A case of antiphospholipid syndrome following gastric signet ring cell adenocarcinoma

Objective: Rare disease Background: Antiphospholipid syndrome (APS) is a rare autoimmune disease characterized by arterial, venous, and small-vessel thrombosis, pregnancy-related morbidity and the presence of antiphospholipid antibodies such as an-ticardiolipin antibody, and/or anti-beta2-glycoprotein I. In the recent years, APS was observed in patients with solid tumors and the renal cancer, lung carcinoma and breast tumors were the most common tumors linked with APS. Case Report: A 53-year-old female presented with pain and pitting edema of left lower extremity that had begun 6 months prior to hospitalization. Deep vein thrombosis (DVT) in the popliteal vein diagnosed by Doppler ultrasonogra-phy and the patient was treated with heparin followed by warfarin. Following subdural hematoma, anticoagu-lant therapy was stopped, and the patient underwent craniotomy. One month later, the patient returned with pain and DVT diagnosed in its right leg. Laboratory tests showed high levels of lupus anticoagulant, IgM and IgG anticardiolipin antibodies. Following a high alkaline phosphatase, diffuse bone marrow involvement was found by whole body bone scan. Looking to find primary tumor, a large infilterable lesion in gastric was seen by endoscopic images, and biopsy histopathology showed a signet ring cell adenocarcinoma. The patient re-fused chemotherapy and died 6 months after diagnosis. Conclusions: APS is associated with gastric signet ring cell adenocarcinoma. © Am J Case Rep, 2020

The IDIP framework for assessing protein function and its application to the prion protein

The quest to determine the function of a protein can represent a profound challenge. Although this task is the mandate of countless research groups, a general framework for how it can be approached is conspicuously lacking. Moreover, even expectations for when the function of a protein can be considered to be ‘known’ are not well defined. In this review, we begin by introducing concepts pertinent to the challenge of protein function assignments. We then propose a framework for inferring a protein's function from four data categories: ‘inheritance’, ‘distribution’, ‘interactions’ and ‘phenotypes’ (IDIP). We document that the functions of proteins emerge at the intersection of inferences drawn from these data categories and emphasise the benefit of considering them in an evolutionary context. We then apply this approach to the cellular prion protein (PrP^{C}), well known for its central role in prion diseases, whose function continues to be considered elusive by many investigators. We document that available data converge on the conclusion that the function of the prion protein is to control a critical post-translational modification of the neural cell adhesion molecule in the context of epithelial-to-mesenchymal transition and related plasticity programmes. Finally, we argue that this proposed function of PrP^{C} has already passed the test of time and is concordant with the IDIP framework in a way that other functions considered for this protein fail to achieve. We anticipate that the IDIP framework and the concepts analysed herein will aid the investigation of other proteins whose primary functional assignments have thus far been intractable

Potential Application of Electrical Conductivity (EC) Map for Variable Rate Seeding

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 7 (2005): Potential Application of Electrical Conductivity (EC) Map for Variable Rate Seeding by M. R. Ehsani, C. D. Durairaj, S. Woods, M. Sulliva

Effect of plant canopy shape and flowers on plant count accuracy using remote sensing imagery

Separate experiments were conducted to evaluate the effect of plant canopy shape and presence of flowers on counting accuracy of container-grown plants.  Images were taken at 12 m above the ground.  Two species of juniper (Juniperus chinensis L. ‘Sea Green’ and Juniperus horizontalis Moench ‘Plumosa Compacta’) were selected to evaluate plant shape and Coral Drift ® rose (Rosa sp. ‘Meidrifora’) was used to evaluate the presence of flowers on plant count.  Counting algorithms were trained using Feature Analyst (FA).  Total counting error, false positives and unidentified plants were reported. There was no difference between all variables measured when an algorithm trained with an image displaying regular or irregular plant canopy shape was applied to images displaying both plant canopy shapes even though the canopy shape of ‘Sea Green’ is less compact than ‘Plumosa Compacta’.  There was a significant difference in all variables measured between images of flowering and non-flowering plants when non-flowering ‘samples’ were used the train the counting algorithm in FA; total counting errors and unidentified plants was greater for flowering plants.  In this specific case, applying an algorithm that did not include a training set displaying flowers, resulted in a less accurate count.  Algorithms developed using FA appears to be fairly robust under these conditions

