Miracle-dz/UniFAR-FTUs huggingface dataset:
Biofilm Destruction on Endotracheal Tubes by Photodynamic Inactivation.

BACKGROUND Hospital infections are a public health problem that can occur with the use of catheters and endotracheal tubes (ETT). Pathogenic microorganisms may adhere to surfaces of these materials forming a biofilm and produce an extracellular polymer matrix that promotes resistance of microorganisms to factors such as pH, temperature and drugs. The conventional treatment is being made by antibiotics, which has serious adverse effects in immunocompromised patients. Photodynamic therapy (PDT) is an alternative for microbial inactivation noninvasive without the stimulus of microbial resistance. PDT combines light and a photosensitive molecule for produce reactive oxygen species leading to bacterial death. OBJECTIVE The objective of this study was to determine the efficacy of a PDT protocol in bacterial inactivation of biofilm ETT. METHOD The photosensitizer (PS) used was curcumin and the light source LED at 450nm. A statistical experimental design was used for optimization of antimicrobial PDT. RESULTS The highest microbial inactivation was observed with 70% biofilm reduction in conditions 1.25 mg/mL curcumin, 2 h of PS incubation and 50 J/cm2. CONCLUSION This study described the photodynamic death of bacteria forming a biofilm on ETT. Parameters optimization was important for clinical application of this system.
A novel CHCHD10 mutation implicates a Mia40‐dependent mitochondrial import deficit in ALS

CHCHD10 mutations are linked to amyotrophic lateral sclerosis, but their mode of action is unclear. In a 29‐year‐old patient with rapid disease progression, we discovered a novel mutation (Q108P) in a conserved residue within the coiled‐coil‐helix‐coiled‐coil‐helix (CHCH) domain. The aggressive clinical phenotype prompted us to probe its pathogenicity. Unlike the wild‐type protein, mitochondrial import of CHCHD10 Q108P was blocked nearly completely resulting in diffuse cytoplasmic localization and reduced stability. Other CHCHD10 variants reported in patients showed impaired mitochondrial import (C122R) or clustering within mitochondria (especially G66V and E127K) often associated with reduced expression. Truncation experiments suggest mitochondrial import of CHCHD10 is mediated by the CHCH domain rather than the proposed N‐terminal mitochondrial targeting signal. Knockdown of Mia40, which introduces disulfide bonds into CHCH domain proteins, blocked mitochondrial import of CHCHD10. Overexpression of Mia40 rescued mitochondrial import of CHCHD10 Q108P by enhancing disulfide‐bond formation. Since reduction in CHCHD10 inhibits respiration, mutations in its CHCH domain may cause aggressive disease by impairing mitochondrial import. Our data suggest Mia40 upregulation as a potential therapeutic salvage pathway.
Feline injection site sarcoma: immunohistochemical characteristics

Objectives Feline injection site sarcoma (FISS) is a rapid growing locally aggressive tumor with a low metastatic rate. Its histologic features are clearly defined, but there are few studies regarding its immunohistochemical characteristics. The present study investigated the immunohistochemical characteristics of 21 cases of FISS. Methods FISSs from 12 male and nine female cats, 20 mixed-breed and one Siamese, were included in the study. After histopathological diagnosis, additional histologic sections were immunostained for vimentin, cytokeratin, desmin, S100 protein, viral feline leukemia virus (FeLV) particles, cyclooxygenase 2 (COX-2) and c-KIT. Positive and negative controls were adopted accordingly. Immunostainings were classified as positive or negative according to the number of positive cells from a total of 1000 cells per tumor section. Results Histopathologic diagnosis of the tumors revealed 18 (85.7%) fibrosarcomas and three (14.3%) other sarcomas; four fibrosarcomas (22.2%) were grade III, five (27.8%) were grade II and nine (50.0%) were grade I. Two sarcomas were grade III and one was grade II. Seventeen (81%) tumors were negative for desmin. All samples were positive for vimentin. Twenty tumors (95.2%) were positive for S-100 protein. Positivity for c-KIT was observed in four (19%) samples; COX-2 was positive in 13 (61.9%) and FeLV viral particles were positive in nine (42.9%) FISSs. Conclusions and relevance Immunohistochemical findings of FISSs revealed positive immunostainings for desmin, vimentin, S-100 protein, c-KIT, COX-2 and FeLV viral particles.
A Note on Wage Inequality, Technology, and Trade

