cssi/SciSciGPT-SciSciNet huggingface dataset:
Altered beta-adrenergic and muscarinic response of CFTR Cl- current in dialyzed cardiac myocytes

Autonomic regulation of the cardiac cystic fibrosis transmembrane conductance regulator (CFTR) Cl- current was studied in isolated guinea pig ventricular myocytes using various configurations of the whole cell patch-clamp technique. When currents were recorded using the conventional patch-clamp technique, it was possible to continue to activate the Cl- current on repeated exposure to isoproterenol (Iso) for up to 60 min after initiating dialysis. However, there was significant rundown of the magnitude of the Cl- current response to the maximally stimulating concentrations of Iso. In addition, the concentration of Iso that produced half-maximal activation of the Cl- current (K1/2) increased with time. Conversely, the K1/2 for acetylcholine inhibition of the Iso-activated current decreased with time. When currents were recorded using the perforated patch-clamp technique, the sensitivity to both beta-adrenergic- and muscarinic-receptor stimulation was stable. Immediately after initiation of dialysis with the conventional patch-clamp technique, the sensitivity to Iso was nearly identical to that determined using the perforated patch-clamp technique. However, the initial sensitivity to muscarinic-receptor activation was significantly greater. These results indicate that cell dialysis associated with conventional patch-clamp techniques not only results in a time-dependent rundown of current amplitude, but it also significantly alters the concentration dependence of beta-adrenergic and muscarinic-receptor regulation of ion channel function.
Compiler construction of idempotent regions and applications in architecture design

In the field of computer architecture today, out-of-order execution is important to maximize architectural efficiency, the shadow of unreliable hardware is ever-looming, and, with the emergence of mainstream parallel hardware, programmability is once again an important and fundamental challenge. Traditionally, hardware checkpointing and buffering techniques are used to assist with each of these problems. However, these techniques introduce overheads, add complexity to the hardware, and often save more state than necessary. With today's renewed focus on energy efficiency, and with the commercial importance of reduced hardware complexity in today's processor market, the efficacy of these techniques is no longer absolute. This thesis develops a novel compiler-based technique to efficiently support a range of hardware features without the need for checkpoints or buffers. The technique breaks programs into idempotent regions—regions that can be freely re-executed—to enable recovery by simple re-execution. The thesis observes that programs can be executed entirely as sequences of {idempotent} regions, develops static analysis and compiler code generation techniques to construct idempotent regions, and demonstrates low overheads and potentially large region sizes for an LLVM-based compiler implementation. Finally, it demonstrates applicability across a range of modern architecture designs in addressing a variety of problems. The thesis presents several findings. First, it finds that a compiler, through careful allocation of function-local state, is capable of constructing large idempotent regions in the range of tens to hundreds of instructions. These regions can be sub-divided into smaller regions to optimize for specific constraints. However, code generation of small idempotent regions forces relatively high compiler-induced run-time overheads in the range of 10–20%, while, for larger regions, this overhead quickly approaches zero as region size grows beyond a few tens of instructions. Thus, the compiler-induced costs of constructing small regions are often out-weighed by any benefits, and optimization trade-offs thus generally favor constructing regions that are a few tens of instructions or more. This optimization goal tailors the suitability of idempotence-based recovery to specific architecture domains; this thesis considers specifically architecture design and evaluation for general exception support in GPUs, out-of-order retirement in general-purpose processors, and hardware fault tolerance in emerging processor designs.
Automated Text Data Mining Analysis of Five Decades of Educational Leadership Research Literature: Probabilistic Topic Modeling of EAQ Articles From 1965 to 2014

Purpose: The purpose of this study is to describe the underlying topics and the topic evolution in the 50-year history of educational leadership research literature. Method: We used automated text ...
Comparison of Thrombelastography-Derived Fibrinogen Values at Rewarming and Following Cardiopulmonary Bypass in Cardiac Surgery Patients.

