Massive malignant pleural effusion due to lung adenocarcinoma in 13-year-old boy

A 13-year-old boy with no risk factors for lung cancer presented with a massive left-sided pleural effusion and a mediastinal shift on chest radiography and computed tomography. A chest tube drained bloody pleural fluid with an exudative pattern. A pleural biopsy and wedge biopsy of the left lower lobe revealed mucinous adenocarcinoma in the left lower lobe wedge biopsy and metastatic adenocarcinoma in the pleural biopsy. The patient is currently undergoing chemotherapy. Radiotherapy is planned after shrinkage of the tumor. Adenocarcinoma of the lung is very rarely seen in teenagers or children, especially in the absence of risk factors. © SAGE Publications

Approximating Connected Facility Location with Lower and Upper Bounds via LP Rounding

We consider a lower- and upper-bounded generalization of the classical facility location problem, where each facility has a capacity (upper bound) that limits the number of clients it can serve and a lower bound on the number of clients it must serve if it is opened. We develop an LP rounding framework that exploits a Voronoi diagram-based clustering approach to derive the first bicriteria constant approximation algorithm for this problem with non-uniform lower bounds and uniform upper bounds. This naturally leads to the the first LP-based approximation algorithm for the lower bounded facility location problem (with non-uniform lower bounds). We also demonstrate the versatility of our framework by extending this and presenting the first constant approximation algorithm for some connected variant of the problems in which the facilities are required to be connected as well

Approximation Schemes for Min-Sum k-Clustering

We consider the Min-Sum k-Clustering (k-MSC) problem. Given a set of points in a metric which is represented by an edge-weighted graph G = (V, E) and a parameter k, the goal is to partition the points V into k clusters such that the sum of distances between all pairs of the points within the same cluster is minimized. The k-MSC problem is known to be APX-hard on general metrics. The best known approximation algorithms for the problem obtained by Behsaz, Friggstad, Salavatipour and Sivakumar [Algorithmica 2019] achieve an approximation ratio of O(log |V|) in polynomial time for general metrics and an approximation ratio 2+? in quasi-polynomial time for metrics with bounded doubling dimension. No approximation schemes for k-MSC (when k is part of the input) is known for any non-trivial metrics prior to our work. In fact, most of the previous works rely on the simple fact that there is a 2-approximate reduction from k-MSC to the balanced k-median problem and design approximation algorithms for the latter to obtain an approximation for k-MSC. In this paper, we obtain the first Quasi-Polynomial Time Approximation Schemes (QPTAS) for the problem on metrics induced by graphs of bounded treewidth, graphs of bounded highway dimension, graphs of bounded doubling dimensions (including fixed dimensional Euclidean metrics), and planar and minor-free graphs. We bypass the barrier of 2 for k-MSC by introducing a new clustering problem, which we call min-hub clustering, which is a generalization of balanced k-median and is a trade off between center-based clustering problems (such as balanced k-median) and pair-wise clustering (such as Min-Sum k-clustering). We then show how one can find approximation schemes for Min-hub clustering on certain classes of metrics

Scheduling Problems over Network of Machines

We consider scheduling problems in which jobs need to be processed through a (shared) network of machines. The network is given in the form of a graph the edges of which represent the machines. We are also given a set of jobs, each specified by its processing time and a path in the graph. Every job needs to be processed in the order of edges specified by its path. We assume that jobs can wait between machines and preemption is not allowed; that is, once a job is started being processed on a machine, it must be completed without interruption. Every machine can only process one job at a time. The makespan of a schedule is the earliest time by which all the jobs have finished processing. The flow time (a.k.a. the completion time) of a job in a schedule is the difference in time between when it finishes processing on its last machine and when the it begins processing on its first machine. The total flow time (or the sum of completion times) is the sum of flow times (or completion times) of all jobs. Our focus is on finding schedules with the minimum sum of completion times or minimum makespan. In this paper, we develop several algorithms (both approximate and exact) for the problem both on general graphs and when the underlying graph of machines is a tree. Even in the very special case when the underlying network is a simple star, the problem is very interesting as it models a biprocessor scheduling with applications to data migration

