Ohio University Southern

The epidemiology, clinical features, and drug treatment of depression in HIV-infected patients are discussed. The lifetime prevalence of depression in patients infected with HIV has been estimated at 22-45%. The signs and symptoms of depression are similar in HIV-infected and noninfected patients, but patients with HIV infection may more frequently have sleep and appetite disturbances. Diagnosis should focus on affective or cognitive depression symptoms that reflect mood state alone. Patients with a history of depression, homosexual men, women, and i.v. drug abusers are among HIV-infected individuals who may be at increased risk for depression. Depression may alter the course of HIV infection by impairing immune function or influencing behavior. Depression my contribute to nonadherence to therapy. Antidepressant therapy is effective in most HIV-positive patients with major depression. Tricyclic antidepressants (TCAs) have produced response rates as high as 89%, but their usefulness has been limited by adverse effects. Selective serotonin-reuptake inhibitors and other non-TCAs have also demonstrated efficacy and are generally better tolerated. Psychostimulants have improved mood, cognition, and energy level, and androgens have been used for their anabolic effects. The systemic concentrations of antidepressants may be altered by coadministered drugs that affect their cytochrome P-450 isoenzyme-mediated metabolism; in turn, the metabolism and toxicity of certain antiretrovirals may be affected by antidepressants. Guidelines on the treatment of depression in the general population may be applied to patients with HIV infection. Depressive disorders are prevalent among patients with HIV infection but often respond to a variety of treatments.

In this paper, we consider building extraction from high spatial resolution remote sensing images. At present, most building extraction methods are based on artificial features. However, the diversity and complexity of buildings mean that building extraction methods still face great challenges, so methods based on deep learning have recently been proposed. In this paper, a building extraction framework based on a convolution neural network and edge detection algorithm is proposed. The method is called Mask R-CNN Fusion Sobel. Because of the outstanding achievement of Mask R-CNN in the field of image segmentation, this paper improves it and then applies it in remote sensing image building extraction. Our method consists of three parts. First, the convolutional neural network is used for rough location and pixel level classification, and the problem of false and missed extraction is solved by automatically discovering semantic features. Second, Sobel edge detection algorithm is used to segment building edges accurately so as to solve the problem of edge extraction and the integrity of the object of deep convolutional neural networks in semantic segmentation. Third, buildings are extracted by the fusion algorithm. We utilize the proposed framework to extract the building in high-resolution remote sensing images from Chinese satellite GF-2, and the experiments show that the average value of IOU (intersection over union) of the proposed method was 88.7% and the average value of Kappa was 87.8%, respectively. Therefore, our method can be applied to the recognition and segmentation of complex buildings and is superior to the classical method in accuracy.

Importance: Following recent US Food and Drug Administration approval, adoption of whole slide imaging in clinical settings may be imminent, and diagnostic accuracy, particularly among challenging breast biopsy specimens, may benefit from computerized diagnostic support tools. Objective: To develop and evaluate computer vision methods to assist pathologists in diagnosing the full spectrum of breast biopsy samples, from benign to invasive cancer. Design, Setting, and Participants: In this diagnostic study, 240 breast biopsies from Breast Cancer Surveillance Consortium registries that varied by breast density, diagnosis, patient age, and biopsy type were selected, reviewed, and categorized by 3 expert pathologists as benign, atypia, ductal carcinoma in situ (DCIS), and invasive cancer. The atypia and DCIS cases were oversampled to increase statistical power. High-resolution digital slide images were obtained, and 2 automated image features (tissue distribution feature and structure feature) were developed and evaluated according to the consensus diagnosis of the expert panel. The performance of the automated image analysis methods was compared with independent interpretations from 87 practicing US pathologists. Data analysis was performed between February 2017 and February 2019. Main Outcomes and Measures: Diagnostic accuracy defined by consensus reference standard of 3 experienced breast pathologists. Results: The accuracy of machine learning tissue distribution features, structure features, and pathologists for classification of invasive cancer vs noninvasive cancer was 0.94, 0.91, and 0.98, respectively; the accuracy of classification of atypia and DCIS vs benign tissue was 0.70, 0.70, and 0.81, respectively; and the accuracy of classification of DCIS vs atypia was 0.83, 0.85, and 0.80, respectively. The sensitivity of both machine learning features was lower than that of the pathologists for the invasive vs noninvasive classification (tissue distribution feature, 0.70; structure feature, 0.49; pathologists, 0.84) but higher for the classification of atypia and DCIS vs benign cases (tissue distribution feature, 0.79; structure feature, 0.85; pathologists, 0.72) and the classification of DCIS vs atypia (tissue distribution feature, 0.88; structure feature, 0.89; pathologists, 0.70). For the DCIS vs atypia classification, the specificity of the machine learning feature classification was similar to that of the pathologists (tissue distribution feature, 0.78; structure feature, 0.80; pathologists, 0.82). Conclusion and Relevance: The computer-based automated approach to interpreting breast pathology showed promise, especially as a diagnostic aid in differentiating DCIS from atypical hyperplasia.

