspects of CAM therapies.

Modeling withdrawal syndrome in zebrafish.

The zebrafish (Danio rerio) is rapidly becoming a popular model species in behavioral neuroscience research. Zebrafish behavior is robustly affected by environmental and pharmacological manipulations, and can be examined using exploration-based paradigms, paralleled by analysis of endocrine (cortisol) stress responses. Discontinuation of various psychotropic drugs evokes withdrawal in both humans and rodents, characterized by increased anxiety. Sensitivity of zebrafish to drugs of abuse has been recently reported in the literature. Here we examine the effects of ethanol, diazepam, morphine and caffeine withdrawal on zebrafish behavior. Overall, discontinuation of ethanol, diazepam and morphine produced anxiogenic-like behavioral or endocrine responses, demonstrating the utility of zebrafish in translational research of withdrawal syndrome.

Understanding behavioral and physiological phenotypes of stress and anxiety in zebrafish.

The zebrafish (Danio rerio) is emerging as a promising model organism for experimental studies of stress and anxiety. Here we further validate zebrafish models of stress by analyzing how environmental and pharmacological manipulations affect their behavioral and physiological phenotypes. Experimental manipulations included exposure to alarm pheromone, chronic exposure to fluoxetine, acute exposure to caffeine, as well as acute and chronic exposure to ethanol. Acute (but not chronic) alarm pheromone and acute caffeine produced robust anxiogenic effects, including reduced exploration, increased erratic movements and freezing behavior in zebrafish tested in the novel tank diving test. In contrast, ethanol and fluoxetine had robust anxiolytic effects, including increased exploration and reduced erratic movements. The behavior of several zebrafish strains was also quantified to ascertain differences in their behavioral profiles, revealing high-anxiety (leopard, albino) and low-anxiety (wild type) strains. We also used LocoScan (CleverSys Inc.) video-tracking tool to quantify anxiety-related behaviors in zebrafish, and dissect anxiety-related phenotypes from locomotor activity. Finally, we developed a simple and effective method of measuring zebrafish physiological stress responses (based on a human salivary cortisol assay), and showed that alterations in whole-body cortisol levels in zebrafish parallel behavioral indices of anxiety. Collectively, our results confirm zebrafish as a valid, reliable, and high-throughput model of stress and affective disorders.

Medical students' attitudes to complementary and alternative medicine: further validation of the IMAQ and findings from an international longitudinal study.

BACKGROUND: Current research mainly employs cross-sectional designs to examine changes in medical students' attitudes towards complementary and alternative medicine (CAM). AIMS: This paper reports the findings of a longitudinal study to further validate the Integrative Medicine Attitude Questionnaire (IMAQ) and examine changes in medical students' attitudes over 3 years. METHODS: A total of 154 medical students from four schools in three countries completed a modified version of the IMAQ during their first (T1) and fourth year (T2). RESULTS: We established the validity of a three-factor model for the IMAQ: (1) attitudes towards holism; (2) attitudes towards the effectiveness of CAM therapies, and (3) attitudes towards introspection and the doctor-patient relationship. We found that IMAQ factor scores did not differ significantly from T1 to T2, emphasizing the relative stability in attitudes across time. Various student characteristics were significantly associated with IMAQ factor scores at T2: age, gender, CAM use, CAM education and school; and two variables (gender and CAM use) predicted changes in medical students' attitudes between T1 and T2. CONCLUSIONS: We urge medical educators to continue exploring medical students' attitude changes towards CAM and we provide examples of what further research is needed.

Phylogenetic modeling of heterogeneous gene-expression microarray data from cancerous specimens.

The qualitative dimension of gene expression data and its heterogeneous nature in cancerous specimens can be accounted for by phylogenetic modeling that incorporates the directionality of altered gene expressions, complex patterns of expressions among a group of specimens, and data-based rather than specimen-based gene linkage. Our phylogenetic modeling approach is a double algorithmic technique that includes polarity assessment that brings out the qualitative value of the data, followed by maximum parsimony analysis that is most suitable for the data heterogeneity of cancer gene expression. We demonstrate that polarity assessment of expression values into derived and ancestral states, via outgroup comparison, reduces experimental noise; reveals dichotomously expressed asynchronous genes; and allows data pooling as well as comparability of intra- and interplatforms. Parsimony phylogenetic analysis of the polarized values produces a multidimensional classification of specimens into clades that reveal shared derived gene expressions (the synapomorphies); provides better assessment of ontogenic pathways and phyletic relatedness of specimens; efficiently utilizes dichotomously expressed genes; produces highly predictive class recognition; illustrates gene linkage and multiple developmental pathways; provides higher concordance between gene lists; and projects the direction of change among specimens. Further implication of this phylogenetic approach is that it may transform microarray into diagnostic, prognostic, and predictive tool.