bluuebunny/crossref_metadata_2025 huggingface dataset:
Poststroke depression and risk of stroke recurrence and mortality: protocol of a meta-analysis and systematic review
Authors: Cai Wa , Stewart Robert , Mueller Christoph , Li Yi-Jing , Shen Wei-Dong
Published: December 2018

Introduction

A number of observational studies have indicated that poststroke depression could increase the risk of stroke outcomes. There is a meta-analysis indicating that poststroke depression is a risk factor of all-cause mortality. This paper reports the protocol for a systematic review and meta-analysis to clarify the associations of poststroke depression with stroke recurrence and mortality in order to determine whether poststroke depression is a predictor of stroke outcomes according to data extracted from relevant observational studies.

Methods and analysis

MEDLINE, Web of Science databases, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews will be used to conduct the search. Published studies written in English will be included. The risk of bias for the studies included in the systematic review or meta-analysis will be assessed by the Newcastle–Ottawa Quality Assessment Scale. HRs for stroke recurrence and mortality with 95% CIs will be included as primary outcomes. Subgroup analyses and meta-regression will be performed.

Ethics and dissemination

Ethics approval will not be needed because the data used in this systematic review will be extracted from published studies. The results of the systematic review focusing on whether depression after stroke is a predictor for stroke recurrence and mortality will be disseminated by publication in a peer-reviewed journal.

PROSPERO registration number

CRD42018107944.
Improving analgesia prescription for trauma inpatients
Authors: Stanger Sophie , Dahill Mark , Hillary Charlotte , Whitham Robert , Tasker Andrew
Published: December 2018

Patients value effective pain relief. Complications of inadequate pain control include increased risk of infection, decreased patient comfort and progression to chronic pain, all of which have significant socioeconomic consequence. Accessibility to analgesia is vital to effective administration. This improvement project aimed to improve the consistency and adequacy of analgesia prescribing for trauma inpatients over a 12-month period. Four PDSA (‘plan, do, study, act’) cycles resulted in sustained and significant improvements in analgesia prescription. The interventions included senior encouragement, teaching sessions, targeted inductions and implementation of a novel e-prescribing protocol. Prospective data and real-time discussion from stakeholder medical and management teams enabled iterative change to practice. Drug charts were reviewed for all trauma inpatients (n=276) over a 10-month period, recording all analgesia prescribed within 24 hours of admission. Each prescription was scored (maximum of 10 points) according to parameters agreed by the acute pain specialty leaders. An improving trend was observed in the analgesia score over the study period. Each intervention was associated with improved practice. Based on observed improvements, a novel electronic prescribing protocol was developed in conjunction with the information technology department, resulting in maximum scores for prescribing which were sustained over the final 3 months of the study. This was subsequently adopted as standard practice within the department. One year following completion of the project, a further 3 weeks of data were collected to assess long-term sustainability—scores remained 10 out of 10. Addressing the prescribing habits of junior doctors improved accessibility to analgesia for trauma patients. The electronic prescribing tool made prescribing straightforward and faster, and was the most successful intervention. Doctor satisfaction using this time-saving tool was high. Identifying a stakeholder within the information technology department proved pivotal to transferring the project aims into clinical practice.
Digital technology for health promotion: opportunities to address excess mortality in persons living with severe mental disorders
Authors: Naslund John A , Aschbrenner Kelly A
Published: December 2018

Persons with severe mental disorders (SMDs) experience dramatically reduced life expectancy compared with the general population. We consider the role of digital technologies for addressing this serious public health concern. In this clinical review, we apply themultilevel risk modelrecently introduced by the WHO to conceptualise how digital technology can support efforts to reduce excess mortality risk at the individual, health system and social determinants of health levels. In particular, digital technologies show promise for targeting preventable physical health conditions in persons with SMDs. However, evidence on the use of these technologies for addressing early mortality risk factors is lacking. At the individual level, digital interventions show promise for managing mental health symptoms, promoting healthy lifestyle behaviours and targeting substance use concerns. At the health system level, digital interventions can support care coordination, clinician training, screening and monitoring health indices and shared decision-making. At the social determinants of health level, digital interventions can facilitate opportunities to engage peers for illness self-management and health promotion and for delivering and/or augmenting supported employment programmes. The time is ripe to capitalise on early evidence to support future development, testing and delivery of effective digital efforts targeting risk factors that contribute to shorter life expectancy in persons with SMDs. Key challenges and opportunities for future research include increasing user engagement, involving users during development and testing of digital interventions, carefully considering risks/harms and rigorously evaluating effectiveness and costs to support the scalability and sustainability of promising digital approaches.
Home parenteral nutrition in patients receiving palliative care: a curriculum-based review
Authors: Fletcher Jane , Woodham Diane , Dera Merceline , Cooper Sheldon C
Published: December 2018