Prophet Inequalities for IID Random Variables from an Unknown Distribution

A central object in optimal stopping theory is the single-choice prophet inequality for independent, identically distributed random variables: given a sequence of random variables X1, . . . , Xn drawn independently from a distribution F , the goal is to choose a stopping time τ so as to maximize α such that for all distributions F we have E[Xτ ] ≥ α · E[maxt Xt ]. What makes this problem challenging is that the decision whether τ = t may only depend on the values of the random variables X1, . . . , Xt and on the distribution F . For a long time the best known bound for the problem had been α ≥ 1 − 1/e ≈ 0.632, but quite recently a tight bound of α ≈ 0.745 was obtained. The case where F is unknown, such that the decision whether τ = t may depend only on the values of the random variables X1, . . . , Xt , is equally well motivated but has received much less attention. A straightforward guarantee for this case of α ≥ 1/e ≈ 0.368 can be derived from the solution to the secretary problem, where an arbitrary set of values arrive in random order and the goal is to maximize the probability of selecting the largest value. We show that this bound is in fact tight. We then investigate the case where the stopping time may additionally depend on a limited number of samples from F , and show that even with o(n) samples α ≤ 1/e. On the other hand, n samples allow for a significant improvement, while O(n2) samples are equivalent to knowledge of the distribution: specifically, with n samples α ≥ 1 − 1/e ≈ 0.632 and α ≤ ln(2) ≈ 0.693, and with O(n2) samples α ≥ 0.745 − ε for any ε > 0

Driving performance in older adults: Current measures, findings, and implications for roadway safety

BACKGROUND AND OBJECTIVES: Over 10,000 people a day turn 65 in the United States. For many older adults, driving represents an essential component of independence and is one of the most important factors in overall mobility. Recent survey studies in older adults suggest that up to 60% of older adult drivers with mild cognitive impairment, and up to 30% with dementia, continue to drive. The purpose of this review is to provide a comprehensive and detailed resource on the topics of cognition and driving for clinicians, researchers, and policymakers working on efforts related to older adult drivers. RESEARCH DESIGN AND METHODS: Publications on PubMed and Medline and discussions with experts working in geriatrics, technology, driving policy, psychology, and diverse aspects of driving performance were utilized to inform the current review. RESULTS: Research indicates that there is a complex and inverse correlation between multiple cognitive measures, driving performance, and risky driving behaviors. The fragmented nature of available peer-reviewed literature, and a reliance on correlative data, do not currently allow for the identification of the temporal and reciprocal nature of the interplay between cognition and driving endpoints. DISCUSSION AND IMPLICATIONS: There are currently no widely accepted definitions, conceptual models, or uniform set of analyses for conducting geriatric research that is focused on driving. Establishing conventions for conducting research that harmonizes the fields of geriatrics, cognition, and driving research is critical for the development of the evidence base that will inform clinical practice and road safety policy

Reformism, Economic Liberalisation and Popular Mobilisation in Iran

Whereas in other MENA countries the impact of neo-liberal policies has been the subject of intense debate, there are at present few voices that directly analyse or critique its social and political consequences in Iran. This article seeks to address this lacuna by analysing the dynamics of reformism, economic liberalisation and popular mobilisation in Iran. It charts the country’s move from a post-revolutionary populism to a liberalised yet increasingly exclusivist model of politics and compares this to trajectories of economic liberalisation in Egypt. Two distinct outcomes of economic reform are analysed in the first part of the article: Socio-economic exclusion; and the contraction of political rights. In the second half, I investigate the ways successive post-war governments in Iran have packaged neo-liberal reforms, and how their re-imagining of the role of the state has led to differing levels of popular resistance. Finally I argue that under the present administration, political elites increasingly are oriented toward strengthening the state and seeking to limit opposition to their policies. However, the absence of neo-liberal hegemony in Iran means that growing mobilization on socio-economic issues is challenging these policies. The Right in Iranian politics is utilizing this mobilisation to present a populist challenge to the reformists in power