Medical therapy versus percutaneous coronary intervention in ischemic heart disease: A cost-effectiveness analysis

Background: Ischemic heart disease is categorized into two acute and chronic groups, and its treatments include revascularization and medical therapy. The aim of this study is to evaluate the economic burden of medical therapy compared to percutaneous coronary intervention in ischemic heart disease. Methods: This study has been done in two steps. The first was a systematic review and meta-analysis to measure the effectiveness of two interventions and the second step was a cost-effectiveness analysis from the perspective of society. The data analysis included a meta-analysis and the Markov cohort simulation. RewMan v5 and tree age software were utilized. Uncertainties related to the model parameters were evaluated using one-way and two-way sensitivity analyses. Results: Regarding the effectiveness of interventions, the odd ratio of the quality of life in the medical therapy group (CI: 0.76-1.10) was 0.91 times the PCI group (p=0.34). This rate for mortality in medical therapy (CI: 0.52-9.68) was 2.23 times more than the PCI group; this result was not significant (p=0.02). In the cost-effectiveness analysis, the cost-effectiveness threshold was 16,482; ICER in increasing the QoL and reduction in the mortality rate was 25320.11 and 562.6691, respectively. Regarding the sensitivity analysis, the model was not sensitive in changing parameters in a specific domain. Conclusion: According to this study, PCI is more cost-effective than medical therapy in the reduction of mortality rate and in the field of increasing quality of life. MT strategy is more cost-effective than the PCI. This study considers controversies regarding the most appropriate treatment for patients with ischemic heart disease that is helpful for health policymakers, cardiologists and health managers. © 2020 Iran University of Medical Sciences. All Rights Reserved

Dietary predictors of childhood obesity in a representative sample of children in North East of Iran

Objective: The prevalence of obesity is increasing in Iranian youngsters. This study aimed to assess some dietary determinants of obesity in a representative sample of children in Neishabour, a city in northeastern, Iran. Methods: This case-control study was conducted among 114 school students, aged 6-12 years, with a body mass index (BMI) �95th (based on percentile of Iranian children) as the case group and 102 age- and gender-matched controls, who were selected from their non-obese classmates. Nutrient intake data were collected by trained nutritionists by using two 24-hour-dietary recalls through maternal interviews in the presence of their child. A food frequency questionnaire was used for detecting the snack consumption patterns. Statistical analysis was done using univariate and multivariate logistic regression (MLR) by SPSS version 16. Results: In univariate logistic regression, total energy, protein, carbohydrate, fat (including saturated, mono- and poly-unsaturated fat), and dietary fiber were the positive predictors of obesity in studied children. The estimated crude ORs for frequency of corn-based extruded snacks, carbonated beverages, potato chips, fast foods, and chocolate consumption were statistically significant. After MLR analysis, the association of obesity remained significant with energy intake (OR = 2.489, 95 CI: 1.667-3.716), frequency of corn-based extruded snacks (OR = 1.122, 95 CI; 1.007-1.250), and potato chips (OR = 1.143, 95 CI: 1.024-1.276). The MLR analysis showed that dietary fiber (OR = 0. 01, 95 CI; 0.368-0.983) and natural fruit juice intake (OR = 0.909, 95 CI; 0.835-0.988) were protective factors against obesity. Conclusions: The findings serve to confirm the role of an unhealthy diet, notably caloriedense snacks, in childhood obesity. Healthy dietary habits, such as the consumption of high-fiber foods, should be encouraged among children

Neuroscience-informed classification of prevention interventions in substance use disorders : an RDoC-based approach