Background The inflated costs and documented deleterious effects of excess perioperative transfusion have led to the investigation of targeted coagulation factor replacement strategies. One particular coagulation factor of interest is factor I (fibrinogen). Hypofibrinogenemia is typically tested for using time-consuming standard laboratory assays. The thrombelastography (TEG)-based functional fibrinogen level (FLEV) provides an assessment of whole blood clot under platelet inhibition to report calculated fibrinogen levels in significantly less time. If FLEV values obtained on cardiopulmonary bypass (CPB) during rewarming are similar to values obtained immediately after the discontinuation of CPB, then rewarming values could be used for preemptive ordering of appropriate blood product therapy. Methods Fifty-one cardiac surgery patients were enrolled into this prospective nonrandomized study to compare rewarming fibrinogen values with postbypass values using TEG FLEV assays. Baseline, rewarming, and postbypass fibrinogen values were recorded for all patients using both standard laboratory assay (Clauss method) and FLEV. Mixed-effects regression models were used to examine the change in TEG FLEV values over time. Bland-Altman analysis was used to examine bias and the limits of agreement (LOA) between the standard laboratory assay and FLEVs. Results Forty-nine patients were included in the analysis. The mean FLEV value during rewarming was 333.9 mg/dL compared with 332.8 mg/dL after protamine, corresponding to an estimated difference of -1.1 mg/dL (95% confidence interval [CI], -25.8 to 23.6; P = 0.917). Rewarming values were available on average 47 minutes before postprotamine values. Bland-Altman analysis showed poor agreement between FLEV and standard assays: mean difference at baseline was 92.5 mg/dL (95% CI, 71.1 to 114.9), with a lower LOA of -56.5 mg/dL (95% CI, -94.4 to -18.6) and upper LOA of 242.4 mg/dL (95% CI, 204.5 to 280.3). The difference between assays increased after CPB and persisted after protamine administration. Conclusions Our results revealed negligible change in FLEV values from the rewarming to postbypass periods, with a CI that does not include clinically meaningful differences. These findings suggest that rewarming samples could be utilized for ordering fibrinogen-specific therapies before discontinuation of CPB. Mean FLEV values were consistently higher than the reference standard at each time point. Moreover, bias was highly heterogeneous among samples, implying a large range of potential differences between assays for any 1 patient.
France: New face at nuclear labs promises fresh links for researchers

The 7000 scientists working for France's atomic energy commission have a new boss – physicist Rene Pellat. An active researcher and respected administrator with a reputation for being a tough-talker, Pellat brings a wealth of experience to the post.
Percolation Effects and Disorder

The main object of these lectures concerns the effect of quenched disorder in ferromagnetic transitions. Much emphasis will be given to the structure of the incipient infinite cluster. Hopefully this will clarify some controversial aspects of dilute ferromagnets near the percolation threshold. The last lecture will consider the “thermal” disorder in a pure ferromagnetic system with a droplet model approach.
Society of behavioral medicine supports increasing HPV vaccination uptake: an urgent opportunity for cancer prevention

Human papillomavirus (HPV) vaccine coverage remains low in the USA. The Society for Behavioral Medicine (SBM) supports the goals outlined by Healthy People 2020, the President’s Cancer Panel, and the National Vaccine Advisory Committee to increase vaccination coverage among both males and females. SBM makes the following recommendations in support of efforts to reduce structural and other barriers to HPV vaccination services in order to increase rates of series completion. We encourage legislators and other policymakers to improve administration authority, insurance coverage, and reimbursement rates to healthcare providers who make the HPV vaccine available to adolescents; provide instrumental support to fund the development of school curricula on HPV vaccination; and increase public awareness that HPV vaccination can prevent cancer. We urge healthcare providers and healthcare systems to increase the strength, quality, and consistency of HPV vaccination recommendations for all eligible patients; to treat HPV vaccination as a routine preventive service; employ culturally appropriate communication strategies in clinical settings to educate eligible patients, parents, and guardians about the importance, effectiveness, and safety of HPV vaccination; and to strengthen and better coordinate the use of electronic medical records and immunization information systems.
Change detection by deep neural networks for synthetic aperture radar images

In this Research Experience for Undergraduate (REU) project, we develop and implement deep neural network algorithms for change detection of synthetic aperture radar (SAR) images. Deep neural networks represent a powerful data processing methodology that integrates recent deep learning techniques on neural network computing frameworks to undercover underlying features and structures of observational data. The classic change detection method for SAR images is through the difference image analysis method, i.e., filtering the noise in each before-change and after-change image and then identifying the changes between the two images. Although well researched, the difference image method requires significant pre-processing and has difficulty with applications that require high accuracy and flexibility. The proposed deep neural networks create a change detection map from original SAR images directly without generating difference images, thus providing a novel framework for change detection of complicated SAR images where speckle noise is also present. We conduct numerous experiments on artificial images with added speckle noise and real-world synthetic aperture radar images.
Building a Translational Microbiome Toolbox.

Designing successful microbiota-based therapies requires in-depth understanding of the ecological foundations of this community. In this issue, two studies by Whitaker et al. and Lim et al. provide refined genetic tools for dissecting the spatial organization and temporal dynamics of bacterial communities at the single-cell and -gene levels.
Intraoperative Near-Infrared Optical Contrast Can Localize Brain Metastases.

