The Role of Phosphatidylethanolamine N-Methyltransferase (PEMT) and Its Waist-Hip-Ratio-Associated Locus rs4646404 in Obesity-Related Metabolic Traits and Liver Disease.

In previous genome-wide association studies (GWAS), genetic loci associated with obesity and impaired fat distribution (FD) have been identified. In the present study, we elucidated the role of the PEMT gene, including the waist-hip-ratio-associated single nucleotide polymorphism rs4646404, and its influence on obesity-related metabolic traits. DNA from 2926 metabolically well-characterized subjects was used for genotyping. PEMT expression was analyzed in paired visceral (vis) and subcutaneous (sc) adipose tissue (AT) from a subset of 574 individuals. Additionally, PEMT expression was examined in vis, sc AT and liver tissue in a separate cohort of 64 patients with morbid obesity and liver disease. An in vitro Pemt knockdown was conducted in murine epididymal and inguinal adipocytes. Our findings highlight tissue-specific variations in PEMT mRNA expression across the three studied tissues. Specifically, vis PEMT mRNA levels correlated significantly with T2D and were implicated in the progression of non-alcoholic steatohepatitis (NASH), in contrast to liver tissue, where no significant associations were found. Moreover, sc PEMT expression showed significant correlations with several anthropometric- and metabolic-related parameters. The rs4646404 was associated with vis AT PEMT expression and also with diabetes-related traits. Our in vitro experiments supported the influence of PEMT on adipogenesis, emphasizing its role in AT biology. In summary, our data suggest that PEMT plays a role in regulating FD and has implications in metabolic diseases.

Emergency services utilization in Jakarta (Indonesia): a cross-sectional study of patients attending hospital emergency departments.

BACKGROUND: Pre-hospital and emergency services in Indonesia are still developing. Despite recent improvements in the Indonesian healthcare system, issues with the provision of pre-hospital and emergency services persist. The demand for pre-hospital and emergency services has not been the subject of previous research and, therefore, has not been fully understood. Our research explored the utilization of emergency medical services by patients attending hospital emergency departments in Jakarta, Indonesia. METHODS: The study used a cross-sectional survey design involving five general hospitals (four government-funded and one private). Each patient's demographic profile, medical conditions, time to treatment, and mode of transport to reach the hospital were analysed using descriptive statistics. RESULTS: A total of 1964 (62%) patients were surveyed. The median age of patients was 44 years with an interquartile range (IQR) of 26 to 58 years. Life-threatening conditions such as trauma and cardiovascular disease were found in 8.6 and 6.6% of patients, respectively. The majority of patients with trauma travelled to the hospital using a motorcycle or car (59.8%). An ambulance was used by only 9.3% of all patients and 38% of patients reported that they were not aware of the availability of ambulances. Ambulance response time was longer as compared to other modes of transportation (median: 24 minutes and IQR: 12 to 54 minutes). The longest time to treatment was experienced by patients with neurological disease, with a median time of 120 minutes (IQR: 78 to 270 minutes). Patients who used ambulances incurred higher costs as compared to those patients who did not use ambulances. CONCLUSION: The low utilization of emergency ambulances in Jakarta could be contributed to patients' lack of awareness of medical symptoms and the existence of ambulance services, and patients' disinclination to use ambulances due to high costs and long response times. The emergency ambulance services can be improved by increasing population awareness on symptoms that warrant the use of ambulances and reducing the cost burden related to ambulance use.

Adipsin Serum Concentrations and Adipose Tissue Expression in People with Obesity and Type 2 Diabetes.