A new hazard for adolescents is the negative health effects of energy drink consumption. Adolescents are consuming these types of drinks at an alarming amount and rate. Specific effects that have been reported by adolescents include jitteriness, nervousness, dizziness, the inability to focus, difficulty concentrating, gastrointestinal upset, and insomnia. Health care providers report that they have seen the following effects from the consumption of energy drinks: dehydration, accelerated heart rates, anxiety, seizures, acute mania, and strokes. This article is a comprehensive literature review on the health effects of energy drinks. Findings from this article indicate the need for educational intervention to inform adolescents of the consequences of consuming these popular drinks. School nurses are in a unique position to teach adolescents about the side effects and possible health issues that can occur when energy drinks are consumed.

Many schools across the United States do not have a full-time school nurse, resulting in care being provided by unlicensed school employees when children are sick or injured at school. The purpose of this study was to determine if there was a difference in the number of students sent home when ill or injured based on who assessed the student in the school health office--a school nurse or an unlicensed school employee. Findings indicated that 5% of students seen by the school nurse were sent home and 18% of students seen by an unlicensed school employee were sent home. This study suggests that more students could be kept in school when school nurses provide assessment and interventions aimed at helping students who become ill or injured while at school, thus increasing school attendance and promoting academic success. These findings also support the need for a school nurse in every school.

There is growing interest in the possible health benefits of tea. We reported previously on the inhibition by white tea of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP)-induced colonic aberrant crypt foci (ACF) in the rat (4). To distinguish between blocking and suppressing effects, and thus provide mechanistic insights into prevention during the initiation versus post-initiation phases of carcinogenesis, white tea, and green tea were administered at 2% (w/v) as the sole source of drinking fluid either 2 wk before and 2 wk during PhIP dosing (100 mg/kg, every other day by oral gavage), or starting 1 wk after the carcinogen and continued until the study was terminated at 16 wk. In the former protocol, each tea produced marginal inhibition of colonic ACF, despite evidence for changes in several hepatic enzymes involved in heterocyclic amine metabolism. Post-initiation, however, the data were as follows (ACF/colon, mean +/- SE): PhIP/water 12.2 +/- 1.5; PhIP/white tea 5.9 +/- 0.9 (** P < 0.01); PhIP/caffeine 5.9 +/- 1.5 (** P < 0.01); PhIP/EGCG 3.5 +/- 0.8 (***P < 0.001); PhIP/green tea 8.9 +/- 1.2 (P = 0.22, not significant). In the latter study, apoptosis was determined using in situ oligo ligation and cleaved caspase-3 assays, whereas cell proliferation was assessed via bromodeoxyuridine (BrdU) incorporation. No consistent changes were seen in apoptosis assays, but BrdU labeling was as follows (percent of cells positive/colonic crypt, mean +/- SE): PhIP/water 10.4 +/- 0.6; PhIP/white tea 8.6 +/- 0.2 (*P < 0.05); PhIP/EGCG 6.0 +/- 0.85 (** P < 0.01); PhIP/caffeine 8.75 +/- 0.45 (*P < 0.05); PhIP/green tea 9.5 +/- 0.4 (P > 0.05, not significant). The data imply that white tea, caffeine, and EGCG may be most effective post-initiation, via the inhibition of cell proliferation in the colon and through the suppression of early lesions.