Difficulty with maintaining nutritional intake is common in patients with cancer. European guidance suggests that wherever possible nutritional support should first be provided by the oral or enteral route. Where this is not possible, for example, in malignant small bowel obstruction, parenteral nutrition (PN) may be considered. In palliative care, it is generally accepted that the significant risks and burdens of PN outweigh the potential benefits in patients with an expected survival <2 months. Determining prognosis is crucial when helping patients to make decisions regarding appropriate care pathways; however, this remains challenging. An overview of clinical issues and prognostic indicators related to selecting patients appropriately for palliative PN is given to cover the relevant advanced competencies of the 2010 Gastroenterology Curriculum. The organisation of Home Parenteral Nutrition (HPN) services in England is described including the associated risks and burdens of HPN in the palliative patient.
Cardiac remodelling and haemodynamic characteristics in primary mitral valve regurgitation
Authors: Bakkestrøm Rine , Banke Ann , Pecini Redi , Irmukhamedov Akhmadjon , Nielsen Søren Kristian , Andersen Mads J , Borlaug Barry A , Moller Jacob Eifer
Published: December 2018

Objective

To assess the association between cardiac morphology and function assessed with cardiac MRI (CMRI) and haemodynamics at rest and during exercise in patients with primary mitral regurgitation (MR).

Methods

In an observational study, subjects with significant primary MR (N = 46) with effective regurgitant orifice ≥ 0.30 cm2and left ventricular (LV) ejection fraction > 60% were examined with right heart catheterisation during rest and exercise and CMRI at rest. End-diastolic pressure volume relationship (EDPVR) was assessed using a single beat method using pulmonary capillary wedge pressure (PCWP) and end-diastolic volume. Patients were divided according to normal PCWP at rest (> 12 mm Hg) and with exercise (> 28 mm Hg). Results: Resting regurgitant volume correlated positively with resting PCWP, (r = 0.42, p = 0.002). However, with exercise no association between PCWP and regurgitant volume was seen (r = 0.09, p = 0.55). At rest left atrial (LA) maximal, minimal and volume index at atrial contraction correlated positively with PCWP (r = 0.60; r = 0.55; r = 0.58, all p < 0.001); in contrast none of these correlated with exercise PCWP (all p > 0.2). EDPVR in patients with high PCWP at rest was shifted towards higher volumes for the same pressures. The opposite was seen for patients with high PCWP during exercise where estimated volumes were smaller for the same pressure than patients with normal exercise PCWP.

Conclusion

In patients with significant MR the degree of regurgitation and LA dilatation is associated with resting PCWP. However, with exercise this association disappears. Estimation of EDPVR suggests lower LV compliance in patients where PCWP is increased with exercise.

Clinical trial registration

URL:https://clinicaltrials.gov/ct2/show/NCT02961647?term=HEMI&rank=1. ID:NCT02961647
Strong, near-infrared absorbing porphyrins: a DFT study
Authors: Agnihotri Neha
Published: December 2018

A systematic density functional theory study of electronic properties and optical spectra of four potential fused porphyrins with extended π-conjugation has been reported employing the M06 functional along with 6-31G(d)+LanL2DZ basis set. Symmetrical tetra fusion of the benzene rings at the β-meso-β position of porphyrins, resulted in four quadruply fused porphyrins. Such studies revealed the fact that the ring fusion with extended π-electrons causes remarkable red-shifts with narrowed band gaps. Thus, such systems can be used to extend the absorption deeper in to near-infrared (NIR) to even better utilize the photon rich region of solar spectrum. These fused porphyrins have emerged as promising NIR absorbing materials, having utility in molecular solar-conversion systems.
Effect of temperature on chlorine treatment for elimination of freshwater phytoplankton in ballast water: bench-scale test
Authors: Casas-Monroy Oscar , Vanden Byllaardt Julie , Bradie Johanna , Sneekes Andrea , Kaag Klaas , Bailey Sarah A.
Published: December 2018

Chlorine efficacy as a biocide for ballast water treatment was investigated under cold- and warm-water temperatures across winter and summer seasons. Freshwater phytoplankton samples were collected and acclimated under in situ environmental conditions ranging from 2 to 22 °C. Samples were exposed to seven chlorine treatments (from 0.02 to 5.0 ppm), in addition to a control (0.0 ppm). Free-chlorine concentrations, phytoplankton abundance, and photosynthetic efficiency were measured up to 48 h following treatment. After 4 h of treatment at concentrations less than 0.22 ppm, phytoplankton densities were reduced by more than 50%, without cell resurgence. Similar reduction was recorded immediately after exposure when chlorine concentrations were higher than 3.0 ppm. After 8 h, free chlorine neared 0.0 ppm for initial chlorine concentrations below 1.2 ppm, irrespective of temperature regime. Winter phytoplankton exhibited slightly lower mortality to chlorine exposure regardless of the temperature, although they also exhibited lower photosynthetic efficiency. Despite a general absence of significant effect of temperature on the chlorine decay, our results suggest that higher doses of chlorine or longer exposure times may be required during winter to achieve full treatment effect. Tests at large scales are needed to further confirm these findings.
STiMR k-Means: An Efficient Clustering Method for Big Data
Authors: Ben HajKacem Mohamed Aymen , Ben N′Cir Chiheb-Eddine , Essoussi Nadia
Published: December 2018

