bluuebunny/crossref_metadata_2025 huggingface dataset:
Control of electroluminescence in a molecular photodiode by gate voltage
Authors: Petrov E. , Leonov V. , Shevchenko Y. , Snitsarev V.
Published: July 2020

The role of the gate voltage in the regulation of electroluminescence (EL) of a molecular photodiode with asymmetric localization of electron density on the frontier highest occupied and lowest unoccupied molecular orbitals of the photochromic molecule is considered. It is shown that the gate voltage can have a significant effect on the formation of EL in devices where one of the orbital energy levels are outside the gap between the biased Fermi levels of the electrodes. The role of the gate voltage consists in shifting the position of the orbital energy levels until both frontier levels fall into the gap and thereby provide a resonant mechanism for the formation of EL. This leads to the inclusion of EL at a lower bias voltage than that which includes EL at zero gate voltage. In addition, the shift in energy levels caused by the gate voltage explains the mechanism for controlling the kinetics of bipolarity formation. The effect is carried out by turning on and off the resonant hopping’s of the electron between the conducting states of the electrodes and molecular orbitals localized at different distances from the electrode surfaces.
Dark–dark solitons for the coupled spatially modulated Gross–Pitaevskii system in the Bose–Einstein condensation
Authors: Zhao Xin , Tian Bo , Qu Qi-Xing , Yuan Yu-Qiang , Du Xia-Xia , Chu Mei-Xia
Published: July 2020

Investigation in this paper is the spatially modulated two-component GP system with Rabi coupling in a Bose–Einstein condensate consisting of the two hyperfine states. Based on the Kadomtsev–Petviashvili hierarchy reduction, we derive the Gramian expression of the one- and two-dark–dark soliton solutions. The nonlinearity coefficients [Formula: see text] and the external spatially varying trapping potential [Formula: see text] can be constrained as the functions of [Formula: see text], where [Formula: see text] is the spatial coordinate, [Formula: see text] is the time coordinate, [Formula: see text] is the dispersion parameter. With the Rabi coupling coefficient [Formula: see text] increasing, period along [Formula: see text] decreases. When [Formula: see text] is a constant, soliton propagates stably with the amplitude and velocity unvarying; When [Formula: see text] is a function of [Formula: see text], background is periodic and velocity of the soliton varies with [Formula: see text] increasing. Head-on and overtaking elastic interactions between the two solitons are presented analytically and graphically.
Quasirandom estimations of two-qubit operator-monotone-based separability probabilities
Authors: Slater Paul B.
Published: July 2020

We conduct a pair of quasirandom estimations of the separability probabilities with respect to 10 measures on the 15-dimensional convex set of two-qubit states, using its Euler-angle parametrization. The measures include the (nonmonotone) Hilbert–Schmidt one, plus nine others based on operator monotone functions. Our results are supportive of previous assertions that the Hilbert–Schmidt and Bures (minimal monotone) separability probabilities are [Formula: see text] and [Formula: see text], respectively, as well as suggestive of the Wigner–Yanase counterpart being [Formula: see text]. However, one result appears inconsistent (much too small) with an earlier claim of ours that the separability probability associated with the operator monotone (geometric-mean) function [Formula: see text] is [Formula: see text]. But a seeming explanation for this disparity is that the volume of states for the [Formula: see text]-based measure is infinite. So, the validity of the earlier conjecture — as well as an alternative one, [Formula: see text], we now introduce — cannot be examined through the numerical approach adopted, at least perhaps not without some truncation procedure for extreme values.
EVOLUTIONARY STAGES OF THE LIFE CYCLE OF INFORMATION AND COMMUNICATION TECHNOLOGY COMPANIES: EVIDENCE FROM BRAZIL
Authors: PEREIRA JOAO HENRIQUE DE SOUZA , FERREIRA LOPES JOSE EDUARDO , PORTO GECIANE SILVEIRA
Published: July 2020

This research aims to identify the factors that characterise the evolutionary stages of the development cycle of information and communication technology (ICT) companies, based on Brazilian evidence. A data collect was done and the analysis shows the factors related to the companies’ success. In addition, the results show factors related to the evolutionary stages of the ICT companies and demonstrate the differences in the characteristics of each stage of the company: nascent, in consolidation and mature. The results of this research provide information to entrepreneurs to improve the performance of their enterprises and, consequently, contribute to the development of the ICT sector in Brazil and other countries with similar characteristics. Furthermore, based on the results found in the different characteristics of companies at each evolutionary stage, this research provides information to policy-makers to develop really effective mechanisms to contribute to the technology sector and, subsequently, to a better economic and social development of their countries.
Dimensionally Aware Multi-Objective Genetic Programming for Automatic Crowd Behavior Modeling
Authors: Li D. , Zhong J.
Published: July 2020

