Impact assessment of self-medication on COVID-19 prevalence in Gauteng, South Africa, using an age-structured disease transmission modelling framework.

OBJECTIVE: To assess the impact of self-medication on the transmission dynamics of COVID-19 across different age groups, examine the interplay of vaccination and self-medication in disease spread, and identify the age group most prone to self-medication. METHODS: We developed an age-structured compartmentalized epidemiological model to track the early dynamics of COVID-19. Age-structured data from the Government of Gauteng, encompassing the reported cumulative number of cases and daily confirmed cases, were used to calibrate the model through a Markov Chain Monte Carlo (MCMC) framework. Subsequently, uncertainty and sensitivity analyses were conducted on the model parameters. RESULTS: We found that self-medication is predominant among the age group 15-64 (74.52%), followed by the age group 0-14 (34.02%), and then the age group 65+ (11.41%). The mean values of the basic reproduction number, the size of the first epidemic peak (the highest magnitude of the disease), and the time of the first epidemic peak (when the first highest magnitude occurs) are 4.16499, 241,715 cases, and 190.376 days, respectively. Moreover, we observed that self-medication among individuals aged 15-64 results in the highest spreading rate of COVID-19 at the onset of the outbreak and has the greatest impact on the first epidemic peak and its timing. CONCLUSION: Studies aiming to understand the dynamics of diseases in areas prone to self-medication should account for this practice. There is a need for a campaign against COVID-19-related self-medication, specifically targeting the active population (ages 15-64).

Prolonged Release Niosomes For Ocular Delivery of Loteprednol: Ocular Distribution Assessment on Dry Eye Disease Induced Rabbit Model.

Loteprednol etabonate (LE) is a topical corticosteroid for the symptomatic management of ocular conditions, encompassing both allergic and infectious etiologies. Owing to the dynamic and static barriers of the eye, LE exhibits significantly low bioavailability, necessitating an increase in the frequency of drug administration. The objective of this study is to overcome the limitations by developing niosomal systems loaded with LE. Design of Experiments (DoE) approach was used for the development of optimal niosome formulation. The optimal formulation was characterized using DLS, FT-IR, and DSC analysis. In vitro and ex vivo release studies were performed to demonstrate drug release patterns. After that HET-CAM evaluation was conducted to determine safety profile. Then, in vivo studies were carried out to determine therapeutic activity of niosomes. Zeta potential (ZP), particle size, polydispersity index (PI), and encapsulation efficacy (EE) were -33.8 mV, 89.22 nm, 0.192, and 89.6%, respectively. Medicated niosomes had a broad distribution within rabbit eye tissues and was absorbed by the aqueous humor of the bovine eye for up to 6 h after treatment. Cumulative permeated drug in the bovine eye and rabbit eye were recorded 52.45% and 54.8%, respectively. No irritation or hemorrhagic situation was observed according to the results of HET-CAM study. Thus, novel LE-loaded niosomal formulations could be considered as a promising treatment option for the dry-eye-disease (DED) due to enhanced bioavailability and decreased side effects.

Explorative cost-effectiveness analysis of colorectal cancer recurrence detection with next-generation sequencing liquid biopsy in Spain, France, and Germany.

Background: Next-generation sequencing liquid biopsy (NGS-LB) for colorectal cancer (CRC) detection and surveillance remains an expensive technology as economies of scale have not yet been realized. Nevertheless, the cost of sequencing has decreased while sensitivity has increased, raising the question of whether cost-effectiveness (CE) has already been achieved from the perspective of European healthcare systems. Objectives: This health economic (HE) modeling study explores the CE of NGS-LB for CRC based on direct treatment costs compared to standard care without liquid biopsy in Spain, France, and Germany. Methods: A structured literature search was used to collect evidence from 2009 to 2020 on the stage-dependent quality of life (quality-adjusted life-years, QALY), efficacy, and total direct treatment costs (TDC) of NGS-LB. A decision-analytic Markov model was developed. Over the remaining lifetime, cumulative life expectancy (LE), TDC, and QALYs were calculated for 60-year-old men and women in CRC stage III with different assumed effects of NGS-LB of 1% or 3% on improved survival and reduced stage progression, respectively. Results: The use of NGS-LB increases LE by 0.19 years in Spanish men (France: 0.19 years, Germany: 0.13 years) and by 0.21 years in Spanish women (France: 0.21 years, Germany: 0.14 years), respectively. The 3% discounted cost per QALY gained was 35,571.95 € for Spanish men (France: 31,705.15 €, Germany: 37,537.68 €) and 35,435.71 € for Spanish women (France: 31,295.57 €, Germany: 38,137.08 €) in the scenario with 3% improved survival and reduced disease progression. Compared to the other two countries, Germany has by far the highest TDC, which can amount to >80k euros in the last treatment year. Conclusion: In this explorative HE modeling study, NGS-LB achieves generally accepted CE levels in CRC treatment from the health system perspective in three major European economies under assumptions of small improvements in cancer recurrence and survival. Confirmation of these findings through clinical trials is encouraged.