Zeira (2007) presents a two-country model of endogenous technology and trade, illustrating that trade liberalization reduces wage inequality in developing countries. The result contrasts the current outsourcing trade literature; the conflict is due to the critical assumption made in his model that “the most rewarding technologies are invested first. ” If we relax this assumption, or allow the technology frontier to foster labor gains in all existing industries, then Zeira’s model is, in fact, consistent with the current outsourcing trade literature.
Overview of TAC-KBP2016 Tri-lingual EDL and Its Impact on End-to-End KBP

In this paper we give an overview of the Tri-lingual Entity Discovery and Linking (EDL) task at the Knowledge Base Population (KBP) track at TAC2016. We will summarize several new and effective research directions including cross-lingual knowledge transfer and exploiting language-specific resources. In this year we make the EDL task as part of end-to-end Tri-lingual cold-start knowledge base construction on a very large document collection (90,003 documents). So we will also measure and investigate the impact of EDL on cold-start slot filling.
Differential Suppression of Nicotiana benthamiana Innate Immune Responses by Transiently Expressed Pseudomonas syringae Type III Effectors

The plant pathogen Pseudomonas syringae injects about 30 different virulence proteins, so-called effectors, via a type III secretion system into plant cells to promote disease. Although some of these effectors are known to suppress either pattern-triggered immunity (PTI) or effector-triggered immunity (ETI), the mode of action of most of them remains unknown. Here, we used transient expression in Nicotiana benthamiana, to test the abilities of type III effectors of Pseudomonas syringae pv. tomato (Pto) DC3000 and Pseudomonas syringae pv. tabaci (Pta) 11528 to interfere with plant immunity. We monitored the sequential and rapid bursts of cytoplasmic Ca2+ and reactive oxygen species (ROS), the subsequent induction of defense gene expression, and promotion of cell death. We found that several effector proteins caused cell death, but independently of the known plant immune regulator NbSGT1, a gene essential for ETI. Furthermore, many effectors delayed or blocked the cell death-promoting activity of other effectors, thereby potentially contributing to pathogenesis. Secondly, a large number of effectors were able to suppress PAMP-induced defense responses. In the majority of cases, this resulted in suppression of all studied PAMP responses, suggesting that these effectors target common elements of PTI. However, effectors also targeted different steps within defense pathways and could be divided into three major groups based on their suppressive activities. Finally, the abilities of effectors of both Pto DC3000 and Pta 11528 to suppress plant immunity was conserved in most but not all cases. Overall, our data present a comprehensive picture of the mode of action of these effectors and indicate that most of them suppress plant defenses in various ways.
Perceptual Surgical Knife with Wavelet Denoising

Robotic surgery is a new technology in medical applications and has been undergoing rapid development. The surgical knife, essential for robotic surgery, has the ability to determine the success of an operation. In this paper, on the basis of the principle of field-effect transistors (FETs), a perceptual surgical knife is proposed to detect the electrons or electric field of the human body with distinguishable signals. In addition, it is difficult to discriminate between the motions of surgical knives from the perceptual signals that are disturbed by high-frequency Gaussian white noise. Therefore, the wavelet denoising approach is chosen to reduce the high-frequency noise. The proposed perceptual surgical knife with the wavelet denoising method has the characteristics of high sensitivity, low cost, and good repeatability.
Overview of Linguistic Resources for the TAC KBP 2015 Evaluations: Methodologies and Results

Knowledge Base Population (KBP) is an evaluation track of the Text Analysis Conference (TAC), a workshop series organized by the National Institute of Standards and Technology (NIST). In 2015, TAC KBP’s seventh year of operation, the evaluations focused on four tracks targeting information extraction and question answering technologies: Tri-lingual Entity Discovery & Linking, Cold Start, Event Argument Linking, and Event Nuggets. Linguistic Data Consortium (LDC) at the University of Pennsylvania has supported TAC KBP since 2009 and continued again in 2015, developing, maintaining, and distributing new and existing linguistic resources for the evaluation series, including queries, human-generated responses, assessments, and tools and specifications. This paper describes LDC's resource creation efforts and their results in support of TAC KBP 2015.
Behavior of singing fin whales Balaenoptera physalus tracked acoustically offshore of Southern California