One limitation of current data-driven automatic crowd modeling methods is that the models generated have low interpretability, which limits the practical applications of the models. In this article, we propose a new data-driven crowd modeling approach that can generate universal behavior rules with better interpretability. Higher interpretability helps people better understand and analyze the rules. Furthermore, the proposed approach considers both static and dynamic features during modeling to generate a realistic crowd, based on the assumption that humans tend to consider different features with respect to their states. In the proposed method, the automatic behavior rule generation problem is formulated as a symbolic regression problem. Then, the problem is solved by multi-objective genetic programming. On one hand, to improve the interpretability of the behavior rules found, a new mechanism is proposed to guide the algorithm to find concise and dimensionally consistent solutions. On the other hand, decisions made by considering static and dynamic features respectively are combined to improve the generated crowd realism. To validate the effectiveness of the proposed method, three real-world datasets are utilized for training and testing. The simulation results demonstrate that the proposed method is able to find universal behavior rules that are competitive to previous work in accuracy while having better interpretability.
Practical Privacy Preserving POI Recommendation
Authors: Chen Chaochao , Zhou Jun , Wu Bingzhe , Fang Wenjing , Wang Li , Qi Yuan , Zheng Xiaolin
Published: July 2020

Point-of-Interest (POI) recommendation has been extensively studied and successfully applied in industry recently. However, most existing approaches build centralized models on the basis of collecting users’ data. Both private data and models are held by the recommender, which causes serious privacy concerns. In this article, we propose a novel Privacy preserving POI Recommendation (PriRec) framework. First, to protect data privacy, users’ private data (features and actions) are kept on their own side, e.g., Cellphone or Pad. Meanwhile, the public data that need to be accessed by all the users are kept by the recommender to reduce the storage costs of users’ devices. Those public data include: (1) static data only related to the status of POI, such as POI categories, and (2) dynamic data dependent on user-POI actions such as visited counts. The dynamic data could be sensitive, and we develop local differential privacy techniques to release such data to the public with privacy guarantees. Second, PriRec follows the representations of Factorization Machine (FM) that consists of a linear model and the feature interaction model. To protect the model privacy, the linear models are saved on the users’ side, and we propose a secure decentralized gradient descent protocol for users to learn it collaboratively. The feature interaction model is kept by the recommender since there is no privacy risk, and we adopt a secure aggregation strategy in a federated learning paradigm to learn it. To this end, PriRec keeps users’ private raw data and models in users’ own hands, and protects user privacy to a large extent. We apply PriRec in real-world datasets, and comprehensive experiments demonstrate that, compared with FM, PriRec achieves comparable or even better recommendation accuracy.
Adaptive Asynchronous Parallelization of Graph Algorithms
Authors: Fan Wenfei , Lu Ping , Yu Wenyuan , Xu Jingbo , Yin Qiang , Luo Xiaojian , Zhou Jingren , Jin Ruochun
Published: July 2020

This article proposes an Adaptive Asynchronous Parallel (AAP) model for graph computations. As opposed to Bulk Synchronous Parallel (BSP) and Asynchronous Parallel (AP) models, AAP reduces both stragglers and stale computations by dynamically adjusting relative progress of workers. We show that BSP, AP, and Stale Synchronous Parallel model (SSP) are special cases of AAP. Better yet, AAP optimizes parallel processing by adaptively switching among these models at different stages of a single execution. Moreover, employing the programming model of GRAPE, AAP aims to parallelize existing sequential algorithms based on simultaneous fixpoint computation with partial and incremental evaluation. Under a monotone condition, AAP guarantees to converge at correct answers if the sequential algorithms are correct. Furthermore, we show that AAP can optimally simulate MapReduce, PRAM, BSP, AP, and SSP. Using real-life and synthetic graphs, we experimentally verify that AAP outperforms BSP, AP, and SSP for a variety of graph computations.
Moment-Guided Discriminative Manifold Correlation Learning on Ordinal Data
Authors: Tian Qing , Zhang Wenqiang , Cao Meng , Wang Liping , Chen Songcan , Yin Hujun
Published: July 2020

Canonical correlation analysis (CCA) is a typical and useful learning paradigm in big data analysis for capturing correlation across multiple views of the same objects. When dealing with data with additional ordinal information, traditional CCA suffers from poor performance due to ignoring the ordinal relationships within the data. Such data is becoming increasingly common, as either temporal or sequential information is often associated with the data collection process. To incorporate the ordinal information into the objective function of CCA, the so-called ordinal discriminative CCA has been presented in the literature. Although ordinal discriminative CCA can yield better ordinal regression results, its performance deteriorates when data is corrupted with noise and outliers, as it tends to smear the order information contained in class centers. To address this issue, in this article we construct a robust manifold-preserved ordinal discriminative correlation regression (rmODCR). The robustness is achieved by replacing the traditional (
l
2
-norm) class centers with

l
p

-norm centers, where
p
is efficiently estimated according to the moments of the data distributions, as well as by incorporating the manifold distribution information of the data in the objective optimization. In addition, we further extend the robust manifold-preserved ordinal discriminative correlation regression to deep convolutional architectures. Extensive experimental evaluations have demonstrated the superiority of the proposed methods.
Dancing with Trump in the Stock Market
Authors: Yuan Kun , Liu Guannan , Wu Junjie , Xiong Hui
Published: July 2020