Neuroscience has contributed to uncover the mechanisms underpinning substance use disorders (SUD). The next frontier is to leverage these mechanisms as active targets to create more effective interventions for SUD treatment and prevention. Recent large-scale cohort studies from early childhood are generating multiple levels of neuroscience-based information with the potential to inform the development and refinement of future preventive strategies. However, there are still no available well-recognized frameworks to guide the integration of these multi-level datasets into prevention interventions. The Research Domain Criteria (RDoC) provides a neuroscience-based multi-system framework that is well suited to facilitate translation of neurobiological mechanisms into behavioral domains amenable to preventative interventions. We propose a novel RDoC-based framework for prevention science and adapted the framework for the existing preventive interventions. From a systematic review of randomized controlled trials using a person-centered drug/alcohol preventive approach for adolescents, we identified 22 unique preventive interventions. By teasing apart these 22 interventions into the RDoC domains, we proposed distinct neurocognitive trajectories which have been recognized as precursors or risk factors for SUDs, to be targeted, engaged and modified for effective addiction prevention.Peer reviewe

Radiation-induced inflammation and autoimmune diseases

Currently, ionizing radiation (IR) plays a key role in the agricultural and medical industry, while accidental exposure resulting from leakage of radioactive sources or radiological terrorism is a serious concern. Exposure to IR has various detrimental effects on normal tissues. Although an increased risk of carcinogenesis is the best-known long-term consequence of IR, evidence has shown that other diseases, particularly diseases related to inflammation, are common disorders among irradiated people. Autoimmune disorders are among the various types of immune diseases that have been investigated among exposed people. Thyroid diseases and diabetes are two autoimmune diseases potentially induced by IR. However, the precise mechanisms of IR-induced thyroid diseases and diabetes remain to be elucidated, and several studies have shown that chronic increased levels of inflammatory cytokines after exposure play a pivotal role. Thus, cytokines, including interleukin-1(IL-1), tumor necrosis factor (TNF-α) and interferon gamma (IFN-γ), play a key role in chronic oxidative damage following exposure to IR. Additionally, these cytokines change the secretion of insulin and thyroid-stimulating hormone(TSH). It is likely that the management of inflammation and oxidative damage is one of the best strategies for the amelioration of these diseases after a radiological or nuclear disaster. In the present study, we reviewed the evidence of radiation-induced diabetes and thyroid diseases, as well as the potential roles of inflammatory responses. In addition, we proposed that the mitigation of inflammatory and oxidative damage markers after exposure to IR may reduce the incidence of these diseases among individuals exposed to radiation. Keywords Radiation Inflammation Autoimmune diseases Thyroid Diabete

Radiation-induced inflammation and autoimmune diseases

Currently, ionizing radiation (IR) plays a key role in the agricultural and medical industry, while accidental exposure resulting from leakage of radioactive sources or radiological terrorism is a serious concern. Exposure to IR has various detrimental effects on normal tissues. Although an increased risk of carcinogenesis is the best-known long-term consequence of IR, evidence has shown that other diseases, particularly diseases related to inflammation, are common disorders among irradiated people. Autoimmune disorders are among the various types of immune diseases that have been investigated among exposed people. Thyroid diseases and diabetes are two autoimmune diseases potentially induced by IR. However, the precise mechanisms of IR-induced thyroid diseases and diabetes remain to be elucidated, and several studies have shown that chronic increased levels of inflammatory cytokines after exposure play a pivotal role. Thus, cytokines, including interleukin-1(IL-1), tumor necrosis factor (TNF-α) and interferon gamma (IFN-γ), play a key role in chronic oxidative damage following exposure to IR. Additionally, these cytokines change the secretion of insulin and thyroid-stimulating hormone(TSH). It is likely that the management of inflammation and oxidative damage is one of the best strategies for the amelioration of these diseases after a radiological or nuclear disaster. In the present study, we reviewed the evidence of radiation-induced diabetes and thyroid diseases, as well as the potential roles of inflammatory responses. In addition, we proposed that the mitigation of inflammatory and oxidative damage markers after exposure to IR may reduce the incidence of these diseases among individuals exposed to radiation. © 2018 The Author(s)