Object detection is widely used in robot navigation, intelligent security and industrial detection, but it is rarely used in water conservancy industry. In the aspect of river and lake health management, it is important to clean out the floating objects in time, which prevents water pollution caused by the accumulation of the floating objects. The early methods of water surface object detection, such as background subtraction and frame difference, are greatly affected by the change of object shape and background, resulting in poor robustness. Therefore, we propose a real-time detection method of surface floating objects based on improved RefineDet model, which includes three modules: the anchor refinement module, the transfer connection block and the object detection module. We improve anchor refinement module by adding convolution layers to obtain higher-level semantic, and fuse high-level features with low-level features to improve detection accuracy. Moreover, we adjust the parameters setting of anchors according to the scale and aspect ratio distribution to match the multi-scale object better. Aiming at the foreground-background class imbalance caused by dense anchors sampling, we introduce focal loss function to solve it and make our model more efficient by adjusting the parameters of the function. We verify the performance of the proposed method on different floating object datasets we constructed. The detection accuracies on these different datasets are 83.8%, 88.0%, and 82.3% respectively, and the detection speed is 28 FPS. This shows that the improved RefineDet realizes high-precision and real-time detection.

PREMISE OF THE STUDY: Recent clarification of the distribution of Marattiales through time provides the impetus for "total evidence" phylogenetic analyses of a major fern clade with a rich fossil record. These analyses serve as empirical tests for results from systematic analyses of living species and also of the belief that relationships among living species accurately reflect the overall pattern of phylogeny for clades with an extensive fossil record and a large percentage of extinction. METHODS: Species of living and fossil Marattiaceae are analyzed employing a "total evidence approach" via maximum parsimony. Analyses were conducted using TNT implemented through WinClada. KEY RESULTS: Systematic analyses of living species and of living + extinct species provide roughly concordant topologies for living taxa. However, living species of Marattiales are only one component of a much larger clade with two major subclades. One consists of Psaroniaceae and extends through time to at least the Early Cretaceous. The other consists of Marattiaceae and includes all living species. Various analyses support the generic-level clades of living species from earlier analyses, but the arrangement of such clades varies from analysis to analysis. CONCLUSIONS: Marattiales is a monophyletic group that is extremely common in late Paleozoic and early Mesozoic deposits, with a stem group Psaroniaceae and a crown group Marattiaceae. Because Marattiaceae represents only a small component of overall marattialean diversity, living species alone neither account for evolutionary changes within the clade over time, nor accurately reflect the overall pattern of marattialean fern phylogeny.

Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time‐varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine‐grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.

INTRODUCTION: Needle decompression of a tension pneumothorax can be a lifesaving procedure. It requires an adequate needle length to reach the chest wall to rapidly remove air. With adult obesity exceeding one third of the United States population in 2010, we sought to evaluate the proper catheter length that may result in a successful needle decompression procedure. Advance Trauma Life Support (ATLS) currently recommends a 51 millimeter (mm) needle, while the needles stocked in our emergency department are 46 mm. Given the obesity rates of our patient population, we hypothesize these needles would not have a tolerable success rate of 90%. METHODS: We retrospectively reviewed 91 patient records that had computed tomography of the chest and measured the chest wall depth at the second intercostal space bilaterally. RESULTS: We found that 46 mm needles would only be successful in 52.7% of our patient population, yet the ATLS recommended length of 51 mm has a success rate of 64.8%. Therefore, using a 64 mm needle would be successful in 79% percent of our patient population. CONCLUSION: Use of longer length needles for needle thoracostomy is essential given the extent of the nation's adult obesity population.

By means of a qualitative research method known as folknography, a concerted effort was made to discern perceptions of math and math education in the rural Midwest. A community that will be referred to as Midville, located in the state of Illinois, was chosen as the target population for this study. The community and surrounding region stands over one hundred miles from the nearest metro complex. The study was conducted in May of 2006. After completion of the initial field work, data were collected, analyzed, and summarized, producing this document.