Big Data clustering has become an important challenge in data analysis since several applications require scalable clustering methods to organize such data into groups of similar objects. Given the computational cost of most of the existing clustering methods, we propose in this paper a new clustering method, referred to as STiMR [Formula: see text]-means, able to provide good tradeoff between scalability and clustering quality. The proposed method is based on the combination of three acceleration techniques: sampling, triangle inequality and MapReduce. Sampling is used to reduce the number of data points when building cluster prototypes, triangle inequality is used to reduce the number of comparisons when looking for nearest clusters and MapReduce is used to configure a parallel framework for running the proposed method. Experiments performed on simulated and real datasets have shown the effectiveness of the proposed method, with the existing ones, in terms of running time, scalability and internal validity measures.
An Active Learning Framework for Alpha Matting
Authors: Shen Yang , Wang Pengjie , Pan Zhifang , Bao Yanxia
Published: December 2018

Good trimap is essential for high-quality alpha matte. However, making high-quality trimap is hardwork, especially for complex images. In this paper, an active learning framework is proposed to make high quality trimap. There are two active learning methods which are employed: minimization of uncertainty sampling (MUS) and maximization of expected model output change (EMOC). MUS model finds the informative area in image which can decrease the uncertain sampling of alpha matte. EMOC model finds the important areas in image which can give the maximum expected output change of alpha matte. Two methods are combined to define the active map. Active map shows important areas which are informative in image. It can help users to make high quality trimap. The analysis and evaluation of benchmark datasets show that proposed method is effective.
A Characteristic Extraction Algorithm Based on Blocking Star Images
Authors: Du Yun , Wen Desheng , Liu Guizhong , Qiu Shi , Li Ni
Published: December 2018

The star images obtained through the CCD camera can visually display the star structure. In order to get the wide starry image, we need to extract the characteristics of star images to achieve the star image stitching. In the star images, star points, whose characteristics are limited, are easily influenced by noise and are also difficult to extract. The number of stars is too large to stitch accurately. Thus, we propose a stitching algorithm based on blocking star images. First, we establish the maximum intensity projection model based on time sequence to locate the star points accurately. Then, according to the relative positions of star points, the block model is introduced to realize the establishment of the characteristics. Finally, the star image stitching is achieved from the perspective of the characteristic similarity. The experiments illustrate that CM (combination measure) reaches 0.87, and the proposed algorithm has better anti-noise performance and robustness.
Long-time behavior of non-local in time Fokker–Planck equations via the entropy method
Authors: Kemppainen Jukka , Zacher Rico
Published: December 2018

We consider a rather general class of non-local in time Fokker–Planck equations and show by means of the entropy method that as [Formula: see text], the solution converges in [Formula: see text] to the unique steady state. Important special cases are the time-fractional and ultraslow diffusion case. We also prove estimates for the rate of decay. In contrast to the classical (local) case, where the usual time derivative appears in the Fokker–Planck equation, the obtained decay rate depends on the entropy, which is related to the integrability of the initial datum. It seems that higher integrability of the initial datum leads to better decay rates and that the optimal decay rate is reached, as we show, when the initial datum belongs to a certain weighted [Formula: see text] space. We also show how our estimates can be adapted to the discrete-time case thereby improving known decay rates from the literature.
Crack problem within the context of implicitly constituted quasi-linear viscoelasticity
Authors: Itou Hiromichi , Kovtunenko Victor A. , Rajagopal Kumbakonam R.
Published: December 2018

A quasi-linear viscoelastic relation that stems from an implicit viscoelastic constitutive body containing a crack is considered. The abstract form of the response function is given first in [Formula: see text], [Formula: see text], due to power-law hardening; second in [Formula: see text] due to limiting small strain. In both the cases, sufficient conditions on admissible response functions are formulated, and corresponding existence theorems are proved rigorously based on the variational theory and using monotonicity methods. Due to the presence of a Volterra convolution operator, an auxiliary-independent variable of velocity type is employed. In the case of limiting small strain, the generalized solution of the problem is provided within the context of bounded measures and expressed by a variational inequality.
Lorentz invariant mass and length scales
Authors: Bosso Pasquale , Das Saurya
Published: December 2018

We show that the standard Lorentz transformations admit an invariant mass (length) scale, such as the Planck scale. In other words, the frame independence of such a scale is built-in within those transformations, and one does not need to invoke the principle of relativity for their invariance. This automatically ensures the frame-independence of the spectrum of geometrical operators in quantum gravity. Furthermore, we show that the above predicts a small but measurable difference between the inertial and gravitational mass of any object, regardless of its size or whether it is elementary or composite.
Evolution of thin shells in D-dimensional general relativity
Authors: Ramirez Marcos A. , Aparicio Daniel
Published: December 2018

In this paper, we consider singular timelike spherical hypersurfaces embedded in a [Formula: see text]-dimensional spherically symmetric bulk spacetime which is an electrovacuum solution of Einstein equations with cosmological constant. We analyze the different possibilities regarding the orientation of the gradient of the standard [Formula: see text] coordinate in relation to the shell. Then we study the dynamics according to Einstein equations for arbitrary matter satisfying the dominant energy condition. In particular, we thoroughly analyze the asymptotic dynamics for both the small and large-shell-radius limits. We also study the main qualitative aspects of the dynamics of shells made of linear barotropic fluids that satisfy the dominant energy condition. Finally, we prove weak cosmic censorship for this class of solutions.
FINN-
R
Authors: Blott Michaela , Preußer Thomas B. , Fraser Nicholas J. , Gambardella Giulio , O’brien Kenneth , Umuroglu Yaman , Leeser Miriam , Vissers Kees
Published: December 2018