Introduction Approximately 100,000 brain metastases are diagnosed annually in the United States. Our laboratory has pioneered a novel technique, second window indocyanine green (SWIG), which allows for real-time intraoperative visualization of brain metastasis through normal brain parenchyma and intact dura. Methods Thirteen patients with intraparenchymal brain metastases were administered indocyanine green (ICG) at 5 mg/kg the day before surgery. A near-infrared (NIR)– capable camera was used intraoperatively to identify the tumor and to inspect surgical margins. Neuropathology was used to assess the accuracy and precision of the fluorescent dye for identifying tumor. Results ICG was infused at 24.7 ± 3.45 hours before visualization. All 13 metastases fluoresced with an average signal-to-background ratio (SBR) of 6.62. The SBR with the dura intact was 67.2% of the mean SBR once the dura was opened. The NIR signal could be visualized through normal brain parenchyma up to 7 mm. For the 39 total specimens, the mean SBR for tumor specimens ( n = 28) was 6.9, whereas the SBR for nontumor specimens ( n = 11) was 3.7. The sensitivity, specificity, positive predictive value, and negative predictive value of NIR imaging for tumor was 96.4%, 27.3%, 77.1%, and 75.0%. Discussion SWIG relies on the passive accumulation of dye in abnormal tumor tissue via the enhanced permeability and retention effect. It provides strong NIR optical contrast, which can be used to localize tumors before dural opening. The use of SWIG for margin assessment remains limited by its lack of specificity (high false-positive rate); however, ongoing improvements in imaging parameters show great potential to reduce false-positive results.
Statins decrease leptin expression in human white adipocytes.

Abstract Statin use is associated with increased calorie intake and consequent weight gain. It is speculated that statin‐dependent improvements in lipid profile may undermine the perceived need to follow lipid‐lowering and other dietary recommendations leading consequently to increased calorie intake. However, increases in calorie intake in statin users may also be related to statin‐dependent decreases in satiety factors such as leptin, an adipocyte‐derived adipokine. The objective of our study was to examine the direct effects of statins on leptin expression. Adipocytes are the main source of circulating leptin. Therefore, we examined the effects of atorvastatin and simvastatin on leptin expression in cultured human white adipocytes. We show that treatment of white adipocytes with simvastatin and atorvastatin decreases leptin mRNA expression (simvastatin: P = 0.008, atorvastatin: P = 0.03) and leptin secretion (simvastatin: P = 0.0001, atorvastatin: P = 0.0001). Both simvastatin and atorvastatin mediate decreases in leptin expression via extracellular‐signal‐regulated kinases 1/2 and peroxisome proliferator‐activated receptor gamma pathways (simvastatin: P = 0.01, atorvastatin: P = 0.026). Additionally, statin treatment also induced expected increases in adiponectin, while decreasing monocyte chemoattractant protein 1 (MCP1) mRNA. Furthermore, statins increased secretion of both total as well as high molecular weight adiponectin while decreasing MCP1 secretion. To conclude, statins act directly on human white adipocytes to regulate adipokine secretion and decrease leptin expression. Leptin is an important satiety factor. Hence, statin‐dependent decreases in leptin may contribute, at least in part, to increases in food intake in statin users.
Divergent Response of Murine and Porcine Adipocytes to Stimulation of Browning Genes by 18-Carbon Polyunsaturated Fatty Acids and Beta-Receptor Agonists

Long-chain fatty acids (LCFA) are known to activate brown and beige adipocytes. However, very little is known about the effects of the number and the position of double bonds in LCFA with the same length on brown fat-specific gene expression. To determine the specificity of LCFA in the regulation of these genes in different adipocyte models, fully differentiated 10T1/2, 3T3-L1, murine, or porcine primary adipocytes (obtained from the subcutaneous fat pad of C57BL/6 mice or Landrace × Yorkshire × Duroc crossbred piglets) were treated with 50 μM of the following 18-carbon fatty acids: stearic acid (STA; 18:0), oleic acid (OLA; 18:1, Δ9), linoleic acid (LNA; 18:2, Δ9,12), α-linolenic acid (ALA; 18:3, Δ9,12,15), γ-linolenic acid (GLA; 18:3, Δ6,9,12), or pinolenic acid (PLA; 18:3, Δ5,9,12) for 24 h with or without 4-h norepinephrine (NE) treatment. Expression levels of thermoregulatory markers were measured by quantitative real-time PCR. LNA, ALA, GLA, and PLA upregulated Ucp1 expression and tended to upregulate Pgc1a expression in murine primary adipocytes, but not in 10T1/2, 3T3-L1, and porcine primary adipocytes. In murine primary adipocytes, NE induced a higher expression of Ucp1 and Pgc1a than non-NE-treated cells, and PLA augmented the NE effect. In 10T1/2 cells, NE upregulated Ucp1 and Pgc1a expression, but there was no fatty acid effect. However, 3T3-L1 cells were insensitive to both fatty acid and beta-adrenergic agonist stimulation. These results indicate that different adipocyte cell types have different levels of sensitivity to both LCFA and beta agonists in regard to induction of brown fat-specific gene expression.
Baseline characteristics of participants in the VITamin D and OmegA-3 TriaL (VITAL): Effects on Bone Structure and Architecture.