It is always deemed crucial to identify the key factors that could have significant impact on the stock market trend. Recently, an interesting phenomenon has emerged that some of President Trump’s posts in Twitter can surge into a dominant role on the stock market for a certain time period, although studies along this line are still in their infancy. Therefore, in this article, we study whether and how this new-rising information can help boost the performance of stock market prediction. Specifically, we have found that the echoing reinforced effect of financial news with Trump’s market-related tweets can influence the market movement—that is, some of Trump’s tweets directly impact the stock market in a short time, and the impact can be further intensified when it echoes with other financial news reports. Along this line, we propose a deep information echoing model to predict the hourly stock market trend, such as the rise and fall of the Dow Jones Industrial Average. In particular, to model the discovered echoing reinforced impact, we design a novel information echoing module with a gating mechanism in a sequential deep learning framework to capture the fused knowledge from both Trump’s tweets and financial news. Extensive experiments have been conducted on the real-world U.S. stock market data to validate the effectiveness of our model and its interpretability in understanding the usability of Trump’s posts. Our proposed deep echoing model outperforms other baselines by achieving the best accuracy of 60.42% and obtains remarkable accumulated profits in a trading simulation, which confirms our assumption that Trump’s tweets contain indicative information for short-term market trends. Furthermore, we find that Trump’s tweets about trade and political events are more likely to be associated with short-term market movement, and it seems interesting that the impact would not degrade as time passes.
Performance evaluation of blockchains in the internet of things
Authors: Alam Tanweer
Published: July 2020

The idea of blockchains technology (BT) in the Internet of Things (IoT) is to allow the physical things to trust in the transactions held within the IoT network. The BT is a distributed, decentralized, publicly shared its digital ledger and secured technology to eternally record the transactions across the shared database. The BT in IoT can be called Trust Machine to eliminate the intermediates and enables the physical things to trust with each other. This research evaluates the performance of BT in IoT. The simulated results are tested and can be used in the sustainable development of the integration of BT and IoT.
СУЧАСНИЙ СТАН ТА ПЕРСПЕКТИВИ ПІДГОТОВКИ ЛІКАРІВ-ІНТЕРНІВ ЗА СПЕЦІАЛЬНІСТЮ «ПСИХІАТРІЯ»
Authors: Venger O. P. , Smashna O. Ye. , Sas L. M. , Mysula Yu. I. , Bilous V. S. , Lyuta O. O. , Gusyeva T. P.
Published: July 2020

Мета: систематизувати та удосконалити навчальні та практичні аспекти підготовки лікарів-інтернів за спеціальністю «Психіатрія».

Матеріали і методи. Використовуючи бібліосемантичний метод та метод системного аналізу, вивчено норма­тивно-правову базу з питань післядипломної підготовки спеціалістів лікарів-інтернів за спеціальністю «Психіатрія».

Результати. Висвітлено сучасні підходи до забезпечення підготовки лікарів-інтернів за спеціальністю «Психіат­рія». Працівники кафедри психіатрії, наркології та медичної психології Тернопільського національного медичного університету імені І. Я. Горбачевського МОЗ України активно удосконалюють підготовку майбутніх лікарів-психіатрів для втілення концепції «lifelong learning», тобто забезпечення безперервності освітнього процесу.

Традиційно основною метою підготовки є удосконалення професійних навичок з основних розділів психіатрії, вивчення клініки та діагностики психічних розладів, методів їх лікування, реабілітації та профілактики. Виконання курсів навчальної програми інтернами на базі стажування досягається шляхом їх практичної лікарської діяльності під керівництвом безпосереднього керівника інтернів у спеціалізованих відділеннях з впровадженням швейцарського досвіду психіатричної допомоги для пацієнтів з психічними розладами. Особливу увагу приділяють мотивації інтернів, оскільки вона корелює із самооцінкою та рівнем домагань особистості, визначає потенційні можливості особистості, активність або пасивність суб’єкта в професійній діяльності та професійний розвиток спеціаліста.

Лікарі-інтерни на кафедрі психіатрії долучаються до участі в об’єктивному структурованому клінічному іспиті, що позитивно впливає на рівень клінічної обізнаності інтернів.

Висновки. Такі напрямки удосконалення післядипломної освіти змінюють парадигму ставлення до психічно хворих, їх статус у суспільстві, пропагують толерантність та терпимість.
ШЛЯХИ ВИРІШЕННЯ ПРОБЛЕМ КАДРОВОЇ ПОЛІТИКИ В УНІВЕРСИТЕТСЬКІЙ КЛІНІЦІ НА ПРИНЦИПАХ ДЕРЖАВНО-ПРИВАТНОГО ПАРТНЕРСТВА
Authors: Chopchyk V. D.
Published: July 2020

Мета: обґрунтувати шляхи вирішення проблем кадрової політики в університетській клініці на принципах державно-приватного партнерства.

Матеріали і методи. Для досягнення поставленої мети у роботі застосовували загальнонаукові методи аналізу, синтезу, узагальнення, інтерпретації наукових даних, а також системний і структурно-функціональний підходи. Інформаційною базою дослідження стали наукові праці вітчизняних і зарубіжних спеціалістів із державно-приватного партнерства та менеджменту.

Результати. Кадри визначено як один з основних ресурсів реформування університетських клінік. Розкрито причини кадрового дисбалансу в галузі охорони здоров᾽я і негативні наслідки цього. Показано наявність проблеми низької ефективності використання кадрових ресурсів у системі охорони здоров᾽я і відсутність відповідних умов для здійснення професійної діяльності медичного персоналу. Доведено, що для вирішення проблем кадрової політики в охороні здоров᾽я України, у першу чергу, необхідні фінансові та матеріально-технічні ресурси, які на сьогодні можна отримати тільки за рахунок приватного інвестора. Таким чином, в існуючій економічній ситуації України для розвитку університетських клінік, як лікувальних баз університетів, необхідно переходити на державно-приватні підприємства. У статті представлено шляхи вирішення проблем кадрової політики в університетській клініці на принципах державно-приватного партнерства.