Convolutional Neural Networks have rapidly become the most successful machine-learning algorithm, enabling ubiquitous machine vision and intelligent decisions on even embedded computing systems. While the underlying arithmetic is structurally simple, compute and memory requirements are challenging. One of the promising opportunities is leveraging reduced-precision representations for inputs, activations, and model parameters. The resulting scalability in performance, power efficiency, and storage footprint provides interesting design compromises in exchange for a small reduction in accuracy. FPGAs are ideal for exploiting low-precision inference engines leveraging custom precisions to achieve the required numerical accuracy for a given application. In this article, we describe the second generation of the FINN framework, an end-to-end tool that enables design-space exploration and automates the creation of fully customized inference engines on FPGAs. Given a neural network description, the tool optimizes for given platforms, design targets, and a specific precision. We introduce formalizations of resource cost functions and performance predictions and elaborate on the optimization algorithms. Finally, we evaluate a selection of reduced precision neural networks ranging from CIFAR-10 classifiers to YOLO-based object detection on a range of platforms including PYNQ and AWS F1, demonstrating new unprecedented measured throughput at 50 TOp/s on AWS F1 and 5 TOp/s on embedded devices.
ReDCrypt
Authors: Rouhani Bita Darvish , Hussain Siam Umar , Lauter Kristin , Koushanfar Farinaz
Published: December 2018

Artificial Intelligence (AI) is increasingly incorporated into the
cloud business
in order to improve the functionality (e.g., accuracy) of the service. The adoption of AI as a cloud service raises serious privacy concerns in applications where the
risk of data leakage
is not acceptable. Examples of such applications include scenarios where clients hold potentially sensitive private information such as medical records, financial data, and/or location. This article proposes ReDCrypt, the first
reconfigurable
hardware-accelerated framework that empowers privacy-preserving inference of deep learning models in cloud servers. ReDCrypt is well-suited for
streaming (a.k.a., real-time AI)
settings where clients need to dynamically analyze their data as it is collected over time without having to queue the samples to meet a certain batch size. Unlike prior work, ReDCrypt neither requires to change how AI models are trained nor relies on two non-colluding servers to perform. The privacy-preserving computation in ReDCrypt is executed using
Yao’s Garbled Circuit
(GC) protocol. We break down the deep learning inference task into two phases: (i) privacy-insensitive (local) computation, and (ii) privacy-sensitive (interactive) computation. We devise a high-throughput and power-efficient implementation of GC protocol on FPGA for the privacy-sensitive phase. ReDCrypt’s accompanying API provides support for seamless integration of ReDCrypt into any deep learning framework. Proof-of-concept evaluations for different DL applications demonstrate up to 57-fold higher throughput per core compared to the best prior solution with no drop in the accuracy.
Sub-Stroke-Wise Relative Feature for Online Indic Handwriting Recognition
Authors: Bhattacharya Nilanjana , Roy Partha Pratim , Pal Umapada
Published: December 2018

The main problem of Bangla (Bengali) and Devanagari handwriting recognition is the shape similarity of characters. There are only a few pieces of work on writer-independent cursive online Indian text recognition, and the shape similarity problem needs more attention from the researchers. To handle the shape similarity problem of cursive characters of Bangla and Devanagari scripts, in this article, we propose a new category of features called ‘
sub-stroke-wise relative feature
’ (SRF) which are based on relative information of the constituent parts of the handwritten strokes. Relative information among some of the parts within a character can be a distinctive feature as it scales up small dissimilarities and enhances discrimination among similar-looking shapes. Also, contextual anticipatory phenomena are automatically modeled by this type of feature, as it takes into account the influence of previous and forthcoming strokes. We have tested popular state-of-the-art feature sets as well as proposed SRF using various (up to 20,000-word) lexicons and noticed that SRF significantly outperforms the state-of-the-art feature sets for online Bangla and Devanagari cursive word recognition.
Instruction Driven Cross-layer CNN Accelerator for Fast Detection on FPGA
Authors: Yu Jincheng , Ge Guangjun , Hu Yiming , Ning Xuefei , Qiu Jiantao , Guo Kaiyuan , Wang Yu , Yang Huazhong
Published: December 2018

In recent years, Convolutional Neural Networks (CNNs) have been widely applied in computer vision and have achieved significant improvements in object detection tasks. Although there are many optimizing methods to speed up CNN-based detection algorithms, it is still difficult to deploy detection algorithms on real-time low-power systems. Field-Programmable Gate Array (FPGA) has been widely explored as a platform for accelerating CNN due to its promising performance, high energy efficiency, and flexibility. Previous works show that the energy consumption of CNN accelerators is dominated by the memory access. By fusing multiple layers in CNN, the intermediate data transfer can be reduced. However, previous accelerators with the cross-layer scheduling are designed for a particular CNN model. In addition to the memory access optimization, the Winograd algorithm can greatly improve the computational performance of convolution.

In this article, to improve the flexibility of hardware, we design an instruction-driven CNN accelerator, supporting the Winograd algorithm and the cross-layer scheduling, for object detection. We modify the loop unrolling order of CNN, so that we can schedule a CNN across different layers with instructions and eliminate the intermediate data transfer. We propose a hardware architecture to support the instructions with Winograd computation units and reach the state-of-the-art energy efficiency. To deploy image detection algorithms onto the proposed accelerator with fixed-point computation units, we adopt the fixed-point fine-tune method, which can guarantee the accuracy of the detection algorithms.