The tidal flat is long and narrow area along rivers and coasts with high sediment content, so there is little feature difference between the waterbody and the background, and the boundary of the waterbody is blurry. The existing waterbody extraction methods are mostly used for the extraction of large water bodies like rivers and lakes, whereas less attention has been paid to tidal flat waterbody extraction. Extracting tidal flat waterbody accurately from high-resolution remote sensing imagery is a great challenge. In order to solve the low accuracy problem of tidal flat waterbody extraction, we propose a fine-grained tidal flat waterbody extraction method, named FYOLOv3, which can extract tidal flat water with high accuracy. The FYOLOv3 mainly includes three parts: an improved object detection network based on YOLOv3 (Seattle, WA, USA), a fully convolutional network (FCN) without pooling layers, and a similarity algorithm for water extraction. The improved object detection network uses 13 convolutional layers instead of Darknet-53 as the model backbone network, which guarantees the water detection accuracy while reducing the time cost and alleviating the overfitting phenomenon; secondly, the FCN without pooling layers is proposed to obtain the accurate pixel value of the tidal flat waterbody by learning the semantic information; finally, a similarity algorithm for water extraction is proposed to distinguish the waterbody from non-water pixel by pixel to improve the extraction accuracy of tidal flat water bodies. Compared to the other convolutional neural network (CNN) models, the experiments show that our method has higher accuracy on the waterbody extraction of tidal flats from remote sensing images, and the IoU of our method is 2.43% higher than YOLOv3 and 3.7% higher than U-Net (Freiburg, Germany).

A major goal of The Patient Protection and Affordable Care Act is to broaden health care access through the extension of insurance coverage. However, little attention has been given to growing disparities in access to health care among the insured, as trends to reduce benefits and increase cost sharing (deductibles, co-pays) reduce affordability and access. Through a political economic perspective that critiques moral hazard, this article draws from ethnographic research with the United Steelworkers (USW) at a steel mill and the Retail, Wholesale and Department Store Union (RWDSU) at a food-processing plant in urban Central Appalachia. In so doing, this article describes difficulties of health care affordability on the eve of reform for differentially insured working families with employer-sponsored health insurance. Additionally, this article argues that the proposed Cadillac tax on high-cost health plans will increase problems with appropriate health care access and medical financial burden for many families.

OBJECTIVE: We compared the physician-assessed diagnostic likelihood of SLE resulting from standard diagnosis laboratory testing (SDLT) to that resulting from multianalyte assay panel (MAP) with cell-bound complement activation products (MAP/CB-CAPs), which reports a two-tiered index test result having 80% sensitivity and 86% specificity for SLE. METHODS: Patients (n=145) with a history of positive antinuclear antibody status were evaluated clinically by rheumatologists and randomised to SDLT arm (tests ordered at the discretion of the rheumatologists) or to MAP/CB-CAPs testing arm. The primary endpoint was based on the change in the physician likelihood of SLE on a five-point Likert scale collected before and after testing. Changes in pharmacological treatment based on laboratory results were assessed in both arms. Statistical analysis consisted of Wilcoxon and Fisher's exact tests. RESULTS: At enrolment, patients randomised to SDLT (n=73, age=48±2 years, 94% females) and MAP/CB-CAPs testing arms (n=72, 50±2 years, 93% females) presented with similar pretest likelihood of SLE (1.42±0.06 vs 1.46±0.06 points, respectively; p=0.68). Post-test likelihood of SLE resulting from randomisation in the MAP/CB-CAPs testing arm was significantly lower than that resulting from randomisation to SDLT arm on review of test results (-0.44±0.10 points vs -0.19±0.07 points) and at the 12-week follow-up visit (-0.61±0.10 points vs -0.31±0.10 points) (p<0.05). Among patients randomised to the MAP/CB-CAPs testing arm, two-tiered positive test results associated significantly with initiation of prednisone (p=0.034). CONCLUSION: Our data suggest that MAP/CB-CAPs testing has clinical utility in facilitating SLE diagnosis and treatment decisions.