Abstract Vitamin D supplements are often used to benefit skeletal health, although data on effects of daily high-dose vitamin D alone on bone density and structure are lacking. The ongoing VITamin D and OmegA-3 TriaL (VITAL) is a double-blind, randomized, placebo-controlled trial testing effects of high-dose supplemental vitamin D3 (cholecalciferol; 2000 IU/day) and/or omega-3 fatty acids (FAs; 1 g/day) for the primary prevention of cancer and cardiovascular disease. The study has a mean treatment period of 5 years among 25,874 U.S. men ≥50 years and women ≥55 years old from all 50 states. The ancillary study, VITAL: Effects on Bone Structure and Architecture, is testing effects of vitamin D3 and/or omega-3 FAs on musculoskeletal outcomes and body composition in a subcohort of 771 participants. At in-person visits at the Harvard Catalyst Clinical and Translational Science Center (CTSC), participants completed bone density/architecture, body composition, and physical performance assessments at baseline and two-year follow-up. Baseline characteristics were evenly distributed among treatment groups, suggesting that any uninvestigated confounders will be evenly distributed; sex differences were also analyzed. Future analyses of the two-year follow-up visits will elucidate whether daily high-dose, supplemental vitamin D3 and/or omega-3 FAs improve musculoskeletal outcomes, helping to advance clinical and public health recommendations. Clinical trial registration number: NCT01747447 .
The Equal Rights Amendment: Back for an Encore Performance?

On March 27, 2007, a number of Members of Congressional, all Democrats, announced with great fanfare a renewed effort to pass the Equal Rights Amendment. This article points out the ways in which the text of the Equal Rights Amendment should be clarified. It also points out the similarities between the Equal Rights Amendment and California’s Proposition 209, which passed in 1996 over the objections of the California Democratic Party. Proposition 209 prohibits state-sponsored discrimination or preferential treatment on account sex. So, too, presumably, will the Equal Rights Amendment if it becomes part of the Constitution.
Gibt es Atome

Jeder gebildete Mensch halt es heute fur eine wohlbegrundete Tatsache, das die Materie aus kleinen Teilchen, den Atomen, besteht. Wenn er das nicht in der Schule gelernt hat, dann hat er es in der Zeitung gelesen. Da es Atombomben gibt, so schliest er, mus es auch Atome geben.
A Nonlinear Finite Element Model of Soft Tissue Indentation

Mathematically describing the mechanical behavior of soft tissues under large deformations is of paramount interest to the medical simulation community. Most of the data available in the literature apply small strains (<10%) to the the tissue of interest to assume a linearly elastic behavior. This paper applies a nonlinear hyperelastic 8-chain network constitutive law to model soft tissues undergoing large indentations. The model requires 2 material parameters (initial modulus, locking stretch) to reflect the underlying physics of deformation over a wide range of stretches. A finite element model of soft tissue indentation was developed and validated employing this constitutive law. Ranges of the initial shear modulus and locking stretches were explored based on values found for breast tissue [17, 25]. Results of the model are shown with a lookup table containing third order polynomial coefficient fits. This work serves as an initial method to determine the unique material parameters of breast tissue from indentation experiments.
A unified derivation of quasi-Newton methods for solving non-sparse and sparse nonlinear equations

An augmented quasi-Newton equation is solved by using theW-V generalized inverse to give a unified derivation of the known quasi-Newton methods for solving systems of nonlinear algebraic equations. This approach makes it possible to get new formulas for sparse and non-sparse systems, and also to determine what norms of the update matrices are minimized when several useful quasi-Newton update formulas are derived.
Analysis on the Use of Continuous Improvement, Technology and Flipped Classroom in the Teaching-Learning Process by means of Data Science

This mixed research uses the Juran’s methodology to achieve continuous improvement in the teaching-learning process on mathematics through technology. This study proposes the creation of a virtual environment by means of the FreeDFD simulator, flipped classroom and YouTube videos with the purpose of linking the theoretical topics in the Logical of Predicates Unit with the field of computer science. The variables related to the teaching-learning process are Efficiency (assimilation of knowledge) and Technical Quality (Bloom’s Taxonomy: Memory, Comprehension and Application). On the other hand, students’ perception is analyzed through the Quality of service (teaching-learning process, technological ability and mathematical ability) and Customer satisfaction (utility, benefits and need). By means of data mining (decision trees technique), this research identifies four predictive models on assimilation of knowledge considering Bloom’s Taxonomy. The results obtained from linear regression (machine learning with 50% training and 50% evaluation) indicate that the Juran’s methodology facilitates the construction of virtual educational spaces through the stages related to the identification of clients, establishment of customer needs, translation of needs into the language of the organization, development of the product or service, creation of a process and transfer of the process to the operation. In conclusion, universities should improve educational conditions considering aspects of the technology, flipped classroom and continuous improvement.
Enhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithms

Abstract The vision of smart cities has emerged from the integration of advances in information technologies to a city’s infrastructures and assets. The use of information will improve the daily operations, and lead to greener, safer, and more human friendly cities. The most preeminent city asset is the electrical power grid, upon which the modernization of human life is built. However, integration of power grid with information technologies, known as smart grid, comes at a cost of reduced privacy. Electricity consumer behavior expressed via daily consumption patterns may be visible to third parties, which can make critical inferences over the consumers’ personal life. In this paper, a new method is proposed that aims at enhancing consumer privacy in smart cities by proposing an intelligent aggregation of anticipated demand patterns of multiple consumers as a mean to hide individual features. To that end, the method utilizes consumers self-elasticities matrices and a genetic algorithm to create an aggregated pattern that masks individual consumption data. The proposed method is tested on real world electricity demand patterns, and morphing performance is recorded with respect to symmetric mean average percentage error (SMAPE) attaining morphing over 60% in all tested cases.
Downlink Resource Allocation in Cell-Free Massive MIMO Systems

Cell-free Massive Multiple-Input Multiple-Output (MIMO) is introduced as a promising network architecture for the upcoming fifth-generation (5G) wireless communication networks. It enhances user experience and improves the overall system performance by providing huge throughput and coverage probability to all users throughout a system. In this paper, a resource allocation problem is studied for downlink cell-free massive MIMO networks, where each access point (AP) serves a cluster of user equipment (UE). Transmit precoding and power allocation are linked to the underlying max-min scheduling to ensure uniform and excellent service throughout the coverage area. Due to the coupled interference among UEs, the resulting max-min resource allocation optimization problem becomes non-convex. We demonstrate the uplink-downlink duality and propose an iterative algorithm which solves the primal downlink problem efficiently. By utilizing the max-min beam former and taking the channel estimation error into account, we further derive the capacity lower bound of the underlying cell-free massive MIMO network. The performance of the introduced scheme is also investigated through simulations. Numerical results show the efficiency of the introduced algorithm.
Wave Propagation in Anisotropic Media Using Born Series Through 4th Order

The Born series is used to calculate a field propagating in a Gaussian medium which itself has a Gaussian-form correlation function. These specializations lead to integrals for the moments with integrands which are themselves mainly of Gaussian form. They can be integrated algebraically using multivariate Gaussian distribution formulas. Specifically for moments the, say, fourth order Born term involves a 12-fold integration of which eight can be done algebraically using the formulas. We are able, for a two-scale anisotropic medium, to sum the Born series for the average (the first moment) of the radiation field. The result reduce to familiar ones when we specialize to isotropic media. A novel characteristic is that for physically interesting parameter ranges diffraction effects can be substantially reduce the phase variance, thus reducing the randomizing effect of the medium on the propagated field. Anisotropy also leads to an intensity dependance on angle. The fourth-order moment (the intensity variance) is considered through fourth-order Born terms; it is not possible to sum the Born series for this moment in terms of simple functions even for isotropic media. Previous results are in large part confirmed: when diffraction effects are slight, sound field fluctuation effects are confined to the phase, leading at sufficient range to a log-normal field distribution. When diffraction effects become appreciable, the sound amplitude fluctuates and the distribution becomes Gaussian. There is also an expected region of appreciable overshoot in the intensity variance, that variance exceeding its Gaussian value for intermediate ranges at lower frequencies.
Brutality Following the Fall of Nanjing: Large-Scale Massacres

Japanese troops committed atrocities in and around Nanjing the moment they arrived. Five American and British correspondents, who remained inside the city walls to cover the siege battles and expected fall of the city, provided timely eyewitness accounts of Japanese atrocious behaviors in their news wires, thus breaking the news of the Nanjing Massacre to the outside world, placing the infamous carnage under the global spotlight, and shocking the world with its magnitude and brutality.
Infective Endocarditis as a Complication of Intravenous Drug Use in Pregnancy: A Retrospective Case Series and Literature Review.

Objective An increase in opioid use disorder and subsequent intravenous drug use has led to an increase in sequalae that may complicate pregnancy, such as infective endocarditis. Infective endocarditis has the potential for significant maternal and neonatal morbidity and mortality. We sought to examine the management considerations and clinical implications of intravenous drug use-related infective endocarditis in pregnancy from our center's experience. Study Design Retrospective study of management of pregnancies complicated by infective endocarditis as a result of active intravenous drug use at an academic tertiary care hospital from January 2012 through December 2019. Results Twelve women with active intravenous drug use histories were identified as having clinical and echocardiographic features consistent with infective endocarditis. Six women were discharged against medical advice and did not complete the full course of recommended antibiotic regimen. Eight women were started or continued on opioid agonist therapy during their hospitalization. Four neonates required neonatal intensive care unit admission for pharmacologic treatment for neonatal abstinence syndrome. Conclusion Management of intravenous drug use-associated infective endocarditis in pregnancy involves more than treating the acute condition. In pregnant women with opioid use disorder and infective endocarditis, addiction and chronic psychosocial conditions need to be addressed to optimize care.
Learnable Spectro-Temporal Receptive Fields for Robust Voice Type Discrimination.