We evaluate our accelerator and scheduling policy on the Xilinx KU115 FPGA platform. The intermediate data transfer can be reduced by more than 90% on the VGG-D CNN model with the cross-layer strategy. Thus, the performance of our hardware accelerator reaches 1700GOP/s on the classification model VGG-D. We also implement a framework for object detection algorithms, which achieves 2.3× and 50× in energy efficiency compared with GPU and CPU, respectively. Compared with floating-point algorithms, the accuracy of the fixed-point detection algorithms only drops by less than 1%.
Database Theory Column Report on PODS 2018
Authors: Arenas Marcelo
Published: December 2018

The 37th edition of the ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS) took place from June 11 to June 13, 2018, in Houston, Texas, USA. As in previous years, the symposium was held jointly with the ACM SIGMOD International Conference on Management of Data (SIGMOD). PODS focuses on theoretical aspects of data management systems and techniques, and the co-location with SIGMOD stimulates interaction between theory-oriented and system-oriented research.
Impairments of Visuospatial Attention in Children with Unilateral Spastic Cerebral Palsy
Authors: Ickx Gaétan , Hatem Samar M. , Riquelme Inmaculada , Friel Kathleen M. , Henne Camille , Araneda Rodrigo , Gordon Andrew M. , Bleyenheuft Yannick
Published: December 2018

Aim. This observational study aimed at assessing the prevalence of visuospatial attention deficits in children with unilateral spastic cerebral palsy (USCP), taking into consideration the affected hemibody and the localization of the brain lesion.Method. Seventy-five children with USCP were assessed with four visuospatial attention tests: star cancellation, Ogden figure copy, line bisection, and proprioceptive pointing.Results. A majority (64%) of children with USCP presented a deficit in at least one test compared to the reference values. The alterations observed in children with left or right USCP were related to egocentric or allocentric neglect, respectively. Children with cortico/subcortical lesion presented more often visuospatial attention deficits than children with periventricular lesion. Visuospatial attention deficits were not associated with brain lesion locations.Interpretation. Visuospatial attention deficits are prevalent in children with USCP and should be taken into account during their rehabilitation process. The present results shed new light on the interpretation of motor impairments in children with USCP as they may be influenced by the frequent presence of visuospatial deficits.
A Rare Localized Pituitary Stalk Germinoma Presenting in the Third Decade
Authors: González Bóssolo Alex , Mangual Garcia Michelle , Davila Kyrmarie , Brau Ricardo , Sanchez Ortiz Javier , Hernan Martinez Jose
Published: December 2018

We report the case of a 34-year-old male Hispanic patient who presented with an 8-month history of polyuria and decreased libido. An evaluation revealed hypopituitarism, central diabetes insipidus, and a pituitary stalk lesion. No evidence of a neoplasm or an inflammatory/infiltrative disease was found. We treated the patient conservatively with steroid therapy. However, as a result of disease progression, transsphenoidal surgery was performed to obtain tissue for a pathological analysis. Histopathology revealed an intrasellar germinoma, confirmed by immunochemistry. Due to localized disease, radiotherapy was initiated and clinical improvement was noted. This case emphasizes the importance of histopathological analysis; for many physicians, the presentation of a pituitary stalk lesion in a young male adult creates a clinical conundrum. Although the most common etiologies are an inflammatory or secondary neoplasm, the possible presence of an intrasellar neoplasm should not be ruled out. In many cases, imaging characteristics and tumor markers may aid in the diagnosis without the need of an aggressive diagnostic approach. However, in this case, histopathological analysis was the only way to make a correct diagnosis and provide adequate treatment for the patient.
Tensioning-Phase Box Girder Deformation Prediction Model Based on Ant Colony Algorithm and Residual Correction
Authors: Xu Gangnian , Wang Youzhi , Liu Shangbin , Wang Shimin
Published: December 2018

The girder of prestressed concrete continuous box girder bridge strengthened by a stay cable system has a very complex deformation mechanism, and it is difficult to establish accurate numerical model for prediction. For these problems, a prediction method based on the combination of ant colony algorithm and residual combination correction model is proposed. In this method, the measuring points are considered as the cities in TSP ant colony algorithm, the information function model and heuristic function model are constructed, the pheromone update mechanism and ant search mechanism are established, and the deformation prediction of the main girder based on ant colony algorithm prediction model is achieved. On this basis, in order to fit the random change process of main girder deflection better, the periodic function generated by harmonic transform and sine function are introduced to modify the predicted results, which makes up for the low precision defect of single model. The results show that compared with finite element method, unequal interval gray model (1,1) (UIGM (1,1)), one-time residual correction UIGM (1,1), Markov chain residual correction UIGM (1,1), and ant colony algorithm model, this model can reflect the space-time effect and casual fluctuation feature of the development of girder deformation better and also has higher prediction accuracy and efficiency. The mean relative error of the predictive value is 3.39%, the posterior error ratio is 0.060, and the accuracy level reaches level 1. This model provides a new way for the girder deformation prediction of bridge strengthened by the stay cable system.
Automated Tumour Recognition and Digital Pathology Scoring Unravels New Role for PD-L1 in Predicting Good Outcome in ER-/HER2+ Breast Cancer
Authors: Humphries Matthew P. , Hynes Sean , Bingham Victoria , Cougot Delphine , James Jacqueline , Patel-Socha Farah , Parkes Eileen E. , Blayney Jaine K. , O’Rorke Michael A. , Irwin Gareth W. , McArt Darragh G. , Kennedy Richard D. , Mullan Paul B. , McQuaid Stephen , Salto-Tellez Manuel , Buckley Niamh E.
Published: December 2018

