The Polycomb group protein Eed protects the inactive X-chromosome from differentiation-induced reactivation.

The Polycomb group (PcG) encodes an evolutionarily conserved set of chromatin-modifying proteins that are thought to maintain cellular transcriptional memory by stably silencing gene expression. In mouse embryos that are mutated for the PcG protein Eed, X-chromosome inactivation (XCI) is not stably maintained in extra-embryonic tissues. Eed is a component of a histone-methyltransferase complex that is thought to contribute to stable silencing in undifferentiated cells due to its enrichment on the inactive X-chromosome in cells of the early mouse embryo and in stem cells of the extra-embryonic trophectoderm lineage. Here, we demonstrate that the inactive X-chromosome in Eed(-/-) trophoblast stem cells and in cells of the trophectoderm-derived extra-embryonic ectoderm in Eed(-/-) embryos remain transcriptionally silent, despite lacking the PcG-mediated histone modifications that normally characterize the facultative heterochromatin of the inactive X-chromosome. Whereas undifferentiated Eed(-/-) trophoblast stem cells maintained XCI, reactivation of the inactive X-chromosome occurred when these cells were differentiated. These results indicate that PcG complexes are not necessary to maintain transcriptional silencing of the inactive X-chromosome in undifferentiated stem cells. Instead, PcG proteins seem to propagate cellular memory by preventing transcriptional activation of facultative heterochromatin during differentiation.

Composite B-cell and T-cell lineage post-transplant lymphoproliferative disorder of the lung with unusual cutaneous manifestations of mycosis fungoides.

We present the case of a 17-year-old male kidney transplant recipient who presented initially with dermatologic symptoms and was found to have histologic changes in the skin that were consistent with mycosis fungoides. Shortly after this diagnosis was made, imaging studies demonstrated multifocal interstitial and airspace consolidation in both lungs. Physical examination revealed no lymphadenopathy or hepatosplenomegaly, but an open lung biopsy revealed an Epstein-Barr virus (EBV)-negative monomorphic T-cell posttransplant lymphoproliferative disorder (PTLD) with a concomitant EBV-positive B-cell PTLD involving the same lesion of the lung. Polymerase chain reaction analysis demonstrated clonal T-cell receptor gene rearrangements in both the skin and the lung biopsies. Interestingly, 1 clone was shared between the skin and lung while a second clone was present only in the lung. To our knowledge, this is the first reported case of a PTLD presenting in the skin in which there was a subsequent discovery of composite, bilineal B- and T-cell PTLD of the lung.

Medical management of stable coronary artery disease.

All patients with stable coronary artery disease require medical therapy to prevent disease progression and recurrent cardiovascular events. Three classes of medication are essential to therapy: lipid-lowering, antihypertensive, and antiplatelet agents. Lipid-lowering therapy is necessary to decrease low-density lipoprotein cholesterol to a target level of less than 100 mg per dL, and physicians should consider a goal of less than 70 mg per dL for very high-risk patients. Statins have demonstrated clear benefits in morbidity and mortality in the secondary prevention of coronary artery disease; other medications that can be used in addition to statins to lower cholesterol include ezetimibe, fibrates, and nicotinic acid. Blood pressure therapy for patients with coronary artery disease should start with beta blockers and angiotensin-converting enzyme inhibitors. If these medications are not tolerated, calcium channel blockers or angiotensin receptor blockers are acceptable alternatives. Aspirin is the first-line antiplatelet agent except in patients who have recently had a myocardial infarction or undergone stent placement, in which case clopidogrel is recommended. Anginal symptoms of coronary artery disease can be treated with beta blockers, calcium channel blockers, nitrates, or any combination of these. Familiarity with these medications and with the evidence supporting their use is essential to reducing morbidity and mortality in patients with coronary artery disease.

Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning.

