Synthesis, modeling, and biological evaluation of anti-tubulin indole-substituted furanones.

Due to the central role of tubulin in various cellular functions, it is a validated target for anti-cancer therapeutics. However, many of the current tubulin inhibitors are derived from complex natural products and suffer from multidrug resistance, low solubility, toxicity issues, and/or the lack of multi-cancer efficacy. As such, there is a continued need for the discovery and development of new anti-tubulin drugs to enter the pipeline. Herein we report on a group of indole-substituted furanones that were prepared and tested for anti-cancer activity. Molecular docking studies showed positive correlations between favorable binding in the colchicine binding site (CBS) of tubulin and anti-proliferative activity, and the most potent compound was found to inhibit tubulin polymerization. These compounds represent a promising new structural motif in the search for small heterocyclic CBS cancer inhibitors.

Discovery of an indole-substituted furanone with tubulin polymerization inhibition activity.

Analogs of diarylpyrrolinone lead compound 1 were prepared and tested for anti-proliferative activity in U-937 cancer cells. Alterations of 1 focused on modifying the two nitrogen atoms: a) the pyrrolinone nitrogen atom was substituted with a propyl group or replaced with an oxygen atom (furanone), and b) the substituents on the indole nitrogen were varied. These changes led to the discovery of a furanone analog 3b with sub-micromolar anti-cancer potency and tubulin polymerization inhibition activity.

Validating estimates of prevalence of non-communicable diseases based on household surveys: the symptomatic diagnosis study.

BACKGROUND: Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing measurement systems in the developing world and the lack of biometry tests for non-communicable diseases. Diagnosis based on self-reported signs and symptoms ("Symptomatic Diagnosis," or SD) analyzed with computer-based algorithms may be a promising method for collecting timely and reliable information on non-communicable disease prevalence. The objective of this study was to develop and assess the performance of a symptom-based questionnaire to estimate prevalence of non-communicable diseases in low-resource areas. METHODS: As part of the Population Health Metrics Research Consortium study, we collected 1,379 questionnaires in Mexico from individuals who suffered from a non-communicable disease that had been diagnosed with gold standard diagnostic criteria or individuals who did not suffer from any of the 10 target conditions. To make the diagnosis of non-communicable diseases, we selected the Tariff method, a technique developed for verbal autopsy cause of death calculation. We assessed the performance of this instrument and analytical techniques at the individual and population levels. RESULTS: The questionnaire revealed that the information on health care experience retrieved achieved 66.1% (95% uncertainty interval [UI], 65.6-66.5%) chance corrected concordance with true diagnosis of non-communicable diseases using health care experience and 0.826 (95% UI, 0.818-0.834) accuracy in its ability to calculate fractions of different causes. SD is also capable of outperforming the current estimation techniques for conditions estimated by questionnaire-based methods. CONCLUSIONS: SD is a viable method for producing estimates of the prevalence of non-communicable diseases in areas with low health information infrastructure. This technology can provide higher-resolution prevalence data, more flexible data collection, and potentially individual diagnoses for certain conditions.

A shortened verbal autopsy instrument for use in routine mortality surveillance systems.

BACKGROUND: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. METHODS: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. RESULTS: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55%. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4%, 0.0%, and 0.6% for the adult, child, and neonatal modules, respectively. CONCLUSIONS: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50% without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

Improving performance of the Tariff Method for assigning causes of death to verbal autopsies.

BACKGROUND: Reliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method. METHODS: This study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database. RESULTS: For median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5%, 7.4%, and 14.9% for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0%, 13.5%, and 21.2%, respectively. Similar levels of improvement are seen in analyses without HCE. CONCLUSIONS: Tariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use.

Provider-patient communication: an illustrative case report of how provider language can influence patient prognosis.

Patient-provider communication can lead to unhelpful ideas and beliefs about a patient's condition, negatively impacting their clinical outcome. A 34-year-old male Veteran presented for an evaluation of high impact chronic low back pain. Previous interactions with various healthcare providers resulted in the Veteran viewing his condition as ominous and in need of intervention, however clinical findings did not support these beliefs. Our Veteran underwent six visits in the chiropractic clinic with treatment consisting of pain education, utilization of cognitive behavioral principles, active home care exercises and spinal manipulation, resulting in improvements in functional and objective outcome measures. This case report highlights the impact of misalignment between an early contact healthcare provider and patient misunderstanding of their condition on long term outcomes. It serves as an example of how physicians utilizing pathoanatomic explanations to describe a patient's chronic low back pain diagnosis can alter the patient's beliefs about their condition.

La communication entre le fournisseur de soins de santé et le patient peut conduire à des idées et à des croyances inutiles sur l'état du patient, ce qui a un impact négatif sur son résultat clinique. Un vétéran de 34 ans s'est présenté pour une évaluation d'une lombalgie chronique à fort impact. Des interactions antérieures avec divers fournisseurs de soins de santé ont amené le vétéran à considérer son état comme inquiétant et nécessitant une intervention, mais les résultats cliniques n'ont pas appuyé ces croyances. Notre ancien combattant a effectué six visites à la clinique chiropratique subissant chaque fois un traitement consistant en une éducation à la douleur, l'utilisation de principes cognitivo-comportementaux, des exercices de soins actifs à domicile et des manipulations vertébrales, ce qui a entraîné des améliorations dans les mesures de résultats fonctionnels et objectifs. Ce rapport de cas met en évidence l'impact d'un mauvais alignement entre un fournisseur de soins de santé de premier contact et l'incompréhension du patient de son état sur les résultats à long terme. Il sert d'exemple de la façon dont les médecins utilisant des explications d'anatomie pathologique pour décrire le diagnostic de lombalgie chronique d'un patient peuvent modifier l'idée que se fait le patient de son état.