Висновки. З урахуванням досвіду країн Заходу та економічної ситуації в Україні обґрунтовано більш ефективні шляхи вирішення проблем кадрової політики в університетській клініці на принципах державно-приватного партнерства.
Bidirectional Spatial–Temporal Network for Traffic Prediction with Multisource Data
Authors: Sun Tuo , Yang Chenwei , Han Ke , Ma Wanjing , Zhang Fan
Published: July 2020

Urban traffic congestion has an obvious spatial and temporal relationship and is relevant to real traffic conditions. Traffic speed is a significant parameter for reflecting congestion of road networks, which is feasible to predict. Traditional traffic forecasting methods have poor accuracy for complex urban road networks, and do not take into account weather and other multisource data. This paper proposes a convolutional neural network (CNN)-based bidirectional spatial–temporal network (CNN-BDSTN) using traffic speed and weather data by crawling electric map information. In CNN-BDSTN, the spatial dependence of traffic network is captured by CNN to compose the time-series input dataset. Bidirectional long short-term memory (LSTM) is introduced to train the convolutional time-series dataset. Compared with linear regression, autoregressive integrated moving average, extreme gradient boosting, LSTM, and CNN-LSTM, CNN-BDSTN presents its ability of spatial and temporal extension and achieves more accurately predicted results. In this case study, traffic speed data of 155 roads and weather information in Urumqi, Xinjiang, People’s Republic of China, with 1-min interval for 5 months are tested by CNN-BDSTN. The experiment results show that the accuracy of CNN-BDSTN with input of weather information is better than the scenario of no weather information, and the average predicted error is less than 5%.
Quantification of Sources of Variability of Air Pollutant Exposure Concentrations among Selected Transportation Microenvironments
Authors: Christopher Frey H. , Gadre Disha , Singh Sanjam , Kumar Prashant
Published: July 2020

The National Research Council has identified the lack of sufficient microenvironmental air pollution exposure data as a significant barrier to quantification of human exposure to air pollution. Transportation microenvironments, including pedestrian, transit bus, car, and bicycle, can be associated with higher exposure concentrations than many other microenvironments. Data are lacking that provide a systematic basis for comparing exposure concentrations in these transportation modes that account for key sources of variability, such as time of day, season, and types of location along a route such as bus stops and intersections. The objectives of this work are: to quantify and compare particulate matter (PM2.5), CO, and O3 exposure concentrations in selected active and passive transportation microenvironments; and to quantify the effect of season, time of day, and location with respect to variability in transportation mode exposure concentrations. Measurements were made with an instrumented backpack and were repeated for multiple days in each season to account for the effect of inter-run variability. Results include mean trends, spatial variability, and contribution to variance. Pedestrian and cycle mode exposure concentrations were approximately similar to each other and were substantially higher than for bus and car cabins for both PM2.5 and O3. Based on over 30 days of field measurements conducted over three seasons and for two times of day on weekdays, transportation mode and season were the largest contributors to variability in exposure for PM2.5 and O3, whereas location type alone and in combination with transport mode helped explain variability in CO exposures.
Differences Between U.S. Workers With Asthma by Paid Sick Leave Status: An Analysis of the 2018 National Health Interview Survey
Authors: DeRigne LeaAnne , Stoddard-Dare Patricia , Collins Cyleste , Bai Rong
Published: July 2020

Having asthma is a chronic condition that requires both acute and preventive care as a vital component of asthma action plans. This study looks at how having access to paid sick leave days may be important to adherence to asthma action plans. Does having paid sick days facilitate preventive care, help people avoid acute asthma incidents, reduce the number of lost work days, reduce the cost of care, and lessen financial worry among asthma sufferers? This research builds on a growing body of literature that has established a relationship between paid sick leave days and preventive and acute health care use and outcomes and yet is the first of its kind to examine the relationship specifically between asthma and paid sick leave. This study used secondary data analysis to examine the relationship between six outcome variables categories and having paid sick leave in a nationally representative sample of N = 1,676 working U.S. adults in the National Health Interview Survey. Workers without paid sick leave benefits were significantly more likely to report they were worried about finances and struggle to afford their prescription medication compared to their counterparts who have paid sick leave benefits. Examined in light of past findings, workers with asthma who lack paid sick leave are in a precarious situation where they have increased worry likely due in part to reduced take-home pay due to unpaid sick days and increased medical expenses. There was no relationship between having paid sick leave and the receipt of preventive asthma care, measures of asthma control, receipt of patient education, and asthma medication use. Implications for policy and practice are put forth.
Massive Left Atrial Thrombus After a Left Atrial Surgical Ablation and Bioprosthetic Mitral Valve Replacement
Authors: Husaini Mustafa , Quader Nishath , Braverman Alan C. , Damiano Ralph J. , Maniar Hersh S.
Published: July 2020

Variability exists regarding the timing and duration of anticoagulation after surgical ablation for atrial fibrillation and bioprosthetic mitral valve replacement (MVR). We report a case in which a patient developed a massive left atrial (LA) thrombus after MVR and left-sided radiofrequency ablation (LRFA). Despite acutely elevated gradients across the bioprosthetic valve, the patient remained asymptomatic and hemodynamically stable; thus, a multidisciplinary, patient-centered discussion was had and the patient was treated successfully with oral anticoagulation.
University Startup Accelerators: Startup Launchpads or Vehicles for Entrepreneurial Learning?
Authors: Metcalf Lynn E. , Katona Thomas M. , York Jonathan L.
Published: July 2020