Is it worthwhile to use next generation liquid biopsy for cancer recurrence detection on patients with colorectal cancer? Colon cancer is common. Worldwide, almost one million people die from it every year. Next Generation Sequencing Liquid Biopsy is a very sensitive technology for detecting cancer cells and their genetic information in the blood. Therefore, it is a good way to detect cancer and to detect early recurrence of a previously treated tumor. This test procedure is not yet used very often. Therefore, it is still expensive. Furthermore, there are still no studies that have demonstrated that and how liquid biopsy can aid doctors and patients after initial treatment. The research team of this study has developed an analytical model to investigate what performance liquid biopsy should have to demonstrate an affordable patient benefit in terms of quality of life, survival and cost per additional quality-adjusted life year gained. To do this, they studied the existing medical literature and many cost studies on colorectal cancer for the countries of Spain, France and Germany to feed their model. Then, they made different assumptions about the performance of liquid biopsy and did calculations. In the process, they also particularly examined the significance of specific influencing factors such as costs or disease progression in so-called sensitivity analyses. As a result, the authors found that there are large differences in treatment costs for colorectal cancer between the three countries Spain, France and Germany. Furthermore, even small improvements in the progression of cancer and the survival of cancer patients lead to the economic efficiency of liquid biopsy for the health care system. However, these are still thought experiments, so the research team of this study says that there should be further clinical trials to assess the impact of liquid biopsy on cancer progression and patient survival by using this technology. By this, one could confirm or contradict the authors' educated assumptions and possibly pave a new way towards medical progress for people with colorectal cancer.

SEIR-diffusion modeling and stability analysis of supply chain finance based on blockchain technology.

Inadequate information sharing and difficult information diffusion are the main factors that cause upstream and downstream enterprises to default on supply chain finance. Blockchain technology, which exploits distributed storage and a consensus mechanism, can provide effective solutions to overcome these problems such as information sharing. When blockchain technology is adopted by the enterprises that comprise the supply chain finance business, this technology shows a diffusion trend. As a result, the decision pertaining to the application of novel technologies is affected. Therefore, to investigate the diffusion mechanism pertaining to the blockchain technology that is applied in supply chain finance, the study exploited the idea of a class of SEIR infectious disease models, and built a blockchain model that considers the supply chain financial system. Besides, the study verifies the stability of the model by constructing a Lyapunov function. The results indicate that the basic reproduction number determines the proliferation of the blockchain technology. When the basic reproduction number is less than 1, the proliferation of the blockchain technology that is applied in supply chain finance system would terminate. By contrast, when the basic reproduction number is greater than 1, during the average infection period, the number of non-adopting enterprises that accept the blockchain technology becomes greater than 1, which can maintain a continuous impact on supply chain finance system. Over time, the number of enterprises that accept blockchain technology tends to be stable. Through numerical simulations that consider the influencing parameters pertaining to the basic regeneration number, which has important effect on blockchain technology diffusion, we enlarge the diffusion efficiency and increase the transfer rate of potential on-chain enterprises or decrease the default exit rate. As a result, we facilitate the diffusion of blockchain technology in the system.

Experience of Daily Life with Generalized Myasthenia Gravis: A Qualitative Investigation and Assessment of Instrument Content Validity.