School nurses play a crucial role in injury prevention and initial treatment when injuries occur at school. The role of school nurses includes being knowledgeable about the management of head injuries, including assessment and initial treatment. The school nurse must be familiar with the outcomes of a head injury and know when further evaluation is indicated. Developing a head injury protocol in the school setting is one strategy to make sure that all involved are able to consistently and effectively respond to a head injury and prevent a possible negative outcome. The combination of a protocol, nursing judgment, and best practices can ensure that all means are used to take care of children when a head injury is sustained. These strategies will help to increase the safety of children at school. A systematic approach to the management of these types of injuries is essential for preventing possible complications.

It has now been more than 15 yr since the defining articles by Daughton and Ternes 1 and Halling-Sørensen 2 identified pharmaceuticals in the environment as an important issue. Subsequently, a study by Kolpin et al. 3 confirmed the widespread presence of pharmaceuticals in freshwater ecosystems, leading to intensive research in that field. Since then, numerous studies have reported the presence of pharmaceuticals in environmental matrices that were directly or indirectly receiving wastewater discharges (human pharmaceuticals) and animal wastes (veterinary pharmaceuticals) 4. The ability to detect pharmaceuticals in environmental matrices at increasingly lower sub–parts per billion concentrations drove this development to a large extent, making risk assessment of environmentally realistic exposure scenarios all the more challenging. In addition to having diverse physicochemical properties, pharmaceuticals as a class of compounds are designed to have a broad range of therapeutic modes of action. Given the conservation of biological receptors across species, it was expected that the presence of pharmaceuticals in environmental matrices might have adverse ecotoxicological implications 1, 5. Indeed, this was demonstrated in the mid 2000s through predictable 6 and unpredictable 7 exposures and subsequent devastating effects on fish and birds. Other studies showing such dramatic ecotoxicological implications for pharmaceuticals, however, have been much less prevalent than those merely measuring their presence and, to a lesser extent, their fate in the environment. Pharmaceuticals have clear health, economic and societal benefits, and restricting their use to avoid environmental risks is not desirable. Their responsible use, however, not only is attractive to reduce environmental impacts but also helps improve healthcare outcomes and costs 8. Unlike other contaminant classes (such as personal care products), pharmaceuticals are well-studied compounds and have substantial available data on their fate and effects in mammalian systems, which can be used to better understand their environmental hazards and risks 9-11. In 2009, a decade after the first publications highlighted pharmaceuticals in the environment as an issue for environmental research, assessment, and management, Environmental Toxicology and Chemistry (ET&C) published a special issue on the topic to distill the main findings from a decade of intense and growing scientific interest. It was apparent from that special issue that research interest in this area was becoming more refined. Following an increasing number of reports demonstrating the widespread contamination of freshwater systems with pharmaceuticals, their bioavailability was demonstrated in freshwater fish 12, along with the recognition that this could have consequences for ecologically significant effects on behavior 13 and development 14. At the same time, challenges in the ecotoxicological assessment of metabolites and mixtures were identified 15, 16. Furthermore, the issue of perceived potency was addressed in numerous papers with respect to endocrine active pharmaceuticals, cytotoxic pharmaceuticals, and selective serotonin re-uptake inhibitors 13, 14, 17-19. The fate of pharmaceuticals in compartments other than freshwater, the use of readily available pharmacological data, and the potential consequences of the effects of antibiotics on bacterial communities also received some attention 20, 21. The likely global presence of pharmaceuticals beyond the traditionally scrutinized environments in North America and Europe was also highlighted 20, 22. Based on the contributions to that first ET&C special issue on pharmaceuticals in the environment, recommendations for future work focused on the prioritization of pharmaceuticals for environmental assessment to enable better use of limited resources 23. Establishing the importance of environmental processes that determine their ultimate fate in the environment, how this affects exposure assessments, and the implications on bioavailability in a range of environmental compartments were considered critical for a predictive understanding. With respect to effects assessment, it was recommended that the knowledge generated during the registration process of pharmaceuticals should be used for improving decisions related to environmental hazards and risks. The importance of understanding the mode of action of a pharmaceutical in nontarget organisms also was highlighted. Seven years after that first ET&C special issue, it is obvious that scientific interest in the issue of pharmaceuticals in the environment is still strong, measured, for example, in the sheer quantity of