Voice Type Discrimination (VTD) refers to discrimination between regions in a recording where speech was produced by speakers that are physically within proximity of the recording device ("Live Speech") from speech and other types of audio that were played back such as traffic noise and television broadcasts ("Distractor Audio"). In this work, we propose a deep-learning-based VTD system that features an initial layer of learnable spectro-temporal receptive fields (STRFs). Our approach is also shown to provide very strong performance on a similar spoofing detection task in the ASVspoof 2019 challenge. We evaluate our approach on a new standardized VTD database that was collected to support research in this area. In particular, we study the effect of using learnable STRFs compared to static STRFs or unconstrained kernels. We also show that our system consistently improves a competitive baseline system across a wide range of signal-to-noise ratios on spoofing detection in the presence of VTD distractor noise.
Sweet syndrome as an adverse reaction to tyrosine kinase inhibitors: A review.

Tyrosine kinase inhibitors are a class of targeted anticancer drugs that inhibit cancer cell proliferation by inactivating proteins involved in signal transduction cascades. Various cutaneous adverse events have been observed after tyrosine kinase inhibitor administration, including Sweet syndrome. We queried the PubMed database to identify fourteen cases of Sweet syndrome thought to be secondary to tyrosine kinase inhibitors. Tyrosine kinase inhibitor-induced Sweet syndrome had a median of 2 months latency following drug administration. All cases but one had morphologic features classic for Sweet syndrome (erythematous and tender papules, plaques, or nodules). All cases also had classic histopathologic findings (dermal neutrophilic infiltrate without vasculitis or necrosis). Using diagnostic criteria for drug-induced Sweet syndrome and the Naranjo Drug Reaction Probability Scale for a drug-induced cutaneous eruption, we found that six cases favored a drug-induced etiology over malignancy, two cases favored a malignancy-associated Sweet syndrome, and the remaining eight met drug-induced Sweet syndrome criteria but had low Naranjo scores. Nine cases resulted in medication discontinuation, while five cases continued anticancer therapy and were treated only with corticosteroids with quick resolution of skin lesions. Dermatologists should be aware of this adverse cutaneous reaction to tyrosine kinase inhibitors and should treat on a case-by-case basis, though limited evidence in this review suggests that oncologic therapy may safely be continued with prompt corticosteroid treatment. This article is protected by copyright. All rights reserved.
An Explorative Analysis of the Feasibility of Implementing Metacognitive Strategies in Self-Regulated Learning with the Conversational Agents:

With the prevalence of commercially available conversational agents (CAs), little research examined the capacities and constraints of these devices to support adults to learn new information on the...
Technical nuances of machine learning: implementation and validation of supervised methods for genomic prediction in plant breeding

Abstract The decision-making process in plant breeding is driven by data. The machine learning framework has powerful tools that can extract useful information from data. However, there is still a lack of understanding about the underlying algorithms of these methods, their strengths, and pitfalls. Machine learning has two main branches: supervised and unsupervised learning. In plant breeding, supervised learning is used for genomic prediction, where phenotypic traits are modeled as a function of molecular markers. The key supervised learning algorithms for genomic prediction are linear methods, kernel methods, neural networks, and tree ensembles. This manuscript provides an insight into the implementation of these algorithms and how cross-validations can be used to compare methods. Examples for genomic prediction come from plant breeding.
Mind the Semantic Gap: Policy Intent Inference from Network Metadata

Network Policy management is a tedious and laborious task because of scale and dynamic changes in the network. The advent of Softwarized Networks has led to a renewed interest in intent-based network policy management. Intent-based Networking provides a structured way of specifying the intent of policies which are automatically translated and compiled into network device configuration. While this top-down approach of policy intent to policy configuration has worked well for cloud-native infrastructures such as data centers, it has not seen much adoption in legacy networks. We believe one of the primary reasons for this is the semantic gap between policy intents and policy configurations. The problem is further exacerbated by the heterogeneity, scale-on-the-fly, fragmentation, and lack of structure in non-intent native networks. We introduce Policy Intent Inference (PII) System to bridge the semantic gap with its advanced inference layer that extracts the policy intents from policy configurations fragmented over disparate network devices. We adopt a bottom-up approach to extract all policies within network devices, abstract them into a structured data model, and with the use of clustering and information retrieval techniques, build an optimal solution to extract network-wide policy intents from the underlying network that eases policy management especially policy troubleshooting, reducing the configuration clutter and reducing the time taken to compile and resolve conflicts in policies.
Excellence in medical training: developing talent-not sorting it.