INTRODUCTION: Generalized myasthenia gravis (gMG) is a rare autoimmune disease. Symptoms of gMG are diverse, and understanding of their impact on patients is limited. This qualitative study aimed to provide an in-depth exploration of patients' daily experiences of gMG. METHODS: Published qualitative studies were reviewed to identify the most important signs, symptoms, and functional impacts related to the patient experience in gMG. Semi-structured hybrid concept elicitation interviews (allowing spontaneous generation of disease concepts) and cognitive debriefing interviews (assessing the validity of existing disease assessments) were conducted with clinicians and adult patients with gMG. Signs, symptoms, and impacts were reviewed to understand which were most salient (i.e., reported by at least 50% of patients, with disturbance rating 5 or higher [10-point numeric scale]); concept saturation was also assessed. The disease conceptual model was updated. Existing clinical outcomes assessments (COAs) that capture how patients feel, function, and survive were assessed. RESULTS: Interviews with patients (n = 24) identified seven new signs and symptoms and 37 new impacts compared with the literature. Concept saturation was reached. Signs and symptoms identified by patients as most important (salient) were shortness of breath, general fatigue, muscle weakness of arms, legs, and neck, dysphonia, dysarthria, trouble swallowing liquids, choking, and heat sensitivity. Patient-identified salient impacts were work life, depression, difficulty walking, grooming hair, showering, and brushing teeth, eating, personal relationships, family life, and participating in social activities. Clinicians considered ocular, respiratory, swallowing, speech/talking, and extremity function as key clinical manifestations of gMG. Patients and clinicians found clinical outcome assessments (COAs) to be conceptually relevant and comprehensive. CONCLUSION: This research provides a holistic understanding of gMG signs, symptoms, and impacts experienced by patients, as observed by patients and clinicians. The conceptual model of gMG highlights the range of signs, symptoms, and impacts that adult patients with gMG experience in their everyday lives, emphasizing the humanistic impact and unmet needs.

Bias and bias-correction for individual-level models of infectious disease.

Accurate infectious disease models can help scientists understand how an ongoing disease epidemic spreads and forecast the course of epidemics more effectively. Considering various factors that affect the spread of a disease (e.g. geographical, social, domestic, and genetic), a class of individual-level models (ILMs) was developed to incorporate population heterogeneity. In these models, inferences are developed within a Bayesian Markov chain Monte Carlo (MCMC) framework, obtaining posterior estimates of model parameters. The issues of bias of parameter estimates, and methods for bias correction, have been widely studied with respect to many of the most established and commonly used statistical models and associated methods of parameter estimation. However, these methods are not directly applicable to infectious disease data. This paper investigates circumstances in which ILM parameter estimates may be biased in some simple disease system scenarios. Further, we aim to compare the performance of bias-corrected estimates of ILM parameters, using simulation, with the posterior estimates of the parameter. We also discuss the factors that affect the performance of these estimators.

Alcohol use disorder and disability insurance in Switzerland: the attitudes and views of lawyers, insurance medical experts, and addiction-specialist therapists.

BACKGROUND: According to a landmark decision by the Swiss Federal Supreme Court, people with a substance use disorder (SUD) are now eligible for disability benefits if their disorder impairs their ability to work. Alcohol use disorder (AUD) is one of the most common SUDs in Switzerland and is associated with high societal and economic costs. This study aimed to gain an in-depth understanding of the views of professional stakeholder groups regarding AUD and their opinions on the new legal precedent. METHODS: Swiss social insurance lawyers, insurance medical experts, and addiction-specialist therapists (N = 79) answered an online questionnaire. Due to violations of the assumption of normality, non-parametric tests are reported in most cases. RESULTS: Therapists held significantly higher regard for patients with AUD than both lawyers and insurance medical experts. All three groups strongly supported a disease view of AUD but agreed significantly less that it was a disease like cancer, suggesting that AUDs might be seen as at least partially self-inflicted. Overall, moralist views of AUD received considerably less support than the disease view, with lawyers agreeing with moralist views more than therapists. All groups were well-informed and largely supportive about the new legal precedent. When asked about stipulating participation in medical treatment to mitigate damages associated with a claim, attending therapy was supported the most amongst the groups (80% of participants felt this was somewhat or fully appropriate), followed by a reduction in drinking quantity (58%), and abstinence (18%). In all three groups, we identified associations between certain views and opinions on AUD and support for the new legal precedent. CONCLUSIONS: Whilst there were differences between the stakeholder groups in their regard for and views of AUD, all three adopted a clear harm-reduction approach with respect to measures to mitigate damages associated with the insurance disability claim. A possible connection of this stance with the Swiss national drug policy in recent years is discussed together with limitations of the study and practical implications of the findings.