(1) Adipsin is an adipokine that may link increased fat mass and adipose tissue dysfunction to obesity-related cardiometabolic diseases. Here, we investigated whether adipsin serum concentrations and adipose tissue (AT) adipsin mRNA expression are related to parameters of AT function, obesity and type 2 diabetes (T2D). (2) Methods: A cohort of 637 individuals with a wide range of age and body weight (Age: 18-85 years; BMI: 19-70 kg/m2) with (n = 237) or without (n = 400) T2D was analyzed for serum adipsin concentrations by ELISA and visceral (VAT) and subcutaneous (SAT) adipsin mRNA expression by RT-PCR. (3) Results: Adipsin serum concentrations were significantly higher in patients with T2D compared to normoglycemic individuals. We found significant positive univariate relationships of adipsin serum concentrations with age (r = 0.282, p < 0.001), body weight (r = 0.264, p < 0.001), fasting plasma glucose (r = 0.136, p = 0.006) and leptin serum concentrations (r = 0.362, p < 0.001). Neither VAT nor SAT adipsin mRNA expression correlated with adipsin serum concentrations after adjusting for age, sex and BMI. Independent of T2D status, we found significantly higher adipsin expression in SAT compared to VAT (4) Conclusions: Our data suggest that adipsin serum concentrations are strongly related to obesity and age. However, neither circulating adipsin nor adipsin AT expression reflects parameters of impaired glucose or lipid metabolism in patients with obesity with or without T2D.

Metabolic Effects of the Waist-To-Hip Ratio Associated Locus GRB14/COBLL1 Are Related to GRB14 Expression in Adipose Tissue.

GRB14/COBLL1 locus has been shown to be associated with body fat distribution (FD), but neither the causal gene nor its role in metabolic diseases has been elucidated. We hypothesize that GRB14/COBLL1 may act as the causal genes for FD-related SNPs (rs10195252 and rs6738627), and that they may be regulated by SNP to effect obesity-related metabolic traits. We genotyped rs10195252 and rs6738627 in 2860 subjects with metabolic phenotypes. In a subgroup of 560 subjects, we analyzed GRB14/COBLL1 gene expression in paired visceral and subcutaneous adipose tissue (AT) samples. Mediation analyses were used to determine the causal relationship between SNPs, AT GRB14/COBLL1 mRNA expression, and obesity-related traits. In vitro gene knockdown of Grb14/Cobll1 was used to test their role in adipogenesis. Both gene expressions in AT are correlated with waist circumference. Visceral GRB14 mRNA expression is associated with FPG and HbA1c. Both SNPs are associated with triglycerides, FPG, and leptin levels. Rs10195252 is associated with HbA1c and seems to be mediated by visceral AT GRB14 mRNA expression. Our data support the role of the GRB14/COBLL1 gene expression in body FD and its locus in metabolic sequelae: in particular, lipid metabolism and glucose homeostasis, which is likely mediated by AT GRB14 transcript levels.

Modified Needleman-Wunsch algorithm for clinical pathway clustering.

Clinical pathways are used to guide clinicians to provide a standardised delivery of care. Because of their standardisation, the aim of clinical pathways is to reduce variation in both care process and patient outcomes. When learning clinical pathways from data through data mining, it is common practice to represent each patient pathway as a string corresponding to their movements through activities. Clustering techniques are popular methods for pathway mining, and therefore this paper focuses on distance metrics applied to string data for k-medoids clustering. The two main aims are to firstly, develop a technique that seamlessly integrates expert information with data and secondly, to develop a string distance metric for the purpose of process data. The overall goal was to allow for more meaningful clustering results to be found by adding context into the string similarity calculation. Eight common distance metrics and their applicability are discussed. These distance metrics prove to give an arbitrary distance, without consideration for context, and each produce different results. As a result, this paper describes the development of a new distance metric, the modified Needleman-Wunsch algorithm, that allows for expert interaction with the calculation by assigning groupings and rankings to activities, which provide context to the strings. This algorithm has been developed in partnership with UK's National Health Service (NHS) with the focus on a lung cancer pathway, however the handling of the data and algorithm allows for application to any disease type. This method is contained within Sim.Pro.Flow, a publicly available decision support tool.

Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Early identification of resource needs is instrumental in promoting efficient hospital resource management. Hospital information systems, and electronic health records (EHR) in particular, collect valuable demographic and clinical patient data from the moment patients are admitted, which can help predict expected resource needs in early stages of patient episodes. To this end, this article proposes a data mining methodology to systematically obtain predictions for relevant managerial variables by leveraging structured EHR data. Specifically, these managerial variables are: i) Diagnosis categories, ii) procedure codes, iii) diagnosis-related groups (DRGs), iv) outlier episodes and v) length of stay (LOS). The proposed methodology approaches the problem in four stages: Feature set construction, feature selection, prediction model development, and model performance evaluation. We tested this approach with an EHR dataset of 5,089 inpatient episodes and compared different classification and regression models (for categorical and continuous variables, respectively), performed temporal analysis of model performance, analyzed the impact of training set homogeneity on performance and assessed the contribution of different EHR data elements for model predictive power. Overall, our results indicate that inpatient EHR data can effectively be leveraged to inform resource management on multiple perspectives. Logistic regression (combined with minimal redundancy maximum relevance feature selection) and bagged decision trees yielded best results for predicting categorical and numerical managerial variables, respectively. Furthermore, our temporal analysis indicated that, while DRG classes are more difficult to predict, several diagnosis categories, procedure codes and LOS amongst shorter-stay patients can be predicted with higher confidence in early stages of patient stay. Lastly, value of information analysis indicated that diagnoses, medication and structured assessment forms were the most valuable EHR data elements in predicting managerial variables of interest through a data mining approach.

Resource optimization for cancer pathways with aggregate diagnostic demand: a perishable inventory approach.

This work proposes a novel framework for planning the capacity of diagnostic tests in cancer pathways that considers the aggregate demand of referrals from multiple cancer specialties (sites). The framework includes an analytic tool that recursively assesses the overall daily demand for each diagnostic test and considers general distributions for both the incoming cancer referrals and the number of required specific tests for any given patient. By disaggregating the problem with respect to each diagnostic test, we are able to model the system as a perishable inventory problem that can be solved by means of generalized G/D/C queuing models, where the capacity [Formula: see text] is allowed to vary and can be seen as a random variable that is adjusted according to prescribed performance measures. The approach aims to provide public health and cancer services with recommendations to align capacity and demand for cancer diagnostic tests effectively and efficiently. Our case study illustrates the applicability of our methods on lung cancer referrals from UK's National Health Service.

DNA methylation of SSPN is linked to adipose tissue distribution and glucose metabolism.

DNA methylation is a crucial epigenetic mechanism in obesity and fat distribution. We explored the Sarcospan ( SSPN) gene locus by using genome-wide data sets comprising methylation and expression data, pyrosequencing analysis in the promoter region, and genetic analysis of an SNP variant rs718314, which was previously reported to associate with waist-to-hip ratio. We found that DNA methylation influences several clinical variables related to fat distribution and glucose metabolism, while SSPN mRNA levels showed directionally opposite effects on these traits. Complete DNA methylation of the SSPN promoter construct suppressed the gene expression of firefly luciferase in MCF7 cells. Moreover, rs718314 was associated with waist and with DNA methylation at CpG sites. Our data strongly support the role of the SSPN locus in body fat composition and glucose homeostasis, and suggest that this is most likely the result of changes in DNA methylation of SSPN in adipose tissue.-Keller, M., Klös, M., Rohde, K., Krüger, J., Kurze, T., Dietrich, A., Schön, M. R., Gärtner, D., Lohmann, T., Dreßler, M., Stumvoll, M., Blüher, M., Kovacs, P., Böttcher, Y. DNA methylation of SSPN is linked to adipose tissue distribution and glucose metabolism.

Cognitive workload reduction in hospital information systems : Decision support for order set optimization.