Using a model heat engine, we show that neural-network-based reinforcement learning can identify thermodynamic trajectories of maximal efficiency. We consider both gradient and gradient-free reinforcement learning. We use an evolutionary learning algorithm to evolve a population of neural networks, subject to a directive to maximize the efficiency of a trajectory composed of a set of elementary thermodynamic processes; the resulting networks learn to carry out the maximally efficient Carnot, Stirling, or Otto cycles. When given an additional irreversible process, this evolutionary scheme learns a previously unknown thermodynamic cycle. Gradient-based reinforcement learning is able to learn the Stirling cycle, whereas an evolutionary approach achieves the optimal Carnot cycle. Our results show how the reinforcement learning strategies developed for game playing can be applied to solve physical problems conditioned upon path-extensive order parameters.

Metal triflate formation of C12-C22 phenolic compounds by the simultaneous C-O breaking and C-C coupling of benzyl phenyl ether.

Catalytic pathways to produce high carbon number compounds from benzyl phenyl ether require multiple steps to break the aryl etheric carbon-oxygen bonds; these steps are followed by energy-intensive processes to remove oxygen atoms and/or carbon-carbon coupling. Here, we show an upgrading strategy to transform benzyl phenyl ether into large phenolic (C12-C22) compounds by a one-step C-O breaking and C-C coupling catalyzed by metal triflates under a mild condition (100 °C and 1 bar). Hafnium triflate was the most selective for the desired products. In addition, we measured the effect of solvent polarity on the catalytic performance. Solvents with a polarity index of less than 3.4 promoted the catalytic activity and selectivity to C12-C22 phenolic products. These C12-C22 phenolic compounds have potential applications for phenol-formaldehyde polymers, diesel/jet fuels, and liquid organic hydrogen carriers.

Extensive deep neural networks for transferring small scale learning to large scale systems.

We present a physically-motivated topology of a deep neural network that can efficiently infer extensive parameters (such as energy, entropy, or number of particles) of arbitrarily large systems, doing so with scaling. We use a form of domain decomposition for training and inference, where each sub-domain (tile) is comprised of a non-overlapping focus region surrounded by an overlapping context region. The size of these regions is motivated by the physical interaction length scales of the problem. We demonstrate the application of EDNNs to three physical systems: the Ising model and two hexagonal/graphene-like datasets. In the latter, an EDNN was able to make total energy predictions of a 60 atoms system, with comparable accuracy to density functional theory (DFT), in 57 milliseconds. Additionally EDNNs are well suited for massively parallel evaluation, as no communication is necessary during neural network evaluation. We demonstrate that EDNNs can be used to make an energy prediction of a two-dimensional 35.2 million atom system, over 1.0 µm2 of material, at an accuracy comparable to DFT, in under 25 minutes. Such a system exists on a length scale visible with optical microscopy and larger than some living organisms.

Deep neural networks for direct, featureless learning through observation: The case of two-dimensional spin models.

We demonstrate the capability of a convolutional deep neural network in predicting the nearest-neighbor energy of the 4×4 Ising model. Using its success at this task, we motivate the study of the larger 8×8 Ising model, showing that the deep neural network can learn the nearest-neighbor Ising Hamiltonian after only seeing a vanishingly small fraction of configuration space. Additionally, we show that the neural network has learned both the energy and magnetization operators with sufficient accuracy to replicate the low-temperature Ising phase transition. We then demonstrate the ability of the neural network to learn other spin models, teaching the convolutional deep neural network to accurately predict the long-range interaction of a screened Coulomb Hamiltonian, a sinusoidally attenuated screened Coulomb Hamiltonian, and a modified Potts model Hamiltonian. In the case of the long-range interaction, we demonstrate the ability of the neural network to recover the phase transition with equivalent accuracy to the numerically exact method. Furthermore, in the case of the long-range interaction, the benefits of the neural network become apparent; it is able to make predictions with a high degree of accuracy, and do so 1600 times faster than a CUDA-optimized exact calculation. Additionally, we demonstrate how the neural network succeeds at these tasks by looking at the weights learned in a simplified demonstration.

Association of pain and itch with depth of invasion and inflammatory cell constitution in skin cancer: results of a large clinicopathologic study.