Many medical schools have reconsidered or eliminated clerkship grades and honor society memberships. National testing organizations announced plans to eliminate numerical scoring for the United States Medical Licensing Examination Step 1 in favor of pass/fail results. These changes have led some faculty to wonder: "How will we recognize and reward excellence?" Excellence in undergraduate medical education has long been defined by high grades, top test scores, honor society memberships, and publication records. However, this model of learner excellence is misaligned with how students learn or what society values. This accolade-driven view of excellence is perpetuated by assessments that are based on gestalt impressions influenced by similarity between evaluators and students, and assessments that are often restricted to a limited number of traditional skill domains. To achieve a new model of learner excellence that values the trainee's achievement, growth, and responsiveness to feedback across multiple domains, we must envision a new model of teacher excellence. Such teachers would have a growth mindset toward assessing competencies and learning new competencies. Actualizing true learner excellence will require teachers to change from evaluators who conduct assessments of learning to coaches who do assessment for learning. Schools will also need to establish policies and structures that foster a culture that supports this change. In this new paradigm, a teacher's core duty is to develop talent rather than sort it.
Integrating Pre-Exposure Prophylaxis Delivery in Public Health Family Planning Clinics: Lessons Learned From a Programmatic Implementation Project in Kenya

Sexually active African women are a priority population for HIV prevention due to disproportionately high frequency of new HIV infections. Family planning clinics (FP) offer an already trusted platform that can be used to reach women for HIV prevention services, including PrEP. In the recent PrEP Implementation in Young Women and Adolescent (PrIYA program), we piloted PrEP implementation in FP clinics in Kisumu, Kenya and demonstrated that it was possible to integrate PrEP provision in FP systems with a program-dedicated staff. In this perspective, we describe experiences and strategies employed to introduce PrEP implementation in FP clinics and lessons learned. We identified the following lessons for PrEP introduction in FP clinics in Kenya: (1) possible to integrate and generate high enthusiasm for PrEP delivery in FP clinics but persistence on PrEP is a challenge (2) Involvement of national and regional stakeholder is critical for buy-in, contextualization, and sustainability, 3) Delivery models that don’t fully integrate with existing staff and systems are less sustainable, 4) Creatinine testing at PrEP initiation may not be necessary, 5) Fully integrated HIV and FP data systems need to be developed, and 6) Incorporating implementation science evaluation is important to understand and document effective implementation strategies. In summary, integration of HIV prevention and FP services provides an opportunity to promote one-stop women-centered care efficiently. However, broader focus on delivery models that utilize existing staff and novel strategies to help women identify their own risk for HIV are needed to ensure greater success and sustainability.
Breaking Down Barriers to Technology Transfer: Reforming WTO Standard-Setting Rules and Establishing an Advisory Facility in Standard-Setting for Developing & Least Developed Countries

This chapter focuses on a subject that might be considered as somewhat specialized or even 'arcane' in the technology transfer debate, but one which I will argue is really quite central to facilitating technology transfer to developing and least developing countries: my topic is technology standard-setting. I have included two concrete proposals.Much has been written about intellectual property (’IP’) and its relevance to technology transfer. In the international context, there has been extended debate about the impact of intellectual property rights on economic development, trade, and technology transfer. However, the standard-setting process is also integrally related to technology transfer, and this carries important implications for developing and "least developed" countries. Currently, these countries are largely marginalized or excluded from important standard-setting processes. Without 'access' or the knowledge and understanding to productively participate in these standards processes, developing and least developed countries are caught in a difficult and negative cycle, in which their exclusion breeds lack of innovation and continuing technological backwardness.In this chapter I approach this problem on two levels. First, I propose changes within the WTO system, in particular, focusing on the rules associated with the WTO’s Agreement on Technical Barriers to Trade ('TBT Agreement'), to facilitate fairness in the international standard-setting where intellectual property rights are involved, and thereby benefiting developing and least developed countries. Second, I also propose a new mechanism to facilitate increased understanding of and participation in the standard-setting process by developing and least developed countries.
Self‐reported antidepressant use among depressed, low‐income homebound older adults: class, type, correlates, and perceived effectiveness

Little research has been done on the use of antidepressants among homebound older adults, especially low-income homebound older adults, and their perceptions of the effectiveness of their medication. The purposes of this study were to examine self-reported use of antidepressants among depressed homebound older adults, class and type of antidepressants used, individual-level correlates of antidepressant use, and users' perceptions of the effectiveness of antidepressants. Data on self-reported use of antidepressants were obtained as part of a feasibility study of short-term telehealth problem-solving therapy for depressed low-income homebound adults (n = 162) aged 50 or older. The 24-item Hamilton Rating Scale for Depression (HAMD) was used to assess depression severity. The findings show that about half of the study participants were taking antidepressants, with 26.6% of those on antidepressants rating their medications very effective and 21.5% rating them effective. Female gender was positively, but older age and being Black/African American were negatively associated with the likelihood of antidepressant use. Perceived effectiveness of antidepressants was negatively associated with older age and the HAMD score. The findings suggest that personalized approaches to depression management may be needed in subgroups of depressed older adults, including culturally tailored medication counseling in Black/African-American older adults.
Teaching Common Errors in Applying a Procedure