Order sets are a critical component in hospital information systems that are expected to substantially reduce physicians' physical and cognitive workload and improve patient safety. Order sets represent time interval-clustered order items, such as medications prescribed at hospital admission, that are administered to patients during their hospital stay. In this paper, we develop a mathematical programming model and an exact and a heuristic solution procedure with the objective of minimizing physicians' cognitive workload associated with prescribing order sets. Furthermore, we provide structural insights into the problem which lead us to a valid lower bound on the order set size. In a case study using order data on Asthma patients with moderate complexity from a major pediatric hospital, we compare the hospital's current solution with the exact and heuristic solutions on a variety of performance metrics. Our computational results confirm our lower bound and reveal that using a time interval decomposition approach substantially reduces computation times for the mathematical program, as does a K -means clustering based decomposition approach which, however, does not guarantee optimality because it violates the lower bound. The results of comparing the mathematical program with the current order set configuration in the hospital indicates that cognitive workload can be reduced by about 20.2% by allowing 1 to 5 order sets, respectively. The comparison of the K -means based decomposition with the hospital's current configuration reveals a cognitive workload reduction of about 19.5%, also by allowing 1 to 5 order sets, respectively. We finally provide a decision support system to help practitioners analyze the current order set configuration, the results of the mathematical program and the heuristic approach.

Decision Support for the Capacity Management of Bronchoscopy Devices: Optimizing the Cost-Efficient Mix of Reusable and Single-Use Devices Through Mathematical Modeling.

BACKGROUND: Increasing costs of material resources challenge hospitals to stay profitable. Particularly in anesthesia departments and intensive care units, bronchoscopes are used for various indications. Inefficient management of single- and multiple-use systems can influence the hospitals' material costs substantially. Using mathematical modeling, we developed a strategic decision support tool to determine the optimum mix of disposable and reusable bronchoscopy devices in the setting of an intensive care unit. METHODS: A mathematical model with the objective to minimize costs in relation to demand constraints for bronchoscopy devices was formulated. The stochastic model decides whether single-use, multi-use, or a strategically chosen mix of both device types should be used. A decision support tool was developed in which parameters for uncertain demand such as mean, standard deviation, and a reliability parameter can be inserted. Furthermore, reprocessing costs per procedure, procurement, and maintenance costs for devices can be parameterized. RESULTS: Our experiments show for which demand pattern and reliability measure, it is efficient to only use reusable or disposable devices and under which circumstances the combination of both device types is beneficial. CONCLUSIONS: To determine the optimum mix of single-use and reusable bronchoscopy devices effectively and efficiently, managers can enter their hospital-specific parameters such as demand and prices into the decision support tool.The software can be downloaded at: https://github.com/drdanielgartner/bronchomix/.

Liver resection after selective internal radiotherapy (SIRT): Proof of concept, initial survival, and safety.

BACKGROUND AND OBJECTIVES: Extent of liver resections are restricted by the volume of the future liver remnant. Different strategies have been developed to increase the frequency of curative resections. Selective internal radiation therapy (SIRT) has emerged as an effective therapy for patients with primary non-resectable malignancies of the liver. Here, we report the first clinical series of patients with curative liver resection following SIRT. METHODS: Starting 2010, patients with marginally resectable liver metastases treated by SIRT followed by liver resection were identified and prospectively documented in a database for subsequent retrospective analysis. RESULTS: Thirteen patients (five female, eight male; age 70 years [32-77 years]) with marginally resectable liver metastases were selected for liver resection after SIRT. After performing SIRT, 12 patients had potentially curative hepatic resection. In two patients, liver resection after SIRT could not be performed due to the appearance of new extrahepatic metastases. Analyzing the effect of SIRT, we observed a decrease in tumor size with central scaring. None of the patients developed liver necrosis after SIRT. Liver resection was performed safely in all patients. CONCLUSIONS: The combination of SIRT with state-of-the-art liver surgery opens up new therapeutic options in patients with liver metastases.