The role of PD-L1 as a prognostic and predictive biomarker is an area of great interest. However, there is a lack of consensus on how to deliver PD-L1 as a clinical biomarker. At the heart of this conundrum is the subjective scoring of PD-L1 IHC in most studies to date. Current standard scoring systems involve separation of epithelial and inflammatory cells and find clinical significance in different percentages of expression, e.g., above or below 1%. Clearly, an objective, reproducible and accurate approach to PD-L1 scoring would bring a degree of necessary consistency to this landscape. Using a systematic comparison of technologies and the application of QuPath, a digital pathology platform, we show that high PD-L1 expression is associated with improved clinical outcome in Triple Negative breast cancer in the context of standard of care (SoC) chemotherapy, consistent with previous findings. In addition, we demonstrate for the first time that high PD-L1 expression is also associated with better outcome in ER- disease as a whole including HER2+ breast cancer. We demonstrate the influence of antibody choice on quantification and clinical impact with the Ventana antibody (SP142) providing the most robust assay in our hands. Through sampling different regions of the tumour, we show that tumour rich regions display the greatest range of PD-L1 expression and this has the most clinical significance compared to stroma and lymphoid rich areas. Furthermore, we observe that both inflammatory and epithelial PD-L1 expression are associated with improved survival in the context of chemotherapy. Moreover, as seen with PD-L1 inhibitor studies, a low threshold of PD-L1 expression stratifies patient outcome. This emphasises the importance of using digital pathology and precise biomarker quantitation to achieve accurate and reproducible scores that can discriminate low PD-L1 expression.
Malignant Hypertension Causing a Pulmonary-Renal Syndrome
Authors: Yong Bryan , Power David A.
Published: December 2018

Background. Pulmonary-renal syndrome is characterised by acute kidney injury, haematuria, and haemoptysis and is a well-recognised presentation of diseases such as ANCA vasculitis that require urgent immunosuppression. Case Presentation. A patient presented with a brief history of haemoptysis, acute renal failure, microscopic haematuria, and severe hypertension. The diagnosis was initially not clear so he was treated with antihypertensives, renal replacement therapy, and immunosuppression. Renal biopsy subsequently showed evidence of malignant hypertension. Autoantibodies were uniformly negative. Conclusions. This case demonstrates that malignant hypertension can present as pulmonary-renal syndrome.
Grape Seed Proanthocyanidin Extract Inhibits Human Esophageal Squamous Cancerous Cell Line ECA109 via the NF-κB Signaling Pathway
Authors: Guo Fangming , Hu Yunhua , Niu Qiang , Li Yu , Ding Yusong , Ma Rulin , Wang Xianhua , Li Shugang , Xie Jianxin
Published: December 2018

Esophageal squamous cell carcinoma is the most common type of squamous cell carcinoma. Grape seed proanthocyanidin extract (GSPE) is considered to exhibit anticancer activity against several different types of cancer. We aimed to determine whether GSPE inhibited esophageal squamous cancerous cells and the possible involvement of NF-κB in this process. The human esophageal squamous cancer cell line ECA109 was treated with GSPE (0–80 μg/mL) and BAY11-7082 (10 μmol/L) for 12, 24, and 48 h. The MTT assay was used to determine cell proliferation; alterations in cell apoptosis were detected by flow cytometry; levels of inflammatory factors interleukin-6 and cyclooxygenase-2 and apoptotic proteins Bax/Bcl-2 were measured by ELISA; qRT-PCR and western blots were used to examine the activation of caspase-3 and NF-κB signaling. GSPE inhibited the proliferation of ECA109 cells and induced cellular apoptosis in a time- and dose-dependent manner. ELISA results showed that GSPE and BAY11-7082 reduced the secretion of inflammatory cytokines interleukin-6 and cyclooxygenase-2. The results of PCR and western blotting indicated that GSPE and BAY11-7082 activated caspase-3 and attenuated the activation of the NF-κB signaling pathway. GSPE induced apoptosis in ECA109 cells and inhibited ECA109 cell proliferation via a reduction in the secretion of inflammatory cytokines. This mechanism may be related to the attenuation of NF-κB activity and the sensitization of caspase-3.
Roles of Moringa oleifera Leaf Extract in Improving the Impact of High Dietary Intake of Monosodium Glutamate‐Induced Liver Toxicity, Oxidative Stress, Genotoxicity, DNA Damage, and PCNA Alterations in Male Rats
Authors: Albrahim Tarfa , Binobead Manal Abdulaziz
Published: December 2018