peer-reviewed publications and meeting abstracts. The number of contributions submitted to the present special issue is also indicative of the ongoing research interest in the topic. In this context, it is worth noting that SETAC's Pharmaceuticals Advisory Group (PAG) did not preselect the content of the present special issue, and thus the special issue represents a true reflection of the current work in the field. Prioritization strategies is one area that has received considerable attention in the present special issue and elsewhere in the literature, with a number of articles proposing risk-based approaches, taking into account not only anticipated exposure levels but also the relative potency of the compounds 24-29. Despite some differences in the composition of prioritization lists, the represented pharmaceutical classes overlap and include antibiotics, selective serotonin reuptake inhibitors (SSRIs), antidepressants, endocrine active pharmaceuticals, and nonsteroidal anti-inflammatory drugs. Although the presence of pharmaceuticals in the environment used in such prioritization strategies can be predicted based largely on their usage volumes, it is critical to ensure that social and cultural factors also are taken into account, as they can greatly influence both temporal and geographical variability 30. In the absence of environmental exposure or effects assessments, Berninger et al. 31 outline how available mammalian pharmacological data can be used to rank the likely hazards of pharmaceuticals to fish. This highlights the value of pre-existing data, an important distinction from other environmental contaminants 9, 11. However, using such information for predicting relevant effects in nontarget organisms in the environment remains problematic. Numerous studies in the present special issue focused on SSRIs, which target the well-conserved neurotransmitter serotonin in humans, all highlighting the potential for their effects at low concentrations 32-35. Exposure of fish to SSRI mixtures was demonstrated to influence the levels of serotonin in the brain, with potential behavioral consequences 34. The reasons for observed effects in invertebrates are less clear, with nonmonotonic dose–response relationships, large interspecies variability, and serotonin-independent effects apparent 32. Other less predictable effects of SSRIs include a decrease in the expression of microRNA, which is usually related to endocrine function 35, and an increase in T lymphocyte production in fish 33. Furthermore, the bioavailability of ionizable pharmaceuticals, such as SSRIs. is likely to be variable in a range of environments and organisms 32, 36, adding even more complexity to their environmental assessment. Additionally, it has long been recognized that the assessment of mixture effects is critical for a realistic assessment of pharmaceuticals in the environment. This also presents a major challenge for ecotoxicologists because of inherent complexities in study design and interpretation 37. Pharmaceuticals have well-defined interactions when used as therapeutic mixtures within the relatively stable internal environment of mammals, and this knowledge could be explored further to improve the understanding of mixture toxicity in nontarget organisms 37. In contrast to the known and comparatively stable mixture composition found in target organisms, wastewater contains highly variable loads of pharmaceuticals, whose effects are further modified by fluctuating water quality parameters. This was highlighted by a number of ecotoxicological studies in the present special issue in which nonmonotonic dose–response and temporal variations in endpoint values occurred 33, 34, 38. When Brodin et al. 39 demonstrated that exposure to a single concentration of a benzodiazepine increases activity and reduces sociality in fish, the effects of pharmaceuticals on behavioral traits attracted widespread scientific attention. Two studies in the present special issue noted reduced feeding rates and aggression in fish following exposure to mixtures of SSRIs, opioids, and benzodiazepine 33, 34, although the implications of such changes in behavior at different levels of biological organization remain to be fully understood. Such integrative ecotoxicological approaches hold much promise for characterizing the environmental risks of pharmaceuticals, despite their inherent variability. More work is needed, however, to correlate physiological responses to population-level effects 23. The complex patterns often found in ecotoxicological data for pharmaceuticals reflects not only the physiological and ecological complexity of exposed organisms and communities but also the temporal variability of pharmaceutical concentrations and the fluctuating physicochemical properties of the receiving environments, both of which affect the bioavailable fractions of pharmaceuticals and the overall risk to exposed organisms 40. Research focus previously has been on freshwater systems, and marine ecosystems have been identified here as being underrepresented and requiring further investigation 41. This is particularly important in coastal environments, where human impacts are pronounced and dynamic, in terms of daily physicochemical cycles; the use of innovative methods for examining bioavailability and potential risks to marine organisms is therefore highly desirable 40, 42. In addition, the terrestrial environment increasingly is receiving attention, especially with respect to crop exposure through wastewater and biosolids application. Other terrestrial pathways, however, such as inputs of veterinary