BariSurg trial: Sleeve gastrectomy versus Roux-en-Y gastric bypass in obese patients with BMI 35-60 kg/m(2) - a multi-centre randomized patient and observer blind non-inferiority trial.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) rank among the most frequently applied bariatric procedures worldwide due to their positive risk/benefit correlation. A systematic review revealed a similar excess weight loss (EWL) 2 years postoperatively between SG and RYGB. However, there is a lack of randomized controlled multi-centre trials comparing SG and RYGB, not only concerning EWL, but also in terms of remission of obesity-related co-morbidities, gastroesophageal reflux disease (GERD) and quality of life (QoL) in the mid- and long-term. METHODS: The BariSurg trial was designed as a multi-centre, randomized controlled patient and observer blind trial. The trial protocol was approved by the corresponding ethics committees of the centres. To demonstrate EWL non-inferiority of SG compared to RYGB, power calculation was performed according to a non-inferiority study design. Morbidity, mortality, remission of obesity-related co-morbidities, GERD course and QoL are major secondary endpoints. 248 patients between 18 and 70 years, with a body mass index (BMI) between 35-60 kg/m(2) and indication for bariatric surgery according to the most recent German S3-guidelines will be randomized. The primary and secondary endpoints will be assessed prior to surgery and afterwards at discharge and at the time points 3-6, 12, 24, 36, 48 and 60 months postoperatively. DISCUSSION: With its five year follow-up, the BariSurg-trial will provide further evidence based data concerning the impact of SG and RYGB on EWL, remission of obesity-related co-morbidities, the course of GERD and QoL. TRIAL REGISTRATION: The trial protocol has been registered in the German Clinical Trials Register DRKS00004766 .

Global DNA methylation levels in human adipose tissue are related to fat distribution and glucose homeostasis.

AIMS/HYPOTHESIS: Epigenetic alterations may influence the metabolic pathways involved in human obesity. We hypothesised that global DNA methylation levels in adipose tissue might be associated with obesity and related phenotypes. METHODS: We measured global DNA methylation levels in paired samples of subcutaneous adipose tissue (SAT) and omental visceral adipose tissue (OVAT) from 51 individuals, and in leucocytes from 559 Sorbs, a population from Germany, using LUminometric Methylation Assay (LUMA). To further investigate the underlying mechanisms of the observed associations, we measured global methylation levels in 3T3-L1 adipocytes exposed to glucose, insulin and lipids. RESULTS: Global methylation levels (±SD) were significantly higher in OVAT (74.27% ± 2.2%) compared with SAT (71.97% ± 2.4%; paired t test, p < 1 × 10(-9)). Furthermore, global methylation levels in SAT were positive correlates of measures of fat distribution (waist measurement, WHR) and glucose homeostasis (HbA1c) (all p < 0.015 after accounting for multiple testing and covariates). Global methylation levels in the German Sorb cohort were associated with glucose homeostasis, but this association did not withstand adjustment for covariates. Exposure of 3T3-L1 adipocytes to insulin, palmitate and glucose decreased global methylation levels 1 h after treatment relative to controls. CONCLUSIONS/INTERPRETATION: Our data suggest that the variability in global methylation in adipose tissue might be related to alterations in glucose metabolism.

Capacity Planning of Virtual Wards for Frail and Elderly Patients.

This paper investigates the planning of virtual ward (VW) capacity including the remote monitoring of frail and elderly patients. The main objective is to optimize VW hub locations across a region in the United Kingdom. Furthermore, assigning the optimal number of clinicians to different regions needs to be considered. We develop a mathematical model that minimizes the setup and travel costs of VW hubs and staff. Our experimental analysis evaluates different levels of demand considering postcode areas within different Trusts, also known as Health Boards, in the National Health Service (NHS). Furthermore, our experiments provide insights into how many hub locations should be deployed and staffed. This can be used to individually find the number of remote monitors and clinicians for each facility as well as the system overall.

30-day morbidity and mortality of revisional bariatric surgery - An international multi-centre collaborative (BROAD) study.