It is common for food to be made more palatable through the use of the flavour enhancer monosodium glutamate, also known as vetsin powder. The purpose of the study described in this paper was to explore how vetsin‐induced hepatic toxicity, DNA fragmentation, damage, and oxidative stress modifications could be mitigated with moringa leaf extract (MLE). To that end, 40 male rats were separated into four groups: normal control, positive control or MLE, vetsin, and vetsin combined with MLE. Results indicated that, compared to the control group, the levels of serum alanine aminotransferase (ALT), aminotransferase (AST), alkaline phosphatase (ALP), gamma‐glutamyl transferase (GGT), liver malondialdehyde (MDA), DNA damage, injury, PCNA, and P53 expressions were significantly enhanced by the administration of vetsin (P < 0.05). However, the vetsin group had significantly reduced levels of albumin, globulin, total protein, liver glutathione (GSH), superoxide dismutase enzyme (SOD), catalase, and glutathione S‐transferase (GST) enzyme activities (P < 0.05) by comparison to control. Meanwhile, modifications in liver functions, oxidative stress, DNA damage, liver injury, and PCNA expression were alleviated when vetsin was administered alongside MLE. The authors conclude that vetsin may have many side effects and that MLE can ameliorate biochemical changes, oxidative stress, hepatic injury, PCNA, and P53 alterations induced by vetsin administration.
Antifibrotic Effect of Marine Ovothiol in an In Vivo Model of Liver Fibrosis
Authors: Brancaccio Mariarita , D’Argenio Giuseppe , Lembo Vincenzo , Palumbo Anna , Castellano Immacolata
Published: December 2018

Liver fibrosis is a complex process caused by chronic hepatic injury, which leads to an excessive increase in extracellular matrix protein accumulation and fibrogenesis. Several natural products, including sulfur‐containing compounds, have been investigated for their antifibrotic effects; however, the molecular mechanisms underpinning their action are partially still obscure. In this study, we have investigated for the first time the effect of ovothiol A, π‐methyl‐5‐thiohistidine, isolated from sea urchin eggs on an in vivo murine model of liver fibrosis. Mice were intraperitoneally injected with carbon tetrachloride (CCl4) to induce liver fibrosis and treated with ovothiol A at the dose of 50 mg/kg 3 times a week for 2 months. Treatment with ovothiol A caused a significant reduction of collagen fibers as observed by histopathological changes and serum parameters compared to mice treated with control solution. This antifibrotic effect was associated to the decrease of fibrogenic markers involved in liver fibrosis progression, such as the transforming growth factor (TGF‐β), the α‐smooth muscle actin (α‐SMA), and the tissue metalloproteinases inhibitor (TIMP‐1). Finally, we provided evidence that the attenuation of liver fibrosis by ovothiol A treatment can be regulated by the expression and activity of the membrane‐bound γ‐glutamyl‐transpeptidase (GGT), which is a key player in maintaining intracellular redox homoeostasis. Overall, these findings indicate that ovothiol A has significant antifibrotic properties and can be considered as a new marine drug or dietary supplement in potential therapeutic strategies for the treatment of liver fibrosis.
The Effects of Maternal Mirroring on the Development of Infant Social Expressiveness: The Case of Infant Cleft Lip
Authors: Murray Lynne , Bozicevic Laura , Ferrari Pier Francesco , Vaillancourt Kyla , Dalton Louise , Goodacre Tim , Chakrabarti Bhismadev , Bicknell Sarah , Cooper Peter , Stein Alan , De Pascalis Leonardo
Published: December 2018

Parent-infant social interactions start early in development, with infants showing active communicative expressions by just two months. A key question is how this social capacity develops. Maternal mirroring of infant expressions is considered an important, intuitive, parenting response, but evidence is sparse in the first two months concerning the conditions under which mirroring occurs and its developmental sequelae, including in clinical samples where the infant’s social expressiveness may be affected. We investigated these questions by comparing the development of mother-infant interactions between a sample where the infant had cleft lip and a normal, unaffected, comparison sample. We videotaped dyads in their homes five times from one to ten weeks and used a microanalytic coding scheme for maternal and infant behaviours, including infant social expressions, and maternal mirroring and marking responses. We also recorded maternal gaze to the infant, using eye-tracking glasses. Although infants with cleft lip did show communicative behaviours, the rate of their development was slower than in comparison infants. This group difference was mediated by a lower rate of mirroring of infant expressions by mothers of infants with cleft lip; this effect was, in turn, partly accounted for by reduced gaze to the infant’s mouth, although the clarity of infant social expressions (indexed by cleft severity) and maternal self-blame regarding the cleft were also influential. Results indicate the robustness of parent-infant interactions but also their sensitivity to specific variations in interactants’ appearance and behaviour. Parental mirroring appears critical in infant social development, likely supported by the mirror neuron system and underlying clinical and, possibly, cultural differences in infant behaviour. These findings suggest new avenues for clinical intervention.
How Senses Work Together: Cross-Modal Interactions between Primary Sensory Cortices
Authors: Teichert Manuel , Bolz Jürgen
Published: December 2018