Over the past decade, universities have invested heavily in startup accelerator programs; however, their role in the university entrepreneurial ecosystem is ambiguous. Are university startup accelerators intended to educate or are they created to facilitate business starts and to contribute to regional economic development? In contrast, most private-sector startup accelerators serve a consistent and differentiated role in the entrepreneurial ecosystem—they provide programming and resources to startups to increase the probability of a return on investment. Understanding the role of university startup accelerators is an important precursor to evaluating their impact and whether or not the return is worth the considerable investment. In this study, we poll university accelerator directors to gain their perspective on the role(s) that university startup accelerators play and to identify how they are structured and operated. Our research reveals a fairly uniform structure and mode of operation. While facilitating business starts is a key role for some, it confirms education as the primary role for university startup accelerators. We outline appropriate means of assessing the learning that takes place in accelerator programs, offer insight into how these findings can help accelerator directors deliver on outcomes and demonstrate impact, and propose avenues for future research.
Leveraging Bayesian networks and information theory to learn risk factors for breast cancer metastasis
Authors: Jiang Xia , Wells Alan , Brufsky Adam , Shetty Darshan , Shajihan Kahmil , Neapolitan Richard E.
Published: July 2020

Background

Even though we have established a few risk factors for metastatic breast cancer (MBC) through epidemiologic studies, these risk factors have not proven to be effective in predicting an individual’s risk of developing metastasis. Therefore, identifying critical risk factors for MBC continues to be a major research imperative, and one which can lead to advances in breast cancer clinical care. The objective of this research is to leverage Bayesian Networks (BN) and information theory to identify key risk factors for breast cancer metastasis from data.

Methods

We develop the Markov Blanket and Interactive risk factor Learner (MBIL) algorithm, which learns single and interactive risk factors having a direct influence on a patient’s outcome. We evaluate the effectiveness of MBIL using simulated datasets, and compare MBIL with the BN learning algorithms Fast Greedy Search (FGS), PC algorithm (PC), and CPC algorithm (CPC). We apply MBIL to learn risk factors for 5 year breast cancer metastasis using a clinical dataset we curated. We evaluate the learned risk factors by consulting with breast cancer experts and literature. We further evaluate the effectiveness of MBIL at learning risk factors for breast cancer metastasis by comparing it to the BN learning algorithms Necessary Path Condition (NPC) and Greedy Equivalent Search (GES).

Results

The averages of the Jaccard index for the simulated datasets containing 2000 records were 0.705, 0.272, 0.228, and 0.147 for MBIL, FGS, PC, and CPC respectively. MBIL, NPC, and GES all learned that grade and lymph_nodes_positive are direct risk factors for 5 year metastasis. Only MBIL and NPC found that surgical_margins is a direct risk factor. Only NPC found that invasive is a direct risk factor. MBIL learned that HER2 and ER interact to directly affect 5 year metastasis. Neither GES nor NPC learned that HER2 and ER are direct risk factors.

Discussion

The results involving simulated datasets indicated that MBIL can learn direct risk factors substantially better than standard Bayesian network learning algorithms. An application of MBIL to a real breast cancer dataset identified both single and interactive risk factors that directly influence breast cancer metastasis, which can be investigated further.
Genome-wide identification and transcript profiles of walnut heat stress transcription factor involved in abiotic stress
Authors: Liu Xuejiao , Meng Panpan , Yang Guiyan , Zhang Mengyan , Peng Shaobing , Zhai Mei Zhi
Published: July 2020

Background

Walnut (Juglans regia) is an important tree cultivated worldwide and is exposed to a series of both abiotic and biotic stress during their life-cycles. The heat stress transcription factors (HSFs) play a crucial role in plant response to various stresses by regulating the expression of stress-responsive genes. HSF genes are classified into 3 classes: HSFA, HSFB, and HSFC. HSFA gene has transcriptional activation function and is the main regulator of high temperature-induced gene expression. HSFB gene negatively regulates plant resistance to drought and NaCl. And HSFC gene may be involved in plant response to various stresses. There are some reports about the HSF family in herbaceous plants, however, there are no reports about the HSFs in walnut.

Result

In this study, based on the complete genome sequencing of walnut, the bioinformatics method was used and 29 HSF genes were identified. These HSFs covered 18 HSFA, 9 HSFB, and 2 HSFC genes. Phylogenetic analysis of these HSF proteins along with those from Arabidopsis thaliana showed that the HSFs in the two species are closely related to each other and have different evolutionary processes. The distribution of conserved motifs and the sequence analysis of HSF genes family indicated that the members of the walnut HSFs are highly conserved. Quantitative Real-Time PCR (qRT-PCR) analysis revealed that the most of walnut HSFs were expressed in the walnut varieties of ‘Qingxiang’ and ‘Xiangling’ under high temperature (HT), high salt and drought stress, and some JrHSFs expression pattern are different between the two varieties.