INTRODUCTION: Revisional bariatric surgery (RBS) for insufficient weight loss/weight regain or metabolic relapse is increasing worldwide. There is currently no large multinational, prospective data on 30-day morbidity and mortality of RBS. In this study, we aimed to evaluate the 30-day morbidity and mortality of RBS at participating centres. METHODS: An international steering group was formed to oversee the study. The steering group members invited bariatric surgeons worldwide to participate in this study. Ethical approval was obtained at the lead centre. Data were collected prospectively on all consecutive RBS patients operated between 15th May 2021 to 31st December 2021. Revisions for complications were excluded. RESULTS: A total of 65 global centres submitted data on 750 patients. Sleeve gastrectomy (n = 369, 49.2 %) was the most common primary surgery for which revision was performed. Revisional procedures performed included Roux-en-Y gastric bypass (RYGB) in 41.1 % (n = 308) patients, One anastomosis gastric bypass (OAGB) in 19.3 % (n = 145), Sleeve Gastrectomy (SG) in 16.7 % (n = 125) and other procedures in 22.9 % (n = 172) patients. Indications for revision included weight regain in 615(81.8 %) patients, inadequate weight loss in 127(16.9 %), inadequate diabetes control in 47(6.3 %) and diabetes relapse in 27(3.6 %). 30-day complications were seen in 80(10.7 %) patients. Forty-nine (6.5 %) complications were Clavien Dindo grade 3 or higher. Two patients (0.3 %) died within 30 days of RBS. CONCLUSION: RBS for insufficient weight loss/weight regain or metabolic relapse is associated with 10.7 % morbidity and 0.3 % mortality. Sleeve gastrectomy is the most common primary procedure to undergo revisional bariatric surgery, while Roux-en-Y gastric bypass is the most commonly performed revision.

Understanding the Impact of Social Networks on the Spread of Obesity.

Previous research has highlighted the significant role social networks play in the spread of non-communicable chronic diseases. In our research, we seek to explore the impact of these networks in more detail and gain insight into the mechanisms that drive this. We use obesity as a case study. To achieve this, we develop a generalisable hybrid simulation and optimisation approach aimed at gaining qualitative and quantitative insights into the effect of social networks on the spread of obesity. Our simulation model has two components. Firstly, an agent-based component mimics the dynamic structure of the social network within which individuals are situated. Secondly, a system dynamics component replicates the relevant behaviours of those individuals. The parameters from the combined model are refined and optimised using longitudinal data from the United Kingdom. The simulation produces projections of Body Mass Index broken down by different age groups and gender over a 10-year period. These projections are used to explore a range of scenarios in a computational study designed to address our research aims. The study reveals that, for the youngest population sub-groups, the network acts to magnify the impact of external and social factors on changes in obesity, whereas, for older sub-groups, the network mitigates the impact of these factors. The magnitude of that impact is inversely correlated with age. Our approach can be used by public health decision makers as well as managers in adult weight management services to enhance initiatives and strategies intended to reduce obesity. Our approach is generalisable to understand the impact of social networks on similar non-communicable diseases.

An operations research approach to automated patient scheduling for eye care using a multi-criteria decision support tool.

Inefficient management of resources and waiting lists for high-risk ophthalmology patients can contribute to sight loss. The aim was to develop a decision support tool which determines an optimal patient schedule for ophthalmology patients. Our approach considers available booking slots as well as patient-specific factors. Using standard software (Microsoft Excel and OpenSolver), an operations research approach was used to formulate a mathematical model. Given a set of patients and clinic capacities, the model objective was to schedule patients efficiently depending on eyecare measure risk factors, referral-to-treatment times and targets, patient locations and slot availabilities over a pre-defined planning horizon. Our decision support tool can feedback whether or not a patient is scheduled. If a patient is scheduled, the tool determines the optimal date and location to book the patients' appointments, with a score provided to show the associated value of the decisions made. Our dataset from 519 patients showed optimal prioritization based on location, risk of serious vision loss/damage and the referral-to-treatment time. Given the constraints of available slots, managers can input hospital-specific parameters such as demand and capacity into our model. The model can be applied and implemented immediately, without the need for additional software, to generate an optimized patient schedule.