medicines 43 or landfill leachates 44, still receive comparatively little attention. As our understanding of the geographic and temporal variability of pharmaceuticals in the environment increases, the assessment of pharmaceuticals thought to be already well-characterized continues to evolve. For example, environmental quality standards accepted by some jurisdictions for carbamazepine, a commonly encountered antiepileptic pharmaceutical, are likely to be exceeded in several exposure scenarios 45. Elucidating the role of environmental processes for causing antimicrobial resistance might also warrant increased attention in the future, particularly because antibiotics are commonly detected in various ecosystems. For example, sulfamethoxazole is ubiquitous in aquatic urban environments throughout the United States, confirming previous studies 46, 47, but its impact on antimicrobial resistance is largely unknown 48. So far, SETAC as a society has not been engaged much in research on antimicrobial resistance, but our members' collective skills in environmental chemistry, ecotoxicology, and environmental sciences make us well placed to provide important contributions to this critical global issue in the future. Given their importance and widespread use in human society, pharmaceuticals are expected to occur globally, yet only a fraction of the pharmaceuticals on the market are monitored. More strategic monitoring programs are required 30, 47, 49, adequately considering pharmacology (e.g., pharmacokinetics, therapeutic potency), geography (e.g., urban density, healthcare or manufacturing facilities, hydrology, environments receiving discharges), societal factors (e.g., use preferences, prevalence of disease, social acceptance), and economic factors (e.g., wealth, healthcare access, subsidies). Such activities will be critical for an effective use of resources and an improved understanding of the risks of pharmaceuticals in environmentally realistic settings 50. Using such information is especially critical as awareness of the global nature of pharmaceuticals in the environment gains increased recognition even in the absence of monitoring information 51. Innovative approaches for identifying the most likely compounds to be present in the environment are needed to enable the effective design of monitoring programs. This is especially pertinent to jurisdictions where previous assumptions may be tenuous because, for example, prescription data is not readily available, therapeutic dosing does not follow indicated uses in human and veterinary applications, and different discharge pathways into the environment may exist 50, 52. As wealth and population increase in regions of low- to medium-income nations in Asia, Africa, and the Americas, pharmaceutical use and entry into the environment also will increase 50. This is caused by the globalization not only of markets for therapeutic use but also of manufacturing facilities, with the need for managing not only environmental but also relevant social risks 53, 54. The expertise of SETAC members will be critical in providing sound scientific advice to policymakers, regulatory bodies, and industry to enable them to make the most effective decisions, based on environmental risks, economic limitations, and societies' expectations. We hope that the studies in the present special issue will make a contribution toward providing new understanding and more refined approaches, thus stimulating further interest relating to the assessment of pharmaceuticals in the environment. We also hope that future special issues relating to pharmaceuticals in the environment will be forthcoming in ET&C, building on the work highlighted in the present issue as well as research priorities identified elsewhere 4. The multidisciplinary and global nature of SETAC is ideally suited to inform regional and global understanding of environmental risks of pharmaceuticals—through engagement not only with regulators and industry but increasingly with human health professionals, environmental engineers, social scientists, nongovernment organizations, economists, and others—to enable socially relevant, economically viable, and technically effective management of pharmaceuticals in the environment. Mike Williams CSIRO Land and Water South Australia, Australia Thomas Backhaus Department of Biological and Environmental Sciences University of Gothenburg Gothenburg, Sweden Craig Bowe Department of Science Ohio University Ironton, OH, USA Kyungho Choi School of Public Health Seoul National University Seoul, Republic of Korea Kristin Connors Oak Ridge Institute for Science and Education Oak Ridge, TN, USA Silke Hickmann Environmental Risk Assessment of Pharmaceuticals German Environment Agency Dessau-Roßlau, Germany Wesley Hunter Center for Veterinary Medicine US Food and Drug Administration Rockville, MD, USA Rai Kookana CSIRO Land and Water South Australia, Australia Ruth Marfil-Vega American Water Belleville, IL, USA Tim Verslycke Gradient Cambridge, MA, USA We would like to acknowledge the vast contributions not included in the present special issue that other groups have made to this area of research. Specifically, we would like to highlight the great contributions to this area of research made by M. Schultz (Wooster University, Wooster, OH, USA), who tragically died before she could submit her intended paper to the present special issue. The body of research she published has given us a great insight into the presence and fate of pharmaceuticals (particularly SSRIs), and her substantive and creative contributions will be sorely missed.