Use of mathematical modelling to assess respiratory syncytial virus epidemiology and interventions: a literature review.

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection worldwide, resulting in approximately sixty thousand annual hospitalizations of< 5-year-olds in the United States alone and three million annual hospitalizations globally. The development of over 40 vaccines and immunoprophylactic interventions targeting RSV has the potential to significantly reduce the disease burden from RSV infection in the near future. In the context of RSV, a highly contagious pathogen, dynamic transmission models (DTMs) are valuable tools in the evaluation and comparison of the effectiveness of different interventions. This review, the first of its kind for RSV DTMs, provides a valuable foundation for future modelling efforts and highlights important gaps in our understanding of RSV epidemics. Specifically, we have searched the literature using Web of Science, Scopus, Embase, and PubMed to identify all published manuscripts reporting the development of DTMs focused on the population transmission of RSV. We reviewed the resulting studies and summarized the structure, parameterization, and results of the models developed therein. We anticipate that future RSV DTMs, combined with cost-effectiveness evaluations, will play a significant role in shaping decision making in the development and implementation of intervention programs.

Comparison of static and dynamic models of maternal immunization to prevent infant pertussis in Brazil.

BACKGROUND: This paper compares cost-effectiveness results from two models of maternal immunization to prevent pertussis in infants in Brazil, one static, one dynamic, to explore when static models are adequate for public health decisions and when the extra effort required by dynamic models is worthwhile. METHODS: We defined two scenarios to explore key differences between static and dynamic models, herd immunity and time horizon. Scenario 1 evaluates the incremental cost/DALY of maternal acellular pertussis (aP) immunization as routine infant vaccination coverage ranges from low/moderate up to, and above, the threshold at which herd immunity begins to eliminate pertussis. Scenario 2 compares cost-effectiveness estimates over the models' different time horizons. Maternal vaccine prices of $9.55/dose (base case) and $1/dose were evaluated. RESULTS: The dynamic model shows that maternal immunization could be cost-saving as well as life-saving at low levels of infant vaccination coverage. When infant coverage reaches the threshold range (90-95%), it is expensive: the dynamic model estimates that maternal immunization costs $2 million/DALY at infant coverage > 95% and maternal vaccine price of $9.55/dose; at $1/dose, cost/DALY is $200,000. By contrast, the static model estimates costs/DALY only modestly higher at high than at low infant coverage. When the models' estimates over their different time horizons are compared at infant coverage < 90-95%, their projections fall in the same range. CONCLUSIONS: Static models may serve to explore an intervention's cost-effectiveness against infectious disease: the direction and principal drivers of change were the same in both models. When, however, an intervention too small to have significant herd immunity effects itself, such as maternal aP immunization, takes place against a background of vaccination in the rest of the population, a dynamic model is crucial to accurate estimates of cost-effectiveness. This finding is particularly important in the context of widely varying routine infant vaccination rates globally. CLINICAL TRIAL REGISTRY: Clinical Trial registry name and registration number: Not applicable.

Cost analysis of vaccination in tick-mouse transmission of Lyme disease.

Lyme disease is one of the most prevalent and fastest growing vector-borne bacterial illnesses in the United States, with over 25,000 new confirmed cases every year. Humans contract the bacterium Borrelia burgdorferi through the bite of the tick Ixodes scapularis. The tick can receive the bacterium from a variety of small mammal and bird species, but the white-footed mouse Peromyscus leucopus is the primary reservoir in the northeastern United States, especially near human settlement. The tick's life cycle and behavior depend greatly on the season, with different stages of tick biting at different times. Reducing the infection in the tick-mouse cycle may greatly lower human Lyme incidence in some areas. However, research on the effects of various mouse-targeted interventions is limited. One particularly promising method involves administering vaccine pellets to white-footed mice through special bait boxes. In this study, we develop and analyze a mathematical model consisting of a system of nonlinear difference equations to understand the complex transmission dynamics and vector demographics in both tick and mice populations. We evaluate to what extent vaccination of white-footed mice can affect Lyme incidence in I. scapularis, and under which conditions this method saves money in preventing Lyme disease. We find that, in areas with high human risk, vaccination can eliminate mouse-tick transmission of B. burgdorferi while saving money.