On our way through a town, the things we see can make us change the way we go. The things that we hear can make us stop or walk on, or the things we feel can cause us to wear a warm jacket or just a t-shirt. All these behaviors are mediated by highly complex processing mechanisms in our brain and reflect responses to many important sensory inputs. The mammalian cerebral cortex, which processes the sensory information, consists of largely specialized sensory areas mainly receiving information from their corresponding sensory modalities. The first cortical regions receiving the input from the outer world are the so called primary sensory cortices. Strikingly, there is convincing evidence that primary sensory cortices do not work in isolation but are substantially affected by other sensory modalities. Here, we will review previous and current literature on this cross-modal interplay.
Intelligent Prediction of Transmission Line Project Cost Based on Least Squares Support Vector Machine Optimized by Particle Swarm Optimization
Authors: Yi Tao , Zheng Hao , Tian Yu , Liu Jin-peng
Published: December 2018

In order to meet the demand of power supply, the construction of transmission line projects is constantly advancing, and the level of cost control is constantly improving, which puts forward higher requirements for the accuracy of cost prediction. This paper proposes an intelligent cost prediction model based on least squares support vector machine (LSSVM) optimized by particle swarm optimization (PSO). Originally extracting natural, technological, and economic indexes from the perspective of cost composition, principal component analysis (PCA) is used to reduce the dimension of indexes. And PSO is innovatively introduced to optimize the parameters of LSSVM model to obtain the optimal parameters. The obtained principal component data are imported into empirical parameter LSSVM prediction model and the optimized parameter PSO-LSSVM prediction model, respectively, for modeling and prediction, and then comparing the prediction results to analyze the effect of model optimization. The results show that the absolute deviation of the optimized parameter prediction model is less than 9%. And the prediction accuracy of the optimized parameter prediction model is better than that of the empirical parameter model, which can provide a reliable basis for investment decision-making of transmission line projects.
Exploring Systemic Autoimmunity in Thyroid Disease Subjects
Authors: Siriwardhane Thushani , Krishna Karthik , Ranganathan Vinodh , Jayaraman Vasanth , Wang Tianhao , Bei Kang , Rajasekaran John J. , Krishnamurthy Hari
Published: December 2018

Introduction. Individuals with one autoimmune disease are at risk of developing a second autoimmune disease, but the pathogenesis or the sequential occurrence of multiple autoimmune diseases has not been established yet. In this study, we explored the association and sequential occurrence of antibodies in thyroid disease and systemic autoimmune disease subjects. We evaluated thyroid hormones, thyroid-stimulating hormone (TSH), free thyroxine (FT4), thyroid autoantibodies, anti-thyroperoxidase (anti-TPO), and anti-thyroglobulin (Tg) to comprehend the association with systemic autoimmune autoantibodies, anti-nuclear antibodies (ANA), and autoantibodies to extractable nuclear antigens (ENA) in subjects with thyroid-related symptoms. Methods. A total of 14825 subjects with thyroid-related symptoms were tested at Vibrant America Clinical Laboratory for thyroid markers (TSH, FT4, anti-TPO, and anti-Tg) and an autoimmune panel (ANA panel and ENA-11 profile) from March 2016 to May 2018. Thyroid-positive (based on TSH and FT4 levels), anti-TPO-positive, and anti-Tg-positive subjects were assessed for the prevalence of ANA and anti-ENA antibodies. A 2-year follow-up study was conducted to assess the sequential order of appearance of autoimmune markers in thyroid and systemic autoimmune diseases. Results. In the retrospective analysis, 343/1671 (20.5%), 2037/11235 (18.1%), and 1658/9349 (17.7%) of thyroid+, anti-TPO+, and anti-Tg+ subjects were found to be seropositive for ANA. Anti-ENA was detected in a higher prevalence than ANA with 475/1671 (28.4%), 3063/11235 (27.3%), and 2511/9349 (26.9%) in the same groups of subjects, respectively. Our results are found to be much higher than the reported prevalence of anti-ENA in general population. During the 2-year follow-up study, anti-TPO appeared significantly earlier than ANA and anti-ENA in an average of 253 (±139) and 227 (±127) days, respectively. Conclusions. A high prevalence of anti-ENA and ANA was found to be coexisting with autoimmune thyroid disease subjects, with anti-TPO occurring prior to the onset of ANA and anti-ENA. Therefore, frequent follow-ups and evaluation of ANA and anti-ENA in subjects with anti-TPO positivity would be beneficial in early detection of other systemic autoimmune diseases.
Transient Acquired Hypoventilation Syndrome Secondary to Uncal Herniation Is Successfully Treated with Bilevel Noninvasive Positive Pressure Ventilation
Authors: Hou Linle , Stoll Jonathan , Pioppo Lauren , Xu Jack , Khan Wajahat
Published: December 2018

Background.To describe an unusual presentation of acquired hypoventilation syndrome treated successfully with noninvasive positive pressure ventilation.Case Presentation.We report a case report of a 48-year-old male who presented to the emergency room for recurrent syncope. He was found to have a ventricular colloid cyst causing uncal herniation. The patient was noted to be intermittently apneic and bradypnic. Transient hypoventilation was successfully treated with noninvasive positive pressure ventilation and the patient made a full neurological recovery following transcallosal resection of the colloid cyst. Subsequently, the hypoventilation resolved.Conclusion.With prompt surgical intervention, full neurological recovery is possible after cerebral uncal herniation. In rare circumstances, this can result in transient alveolar hypoventilation. Bilevel noninvasive positive pressure ventilation can be used to successfully manage the hypoventilation.