IMPORTANCE: This study highlights a simple bedside evaluation of itch and pain for suspicious skin lesions. OBJECTIVE: To examine the correlation of pain and itch with histologic features of skin cancers. DESIGN, SETTING, AND PARTICIPANTS: This large, prospective, clinicopathologic study enrolled patients who filled out questionnaires that assessed itch and pain intensity of their skin tumors at the time of excision. Study participants were from the patient population presenting to the Department of Dermatology surgical unit at Wake Forest University Baptist Medical Center from July 1, 2010, through March 31, 2011. Study participants included 268 patients, representing 339 histopathologically confirmed cutaneous neoplasms. The following skin cancer subtypes were represented in this analysis: 166 basal cell carcinomas, 146 squamous cell carcinomas, and 27 melanomas. MAIN OUTCOMES AND MEASURES: Itch and pain associated with skin cancer at the time of excision ranked on an 11-point (score range, 0-10) numerical visual analog scale and histopathologic analysis for each neoplasm (assessment of the amount and type of inflammation, ulceration, perineural invasion, and depth of invasion). RESULTS: The prevalence of itch and pain across all skin cancers was 36.9% and 28.2%, respectively. However, these symptoms were mostly absent in melanomas. Pain intensity was significantly associated with the degree of inflammation (mild or none vs moderate or marked; P < .001), presence of neutrophils in the inflammatory infiltrate (predominantly mononuclear vs mixed or neutrophilic; P = .003), presence of eosinophils (present vs absent; P = .007), ulceration (yes vs no; P = .003), perineural invasion (yes vs no; P < .001), depth of invasion (P = .001), and largest diameter length of skin lesion (P < .003). Itch intensity was significantly associated with the degree of inflammation (mild or none vs moderate or marked; P = .001) and the presence of eosinophils (present vs absent; P = .02). CONCLUSIONS AND RELEVANCE: These findings support the theory that itch emanates from the upper layers of the skin, whereas pain is associated with deeper processes. This study also reports that a simple bedside assessment for the presence and intensity of pain or itch is an easily implementable tool for physicians evaluating suspicious skin lesions.

Epidermolysis bullosa pruriginosa masquerading as psychogenic pruritus.

BACKGROUND: Epidermolysis bullosa pruriginosa is a rare clinical subtype of dystrophic epidermolysis bullosa characterized by intense pruritus, secondary scratching-induced lesions, and pronounced scarring. OBSERVATIONS: We describe a patient with epidermolysis bullosa pruriginosa who was misdiagnosed as having psychogenic pruritus for several years. Except for nail (toenail) dystrophy, no features of the disease were evident among his immediate family members. An underlying new heterozygous donor splice-site mutation in the type VII collagen gene (IVS55 + 1G>C) was found in both the patient and his family members with nail dystrophy. Inheritance was autosomal dominant. The patient was treated with cyclosporine and experienced significant reduction in pruritus, with subsequent improvement of the skin condition. CONCLUSIONS: Pruritus is an important factor in the development of epidermolysis bullosa pruriginosa and is the focus of management. Patients with this inherited skin disorder can be easily misdiagnosed as having psychogenic pruritus, and this article aims to make physicians aware of this diagnostic pitfall.

Treatment of nursing home-acquired pneumonia.

Pneumonia is an important cause of morbidity and mortality in nursing home residents, with 30-day mortality rates ranging from 10 to 30 percent. Streptococcus pneumoniae is the most common cause of nursing home-acquired pneumonia, although Staphylococcus aureus and gram-negative organisms may be more common in severe cases. Antibiotic therapy for nursing home-acquired pneumonia should target a broad range of organisms, and drug-resistant microbes should be considered when making treatment decisions. In the nursing home setting, treatment should consist of an antipneumococcal fluoroquinolone alone or either a high-dose beta-lactam/beta-lactamase inhibitor or a second- or third-generation cephalosporin, in combination with azithromycin. Treatment of hospitalized patients with nursing home-acquired pneumonia requires broad-spectrum antibiotics with coverage of many gram-negative and gram-positive organisms, including methicillin-resistant S. aureus. Appropriate dosing of antibiotics for nursing home-acquired pneumonia is important to optimize effectiveness and avoid adverse effects. Because many nursing home residents take multiple medications, it is important to consider possible drug interactions.