Comparison of stochastic and deterministic frameworks in dengue modelling.

We perform estimations of compartment models for dengue transmission in rural Cambodia with increasing complexity regarding both model structure and the account for stochasticity. On the one hand, we successively account for three embedded sources of stochasticity: observation noise, demographic variability and environmental hazard. On the other hand, complexity in the model structure is increased by introducing vector-borne transmission, explicit asymptomatic infections and interacting virus serotypes. Using two sources of case data from dengue epidemics in Kampong Cham (Cambodia), models are estimated in the bayesian framework, with Markov Chain Monte Carlo and Particle Markov Chain Monte Carlo. We highlight the advantages and drawbacks of the different formulations in a practical setting. Although in this case the deterministic models provide a good approximation of the mean trajectory for a low computational cost, the stochastic frameworks better reflect and account for parameter and simulation uncertainty.

Assessment of Clinical Meaningfulness of Endpoints in the Generation Program by the Insights to Model Alzheimer's Progression in Real Life (iMAP) Study.

We are launching the Insights to Model Alzheimer's Progression in Real Life study in parallel with the Alzheimer Prevention Initiative Generation Program. This is a 5-year, multinational, prospective, longitudinal, non-interventional cohort study that will collect data across the spectrum of Alzheimer's disease. The primary objective is to assess the ability of the Alzheimer's Prevention Initiative Cognitive Composite Test Score and Repeatable Battery for the Assessment of Neuropsychological Status to predict clinically meaningful outcomes such as diagnosis of mild cognitive impairment or dementia due to Alzheimer's disease, and change in Clinical Dementia Rating - Global Score. This study is the first large-scale, prospective effort to establish the clinical meaningfulness of cognitive test scores that track longitudinal decline in preclinical Alzheimer's disease. This study is also expected to contribute to our understanding of the relationships among outcomes in different stages of Alzheimer's disease as well as models of individual trajectories during the course of the disease.

The rediscovery of the social side of medicine: philosophy and value of the International Classification of Functioning, Disability and Health (ICF).

Medicine is at risk of sliding into a sole repair service for the malfunction of organs. But the patients' hope and confidence towards doctors practicing this repair work go far beyond that: after acute medical treatment many patients suffer from chronic impairments due to the natural course of the disease or as a result of medical interventions. Despite resulting handicaps, patients aim at participating in family and social life, retaining a workplace and receiving support to remain a valued member of the family and the community. Doctors should therefore not only concentrate on the natural science and technological part of medicine, but also consider the background of their patients, their involvement in life situations including environmental and personal factors, as these may influence functioning and disability as facilitators or barriers. Health Insurances Companies must organize, finance and control the achievements of the post-acute treatment process with the goal of participation. "Public Health" must combine and assess individual views to prepare reasonable population based social, economic and political decisions. The philosophy and structure of the International Classification of Functioning, Disability and Health (ICF) is supporting this attitude of medicine, to complement the International Classification of Diseases (ICD) as a basis for health reports.

Model-based analysis of an outbreak of bubonic plague in Cairo in 1801.

Bubonic plague has caused three deadly pandemics in human history: from the mid-sixth to mid-eighth century, from the mid-fourteenth to the mid-eighteenth century and from the end of the nineteenth until the mid-twentieth century. Between the second and the third pandemics, plague was causing sporadic outbreaks in only a few countries in the Middle East, including Egypt. Little is known about this historical phase of plague, even though it represents the temporal, geographical and phylogenetic transition between the second and third pandemics. Here we analysed in detail an outbreak of plague that took place in Cairo in 1801, and for which epidemiological data are uniquely available thanks to the presence of medical officers accompanying the Napoleonic expedition into Egypt at that time. We propose a new stochastic model describing how bubonic plague outbreaks unfold in both rat and human populations, and perform Bayesian inference under this model using a particle Markov chain Monte Carlo. Rat carcasses were estimated to be infectious for approximately 4 days after death, which is in good agreement with local observations on the survival of infectious rat fleas. The estimated transmission rate between rats implies a basic reproduction number R0 of approximately 3, causing the collapse of the rat population in approximately 100 days. Simultaneously, the force of infection exerted by each infected rat carcass onto the human population increases progressively by more than an order of magnitude. We also considered human-to-human transmission via pneumonic plague or human specific vectors, but found this route to account for only a small fraction of cases and to be significantly below the threshold required to sustain an outbreak.