Conclusion

The complex HSF genes family from walnut was confirmed by genome-wide identification, evolutionary exploration, sequence characterization and expression analysis. This research provides useful information for future studies on the function of the HSF genes and molecular mechanism in plant stress response.
Increased expression of hypoxia inducible factor-1 alpha and vascular endothelial growth factor is associated with diabetic gastroparesis
Authors: Wu Xueping , Yang Zhifang , Li Zhihong , Yang Ling , Wang Xinyan , Wang Congrong , Gu Jun
Published: July 2020

Background

Gastroparesis is a recognized complication of diabetes but its pathogenic mechanism incompletely understood. Our aim was to determine whether HIF-1α and VEGF are secreted from gastric tissue is a fundamental factor that drives diabetic gastroparesis.

Methods

Diabetes was induced in Sprague-Dawley by a single intraperitoneal injection of 65 mg/kg streptozotocin. After 4 and 12 weeks, rats were euthanized for assaying body weight, blood glucose, gastric acid secretion and gastric emptying. Morphologic changes in gastric mucosa were observed by the light microscope. Expression of HIF-1α and VEGF were assessed using immunohistochemistry, RT-PCR and Western blot analyses.

Results

Compared with control group, blood glucose were significantly increased and body weight were markedly decreased in streptozotocin-induced diabetes. Gastric emptying was significantly decreased in diabetic rats compared to the control group at different times. The number of parietal cells was obviously decreased, and vacuolated degeneration in diabetic rats. Gastric acid secretion in diabetic group was significantly decreased, and expression of HIF-1α and VEGF were significantly increased in the diabetic group.

Conclusion

These results indicated that overexpression of HIF-1α and VEGF in the gastric mucosa and played a pivotal role in the progression of diabetic gastroparesis.
Multifocal tuberculosis simulating a cancer-a case report
Authors: Wang Congxiao , Luan Ying , Liu Shifeng , Zhao Mingwei , Zhang Hao , Li Wei , Li Zixiang , Hu Xiaokun , Peng Lijing
Published: July 2020

Background

Tuberculosis is a disease that may affect any organ of the body. Multifocal tuberculosis involving multiple systems with associated symptoms are rare, which makes the diagnosis challenging. Distinguishing multifocal tuberculosis from lesions metastatic from system malignancy is difficult. Single detection method is difficult to make a diagnosis. A combination of multiple methods is essential.

Case presentation

A 17-year-old male presented with a 20 days weakness of lower limbs, which aggravated for 6 days. The PET/CT showed increased metabolism of ileocecal intestinal and terminal ileum wall, multiple enlarged lymph node (LNs), multiple osteolytic bone lesions, and soft tissue intensity belong T7 and T8 vertebrae. To confirm the diagnosis of the disease, a biopsy of the mediastinum lymph nodes was carried out. Polymerase chain reaction (PCR) test of the specimen was positive for the Mycobacterium tuberculosis, the T-SPOT and Xpert MTB/RIF test were also positive, which suggested the presence of Mycobacterium tuberculosis. The final diagnosis was multifocal tuberculosis, the patients received the resection of the mass in the spine. Anti-tuberculosis drugs were given. The myodynamia and muscle tension of the patients recovered following the therapy.

Conclusions

Our results indicated that Multifocal tuberculosis should also be taken into consideration when lesions metastatic from system malignancy were suspected from images results even without the clinical symptoms of tuberculosis, and combination of multiple diagnosis methods were essential for the diagnosis of multifocal disease.
Three-year outcome of aflibercept treatment for Japanese patients with neovascular age-related macular degeneration
Authors: Itagaki Kanako , Sekiryu Tetsuju , Kasai Akihito , Sugano Yukinori , Ogasawara Masashi , Saito Masaaki
Published: July 2020

Background

To evaluate the three-year outcome after intravitreal aflibercept injection (IAI) for neovascular age-related macular degeneration (nAMD).

Methods

Forty-nine treatment-naïve nAMD patients (50 eyes) were enrolled in this prospective study. The eyes received IAI at two-month intervals in the first year. The treatment regimen was changed to IAI based on a treat-and-extend approach in the second and third years.

Results

Twenty-nine eyes of 28 patients were successfully followed up over 36 months. The nAMD subtypes included 15 eyes with typical AMD and 14 eyes with polypoidal choroidal vasculopathy. The number of IAIs performed over the 3 years was 17.2 ± 3.1 (mean ± standard deviation). The mean logMAR, which was 0.42 at baseline, improved to 0.19 (P = 0.001) at 12 months, and 0.26 (P = 0.049) at 36 months. The central retinal thickness (CRT) was 329 ± 120 μm at baseline, 151 ± 38 μm (P < 0.001) at 12 months, and 143 ± 61 μm (P < 0.001) at 36 months. The mean subfoveal choroidal thickness (SFCT) was 288 ± 97 μm at baseline, 243 ± 82 μm (P < 0.001) at 12 months, and 208 ± 63 μm (P < 0.01) at 36 months. The changes in logMAR, CRT, and SFCT over the study period did not differ between typical AMD and PCV.