This study investigated whether or not the teaching of matched examples and nonexamples in the form of common errors would improve student performance in applying a procedure to previously unencountered instances, and whether the common errors would be most beneficial in generality form, in example form, or in both forms. Participants were 141 first-year music students, who were randomly assigned to four groups and given the task to learn a procedure that was presented in a self-contained booklet. A pretest-posttest experimental design was used, with a prerequisite test given as a screening device. The two independent variables were the absence and presence of the common errors in the generality form and in the example form (2 x 2 factorial design). Results indicated that the teaching of common errors in the generality form significantly improved learning a procedure at the application level of behavior.
β-d-Glucopyranosyl-O-l-tyrosine: Synthesis, properties and titre during insect development

β-d-Glucopyranosyl-O-l-tyrosine (tyrosine glucoside) was synthesized by acid-catalyzed fusion of β-glucopyranose pentaacetate with N-carbobenzoxy-l-tyrosine methyl ester and subsequent deblocking, transesterification and saponification. The [13C]-NMR spectrum was identical to the natural product isolated from the tobacco hornworm, Manduca sexta L. This conjugate was detected by HPLC in whole body extracts of the Indian meal moth, Plodia interpunctella (Hubner), almond moth, Ephestia cautella (Walker) and bagworm, Thyridopteryx ephemeraeformis (Haworth). Highest levels were found in mature larvae and pharate pupae. Tyrosine glucoside serves as a primary source of tyrosine and glucose for cuticle formation in Lepidoptera undergoing metamorphosis.
Control of divertor heat flux by radiative divertor operation in DIII-D

Summary form only given, as follows. The DIII-D tokamak divertor program is focused on obtaining the physics understanding of the divertor and scrape-off layer plasma required for leaning how to control divertor energy and particle flux in future large tokamaks such as ITER. We have made significant progress, reducing peak divertor heat flux by a factor of 5. This is done using deuterium or impurity gas puffing, which increases divertor density and radiative loss. Thomson scattering measurements in 2-D have shown that the electron temperature is reduced from more than 100 eV at the upstream separatrix to less the 1 eV near the divertor plate. We are now correlating this and simultaneous data from an extensive diagnostic set including fixed and fast-plunging Langmuir probes, VUV spectrometers, bolometers, visible-light TV cameras, and infrared cameras, with predictions from a 2D fluid code. In this low-temperature regime, atomic and molecular physics must now be added to improve our understanding. In addition, we are working toward independent control of core and divertor plasma.
Clinical Trials and the Food and Drug Administration

The Food and Drug Administration (FDA) protects the health of Americans by enforcing the Federal Food, Drug, and Cosmetic Act and other related public health laws. The role of the FDA in clinical trials is to help protect the rights and welfare of the patients participating in the trial. This article discusses the different steps a new drug goes through before it is marketed and the involvement of the FDA in each step. Keywords: food and drug administration (FDA); clinical trials; rules and legislation; phase I clinical trials; new drug development
Disparities in smoking behaviors among those with and without disabilities from 2001 to 2005.

Objectives: Past research has suggested smoking disparities among individuals with disabling conditions. We contrasted smoking behaviors of those with and without disabilities from 2001 to 2005. Design: Descriptive correlational study. Sample: Telephone interviews were conducted in all states with noninstitutionalized adults. Half were female; most were Anglo (70.5%) and had at least a high school education (90%). Their average age was 45 years. Approximately 19% of the sample reported being disabled. Measurement: We analyzed 4 years of data from the population-based Behavioral Risk Factor Surveillance System. Results: While individuals with disabilities were more likely to report ever having smoked than nondisabled respondents, current smoking behaviors were more similar in the 2 groups, and the difference was not statistically significant when demographic factors were included in the model. Smoking behavior decreased somewhat for nondisabled persons between 2001 and 2005, but remained fairly constant for those with disabilities. However, those with disabilities were more likely than those without disabilities to have attempted to quit smoking in all years. Conclusions: Findings underscore the importance of smoking cessation programs tailored to people with disabilities. The role of the public health nurse in addressing smoking cessation at the individual, system, and community level is discussed.
A unified theory for modeling water waves

Publisher Summary This chapter presents a unified theory for modeling water waves. The different types of waves in water, varying from ripples on a placid pond, breaking of shoaling waves on a beach, billows on a stormy sea and in the ocean interior, to geophysical waves and devastating tsunamis, are truly extensive. Euler's equations are adopted to describe three-dimensional, incompressible, inviscid long waves on a layer of water of variable depth, which may vary with the horizontal position vector. Four sets of theoretical models for describing fully nonlinear fully dispersive (FNFD) unsteady gravity-capillary waves on water of variable depth in terms of four sets of basic variables are obtained. It is found that for determining solutions to the model equations for initial-boundary value problems with external forcing by surface pressure and seabed motion, effective numerical schemes are useful. It is observed that for two-dimensional irrotational water waves in particular, an alternative closure relation is derived by applying Cauchy's contour integral formula. The modeling of FNFD waves in water of uniform depth is also elaborated.