Optimizing an Adolescent Hybrid Telemedical Mental Health Service Through Staff Scheduling Using Mathematical Programming: Model Development Study.

BACKGROUND: According to the World Health Organization, globally, one in seven 10- to 19-year-olds experiences a mental disorder, accounting for 13% of the global burden of disease in this age group. Half of all mental illnesses begin by the age of 14 years and some teenagers with severe presentations must be admitted to the hospital and assessed by highly skilled mental health care practitioners. Digital telehealth solutions can be useful for the assessment of young individuals remotely. Ultimately, this technology can save travel costs for the health service rather than assessing adolescents in person at the corresponding hospital. Especially in rural regions, where travel times can be high, this innovative approach can make a difference to patients by providing quicker assessments. OBJECTIVE: The aim of this study is to share insights on how we developed a decision support tool to assign staff to days and locations where adolescent mental health patients are assessed face to face. Where possible, patients are seen through video consultation. The model not only seeks to reduce travel times and consequently carbon emissions but also can be used to find a minimum number of staff to run the service. METHODS: To model the problem, we used integer linear programming, a technique that is used in mathematical modeling. The model features 2 objectives: first, we aim to find a minimum coverage of staff to provide the service and second, to reduce travel time. The constraints that are formulated algebraically are used to ensure the feasibility of the schedule. The model is implemented using an open-source solver backend. RESULTS: In our case study, we focus on real-world demand coming from different hospital sites in the UK National Health Service (NHS). We incorporate our model into a decision support tool and solve a realistic test instance. Our results reveal that the tool is not only capable of solving this problem efficiently but also shows the benefits of using mathematical modeling in health services. CONCLUSIONS: Our approach can be used by NHS managers to better match capacity and location-dependent demands within an increasing need for hybrid telemedical services, and the aims to reduce traveling and the carbon footprint within health care organizations.

Modelling lung cancer diagnostic pathways using discrete event simulation.

The United Kingdom has one of the poorest lung cancer survival rates in Europe. In this study, to help design and evaluate a single lung cancer pathway (SCP) for Wales, existing diagnostic pathways and processes have been mapped and then modelled with a discrete event simulation. The validated models have been used to provide key performance indicators and to examine different diagnostic testing strategies. Under the current diagnostic pathways, the mean time to treatment was 72 days for surgery patients, 56 days for chemotherapy patients, and 61 days for radiotherapy patients. Our research demonstrated that by ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 11 days from the current lung cancer pathway resulting in a 21% increase in patients receiving treatment within the Welsh Government set target of 62 days.

Sex-Specific Effects of the Genetic Variant rs10487505 Upstream of leptin in the Development of Obesity.

The SNP rs10487505 in the promotor region of the leptin gene was reported to be associated with decreased circulating leptin and increased body mass index (BMI). However, the phenotypic outcomes affected by rs10487505 in the leptin regulatory pathway have not been systematically studied. Therefore, the aim of this study was to elucidate the influence of rs10487505 on leptin mRNA expression and obesity-related parameters. We genotyped rs10487505 in DNA samples from 1665 patients with obesity and lean controls and measured leptin gene expression in paired samples of adipose tissue (AT, N = 310), as well as circulating leptin levels. We confirm the leptin-lowering effect of rs10487505 in women. In contrast to the previously reported data from population-based studies, in this mainly obese cohort, we describe a lower mean BMI in women carrying the C allele of rs10487505. However, no association of rs10487505 with AT leptin mRNA expression was found. Our data suggest that reduced circulating leptin levels are not a result of the direct silencing of leptin mRNA expression. Furthermore, leptin reduction by rs10487505 does not associate with BMI in a linear manner. Instead, the decreasing effect on BMI might be dependent on the severity of obesity.