Conclusion

Long-term aflibercept injection can achieve visual improvement and reduce the thickness of the retina and choroid in nAMD. Morphological improvement of these tissues may not be sufficient to sustain earlier visual improvement over the long-term.
Veganism and paediatric food allergy: two increasingly prevalent dietary issues that are challenging when co-occurring
Authors: Protudjer Jennifer L. P. , Mikkelsen Andrea
Published: July 2020

Vegan diets – defined as the exclusion of all foods of animal origin from the diet- are becoming popular. In recent years, the prevalence of food allergy has also increased, and disproportionately affects children. When vegan diets and food allergy co-occur, this combination can be challenging and pose risks of nutritional deficiencies, particularly during childhood. In this paper, we aim to summarise the major concerns regarding vegan diets and food allergy, review the literature on this topic, and provide some suggestions for healthcare providers, particularly dietitians and nutritionists, who work with food allergic, vegan patients and their family. When working with this patient population, a regular and complete medical nutrition history, including screening for any possible nutritional deficiencies, is warranted. Likewise, the routine tracking of serum markers (especially iodine, iron, zinc, calcium, Vitamins B12, D, B2, and A, selected n-3 fatty acids and protein, which are more abundant in animal vs. plant foods) and symptoms of co-morbid diseases, including asthma, is important, as comorbid diseases may increase energy and nutrient requirements. For infants and children, anthropometry ought to be tracked longitudinally at regular intervals to identify any deviations from the child’s previous growth pattern, and to accommodate any increased requirements for growth and development. Correct diagnoses, education and allergy management must be disseminated to the family in a clear and appropriate manner. Children with allergy may have increased nutritional needs due to comorbidity. This is complicated by coincident food allergy and vegan diet as both impose diet restrictions (limiting sources of important nutrients, need for dietary variety and/or increased consumption due to reduced bioavaliability).
LncRNA PLAC2 upregulates miR-663 to downregulate TGF-β1 and suppress bladder cancer cell migration and invasion
Authors: Zhang Zhenxing , Ao Ping , Han Hui , Zhang Qi , Chen Yang , Han Jie , Huang Qunlian , Huang Houbao , Zhuo Dong
Published: July 2020

Background

The roles of lncRNA PLAC2 in bladder cancer (BC) were explored.

Methods

The expression of PLAC2 in two types of tissue of BC patients was detected by RT-qPCR and the expression data were compared by paired t test. The 56 patients were staged according to the AJCC criteria, and 12, 15, 15 and 14 cases were classified into stage I-IV, respectively. The expression of TGF-β1 and miR-663 in BC tissues were also detected by RT-qPCR experiments.

Results

Our data showed that the expression levels of PLAC2 were significantly lower in BC tissues than that in non-cancer tissues. The expression of PLAC2 was not affect by clinical stages and low expression levels of PLAC2 predicted lower survival rate. The expression of PLAC2 was positively correlated with miR-663 and inversely correlated with TGF-β1 in BC tissues. In BC cells, downregulated TGF-β1 and upregulated miR-663 were observed after the overexpression of PLAC2. Overexpression of PLAC2 also resulted in suppressed invasion and migration of BC cells. Overexpression of miR-663 resulted in downregulated TGF-β1 but did not affect the expression of PLAC2. Overexpression of TGF-β1 reduced the inhibitory effects of overexpression of PLAC2 and miR-663 on cell migration and invasion.

Conclusion

PLAC2 can upregulate miR-663 to downregulate TGF-β1 and suppress BC cell migration and invasion.
Computer-aided design of polyetheretherketone for application to removable pediatric space maintainers
Authors: Guo Hui , Wang Yong , Zhao Yijiao , Liu He
Published: July 2020

Background

The premature loss of primary teeth is a common problem in pediatric dentistry, resulting in disruption of the arch integrity. Hence, space maintainers (SM) used for maintaining spaces are necessary. However, current methods of making removable space maintainers (RSM) have some limitations.

Methods

Digital models of dentition defects were obtained by using a scanning technique coupled with laser medical image reconstruction. The digital RSMs were designed using the 3Shape software. They were manufactured using two methods: polyetheretherketone (PEEK), and conventional methods (20 RSMs per group). For qualitative evaluation, the Likert five-point scale was used by 10 experts to obtain a score for 40 RSMs. The spaces between the tissue surfaces of the RSMs and the models were replaced using silicone, and the maximum and mean distances, as well as the standard deviation, were measured. A three-dimensional variation analysis was used to measure these spaces. The student’s t-test and Satterthwaite t-test were used to compare the differences in the spaces for the various materials.

Results

The PEEK RSMs were found to fit the models well. In the qualitative assessment, the mean experts’ scores for the PEEK and conventional groups were 1.80 ± 0.40 and 1.82 ± 0.40, and there was no significant difference between the two groups (p = 0.875). In the quantitative assessment, the mean spaces for the PEEK digital RSMs and the conventional RSMs were 44.32 ± 1.75 μm, and 137.36 ± 18.63 μm, respectively, and the differences were statistically significant (p < 0.001). In addition, there were significant differences in the maximum space and the standard deviation between the two groups.

Conclusion

Digitally designed and integrated RSMs were found to be superior to those produced using the conventional method. 3D variation analysis results showed that the mean distances and standard deviations of the PEEK groups were significantly smaller than those of conventional group (p < 0.01). A PEEK-manufactured RSM produced using CAD/CAM would be extremely suitable for clinical applications.
Using flexible regression models for calculating hospital’s production functions
Authors: Reyes-Santías Francisco , Cordova-Arevalo Octavio , Rivo-Lopez Elena
Published: July 2020

Background

The relative lack of flexibility of parametric models has led to the development of nonparametric regression techniques based on the family of generalized additive models. However, despite the potential advantages of using Generalized Additive Model (GAM) in practice many models have, until now, not been sufficiently explored in health economics problems.