Abstract For an integer s ≥ 0, a graph G is s ‐hamiltonian if for any vertex subset with | S ′ | ≤ s , G ‐ S ′ is hamiltonian. It is well known that if a graph G is s ‐hamiltonian, then G must be ( s +2)‐connected. The converse is not true, as there exist arbitrarily highly connected nonhamiltonian graphs. But for line graphs, we prove that when s ≥ 5, a line graph is s ‐hamiltonian if and only if it is ( s +2)‐connected.

Fanconi anemia (FA) is a complex genetic disorder associated with progressive marrow failure and a strong predisposition to malignancy. FA is associated with metabolic disturbances such as short stature, insulin resistance, thyroid dysfunction, abnormal body mass index (BMI), and dyslipidemia. We studied tryptophan metabolism in FA by examining tryptophan and its metabolites before and during the stress of hematopoietic stem cell transplant (HSCT). Tryptophan is an essential amino acid that can be converted to serotonin and kynurenine. We report here that serotonin levels are markedly elevated 14 days after HSCT in individuals with FA, in contrast to individuals without FA. Kynurenine levels are significantly reduced in individuals with FA compared with individuals without FA, before and after HSCT. Most peripheral serotonin is made in the bowel. However, serotonin levels in stool decreased in individuals with FA after transplant, similar to individuals without FA. Instead, we detected serotonin production in the skin in individuals with FA, whereas none was seen in individuals without FA. As expected, serotonin and transforming growth factor β (TGF-β) levels were closely correlated with platelet count before and after HSCT in persons without FA. In FA, neither baseline serotonin nor TGF-B correlated with baseline platelet count (host-derived platelets), only TGF-B correlated 14 days after transplant (blood bank-derived platelets). BMI was negatively correlated with serotonin in individuals with FA, suggesting that hyperserotonemia may contribute to growth failure in FA. Serotonin is a potential therapeutic target, and currently available drugs might be beneficial in restoring metabolic balance in individuals with FA.

Wireless sensor network technology integrates the sensor, computing and wireless technologies. Interconnecting wireless sensor and IP (Internet Protocol) networks could help bridging physical world to our information infrastructure. It could also help external monitoring and control of wireless sensor networks. Interconnecting two networks offers several research challenges in several areas such as addressing, protocol inter-working and routing. This paper examines those challenges and presents a framework for interconnecting IP and wireless sensor networks using inter- working at the transport layer.

This case study discusses the transformative impact of implementing the tenets of Invitational Education (IE) theory and practice upon a rural elementary school and subsequent preparation of teacher candidates. Through the lens of hermeneutic phenomenology the researcher examined the transformative change as IE theory and practice was exhibited and communicated by students, teachers, administration, staff, families, and the community at large. As a result of implementation, the culture and climate of the school became more positive. People of all ages joined and experienced a metamorphosis that extended from the school into the community. Changes included improved student behavior, greater trust between families and teachers, increased parental involvement and an expansion of the school culture into the community. Between 2010, when there had been more than 100 days of Out-of-School Suspensions issued to students for aggressive behavior and 2013, when only 13 days were missed by students due to suspension (according to West Virginia Education Information System data), the elementary school evolved from a low-performing, negative environment into a child-centered hub of learning where the climate reflected familial connection and care beyond academics. This became evident in the interaction between students and their teachers, families with the school, and between employees within the elementary setting. This case study documents that journey through the lens of hermeneutic phenomenology for the purpose of replication at other schools.