A method for using real world data in breast cancer modeling.

OBJECTIVES: Today, hospitals and other health care-related institutions are accumulating a growing bulk of real world clinical data. Such data offer new possibilities for the generation of disease models for the health economic evaluation. In this article, we propose a new approach to leverage cancer registry data for the development of Markov models. Records of breast cancer patients from a clinical cancer registry were used to construct a real world data driven disease model. METHODS: We describe a model generation process which maps database structures to disease state definitions based on medical expert knowledge. Software was programmed in Java to automatically derive a model structure and transition probabilities. We illustrate our method with the reconstruction of a published breast cancer reference model derived primarily from clinical study data. In doing so, we exported longitudinal patient data from a clinical cancer registry covering eight years. The patient cohort (n=892) comprised HER2-positive and HER2-negative women treated with or without Trastuzumab. RESULTS: The models generated with this method for the respective patient cohorts were comparable to the reference model in their structure and treatment effects. However, our computed disease models reflect a more detailed picture of the transition probabilities, especially for disease free survival and recurrence. CONCLUSIONS: Our work presents an approach to extract Markov models semi-automatically using real world data from a clinical cancer registry. Health care decision makers may benefit from more realistic disease models to improve health care-related planning and actions based on their own data.

High-resolution microendoscopy for esophageal cancer screening in China: A cost-effectiveness analysis.

AIM: To study the cost-effectiveness of high-resolution microendoscopy (HRME) in an esophageal squamous cell carcinoma (ESCC) screening program in China. METHODS: A decision analytic Markov model of ESCC was developed. Separate model analyses were conducted for cohorts consisting of an average-risk population or a high-risk population in China. Hypothetical 50-year-old individuals were followed until age 80 or death. We compared three different strategies for both cohorts: (1) no screening; (2) standard endoscopic screening with Lugol's iodine staining; and (3) endoscopic screening with Lugol's iodine staining and an HRME. Model parameters were estimated from the literature as well as from GLOBOCAN, the Cancer Incidence and Mortality Worldwide cancer database. Health states in the model included non-neoplasia, mild dysplasia, moderate dysplasia, high-grade dysplasia, intramucosal carcinoma, operable cancer, inoperable cancer, and death. Separate ESCC incidence transition rates were generated for the average-risk and high-risk populations. Costs in Chinese currency were converted to international dollars (I$) and were adjusted to 2012 dollars using the Consumer Price Index. RESULTS: The main outcome measurements for this study were quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER). For the average-risk population, the HRME screening strategy produced 0.043 more QALYs than the no screening strategy at an additional cost of I$646, resulting in an ICER of I$11808 per QALY gained. Standard endoscopic screening was weakly dominated. Among the high-risk population, when the HRME screening strategy was compared with the standard screening strategy, the ICER was I$8173 per QALY. For both the high-risk and average-risk screening populations, the HRME screening strategy appeared to be the most cost-effective strategy, producing ICERs below the willingness-to-pay threshold, I$23500 per QALY. One-way sensitivity analysis showed that, for the average-risk population, higher specificity of Lugol's iodine (> 40%) and lower specificity of HRME (< 70%) could make Lugol's iodine screening cost-effective. For the high-risk population, the results of the model were not substantially affected by varying the follow-up rate after Lugol's iodine screening, Lugol's iodine test characteristics (sensitivity and specificity), or HRME specificity. CONCLUSION: The incorporation of HRME into an ESCC screening program could be cost-effective in China. Larger studies of HRME performance are needed to confirm these findings.

Conserved systems and functional genomic assessment of nociception.

Chronic pain represents a significant public health concern and current therapies do not adequately meet patient needs. With the advent of genomic technologies, pain researchers have begun to identify key loci associating with human pain diseases, and these data are instructing the development of next generation analgesics. Although human genetics efforts have been effective, complementary approaches, including functional genomics, may provide additional insight into pain genetics and help identify additional new drug targets. In the present review, we discuss the use of fruit fly systems biology combined with mammalian genetics to accelerate the discovery of novel pain genes and candidate drug targets.