It could be interesting to calculate a new flexible hospital production function by means of a GAM including interactions and to compare it with the classic model Cobb-Douglas in the prediction of the behavior of productive factors.

Method

The flexible model considered has been the AM including the beds-facultative interaction. The covariates “Hospital”, being a categorical variable and “Year” being a continuous variable, have also been included in the model. Based on the estimation of the model penalized thin plate splines will be used to represent smoothed functions. In this configuration, the smoothed parameters will be estimated via REML.

Results

Cobb-douglas model fits well for the production functions of the more general clinical and surgical services, while the GAM adjusts better in the case of more specialized medical services.

Conclusions

Generalized Additive Models are more flexible than parametric models, providing a better fit in the presence of non-linear relationships and thus allowing more accurate prediction values. The results of this study suggest that AM is a promising technique for the areas of research and application in health economics.
A prospective evaluation of inter-rater agreement of routine medical records audits at a large general hospital in São Paulo, Brazil
Authors: Mafra Ana Carolina Cintra Nunes , Miraglia João Luiz , Colugnati Fernando Antonio Basile , Padilha Gilberto Soares Lourenço , Tadeucci Renata Rafaella Santos , Almeida Ederson , Bracco Mario Maia
Published: July 2020

Background

The quality of patient medical records is intrinsically related to patient safety, clinical decision-making, communication between health providers, and continuity of care. Additionally, its data are widely used in observational studies. However, the reliability of the information extracted from the records is a matter of concern in audit processes to ensure inter-rater agreement (IRA). Thus, the objective of this study is to evaluate the IRA among members of the Patient Health Record Review Board (PHRRB) in routine auditing of medical records, and the impact of periodic discussions of results with raters.

Methods

A prospective longitudinal study was conducted between July of 2015 and April of 2016 at Hospital Municipal Dr. Moysés Deutsch, a large public hospital in São Paulo. The PHRRB was composed of 12 physicians, 9 nurses, and 3 physiotherapists who audited medical records monthly, with the number of raters changing throughout the study. PHRRB meetings were held to reach a consensus on rating criteria that the members use in the auditing process. A review chart was created for raters to verify the registry of the patient’s secondary diagnosis, chief complaint, history of presenting complaint, past medical history, medication history, physical exam, and diagnostic testing. The IRA was obtained every three months. The Gwet’s AC1 coefficient and Proportion of Agreement (PA) were calculated to evaluate the IRA for each item over time.

Results

The study included 1884 items from 239 records with an overall full agreement among raters of 71.2%. A significant IRA increase of 16.5% (OR = 1.17; 95% CI = 1.03—1.32; p = 0.014) was found in the routine PHRRB auditing, with no significant differences between the PA and the Gwet’s AC1, which showed a similar evolution over time. The PA decreased by 27.1% when at least one of the raters was absent from the review meeting (OR = 0.73; 95% CI = 0.53—1.00; p = 0.048).

Conclusions

Medical record quality has been associated with the quality of care and could be optimized and improved by targeted interventions. The PA and the Gwet’s AC1 are suitable agreement coefficients that are feasible to be incorporated in the routine PHRRB evaluation process.
Experiences with health care and health-related quality of life of patients with hematologic malignancies in Mexico
Authors: Doubova Svetlana V. , Terreros-Muñoz Eduardo , Delgado-Lòpez Nancy , Montaño-Figueroa Efreen Horacio , Infante-Castañeda Claudia , Pérez-Cuevas Ricardo
Published: July 2020

Background

In Mexico, patients with hematologic malignancies (HMs) are characterized by being at high risk and advanced stages at diagnosis and by having a low cure rate; yet information on their experiences with health care and health-related quality of life (HRQL) is scarce. We aimed to evaluate experiences with health care and HRQL of patients with HMs and the association between these patient-reported measures.

Methods

We conducted a cross-sectional survey in two public oncology hospitals in Mexico City. The study included outpatient cancer patients aged ≥18 years with a diagnosis of leukemia, lymphoma, or multiple myeloma. We used a patient-centered quality of cancer care questionnaire to assess patient experiences with receiving 1) timely care; 2) clear information; 3) information for treatment decision-making; 4) care to address biopsychosocial needs; and 5) respectful and coordinated care. We applied the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) to measure HRQL. We performed a multiple linear regression to evaluate the association between patient-reported experiences (independent variables) and the QLQ-C30 summary score (dependent variable).

Results

Of the 515 participating HM patients, 46.6% had lymphoma, 34% leukemia, and 19.4% multiple myeloma; 70.9% were at advanced stages or at high risk. Additionally, 15.1% had anxiety and 12.8% had depression. Over one third (35.9%) reported receiving clear information, 28.5% timely care, 20.6% information for treatment decision-making, 23.7% care that addressed their biopsychosocial needs, and 31% respectful and coordinated care. The mean QLQ-C30 summary score was 71.9 points. Timely care, clear information, and care that addresses biopsychosocial needs were associated with higher HRQL.

Conclusions

Health care services for HM patients at public oncology hospitals in Mexico need improvement. Notably, providing timely care, clear information, and care that addresses patients’ biopsychosocial needs can increase the likelihood of better HRQL. Health care providers should measure and improve the experiences of HM patients with health care.