Author(s): Varga, LM; Wiggins, SM; Hildebrand, JA | Abstract: © The authors 2018. Fin whales Balaenoptera physalus produce stereotyped low-frequency calls (15- 30 Hz) that can be detected at great ranges and are considered song when produced in a repeated temporal pattern. These calls, referred to as 20 Hz calls, were localized and tracked using a 1 km aperture array of 4 passive acoustic recorders at approximately 800 m depth northwest of San Clemente Island, offshore of Southern California, USA, for 4 continuous weeks during late fall 2007. A total of 1454 calls were localized over the recording period. The average (±SD) estimated source sound pressure level was 194.8 ± 0.2 dBpp re 1 μPa2 at 1 m (where pp is peak-to-peak) and 180.9 ± 0.2 dBrms re 1 μPa at 1 m (where rms is root mean square). The majority of these calls were in the form of a doublet song pattern, with average inter-pulse intervals of 13 and 18 s. These tracks are the first to be reported for transiting solitary singing fin whales using passive acoustic monitoring techniques. Acoustic tracking of fin whales provides insight into the ecology and behavior of this endangered species as well as vocal behaviors, which are important when studying the potential impact of anthropogenic noise. Call source sound pressure level, along with calling behavior, provides important parameters required for population density estimation. Furthermore, studying fin whale song patterns may aid in distinguishing different subpopulations.
Synthetic Inertia Control Strategy for Doubly Fed Induction Generator Wind Turbine Generators Using Lithium-Ion Supercapacitors

To address the system operability challenges due to the continuous reduction of system inertia by increasing penetration of renewable power generation, this paper proposes a new synthetic inertia control (SIC) strategy for doubly fed induction generator (DFIG)-based wind turbine generators. The proposed SIC scheme enables individual DFIG generators to contribute an effective inertial response which helps to stabilise the rate of change of frequency and minimize the maximum frequency deviations in particular under severe disturbance conditions. To achieve the proposed SIC, lithium-ion supercapacitors are required in the dc link of the DFIG power electronic conversion system to increase extra energy storage capability. The DFIG's dc voltage operates at various levels following the derived SIC algorithms for energy exchange with the connected ac grid, and the conventional control system for DFIG is modified to implement the algorithms. The functions and system benefits of SIC scheme are verified using a DFIG model connected to a power system and compared with the simulations of conventional DFIG control scheme. Practical issues such as size, cost, weight, connection configuration, and charging/discharging rate of lithium-ion capacitors for the SIC are discussed and relevant recommendations are presented.
Effects of Psidium guajava leaf extract on secretion systems of gram‐negative enteropathogenic bacteria

In this study, 672 plant‐tissue extracts were screened for phytochemicals that inhibit the function of the type III secretion system (T3SS) of enteropathogenic Escherichia coli (EPEC) and enterohemorrhagic E. coli (EHEC). Among candidates examined, an extract from the leaves of Psidium guajava (guava) was found to inhibit secretion of EPEC‐secreted protein B (EspB) from EPEC and EHEC without affecting bacterial growth. Guava extract (GE) also inhibited EPEC and EHEC from adhering to, and injecting EspB into, HEp‐2 cells. GE seemed to block translocation of EspB from the bacterial cells to the culture medium. In addition, GE also inhibited the T3SS of Yersinia pseudotuberculosis and Salmonella enterica serovar Typhimurium. After exposure to GE, Y. pseudotuberculosis stopped secreting Yersinia outer proteins and was unable to induce apoptosis of mouse bone marrow‐derived macrophages. S. typhimurium exposed to GE stopped secreting Sip proteins and was unable to invade HEp‐2 cells. GE inhibited secretion of EspC, the type V secretion protein of EPEC, but not secretion of Shiga toxin 2 from EHEC. Thus, our results suggest that guava leaves contain a novel type of antimicrobial compound that could be used to treat and prevent gram‐negative enteropathogenic bacterial infections.
Review of Computer Assisted Diagnosis to Analyze the MRI (Magnetic Resource Image) and Detect Alzheimer Disease

Technological evolution has led to biomedical data acquisitions increasingly voluminous, heterogeneous and complex require efficient and timely systems to analyze and treatments to help physicians define diagnoses and appropriate prognoses in a timely manner. Support systems for Decision-making based on Biomedical Computing have become ubiquitous in clinical settings. In this context, we present in the first part of this article the main steps and components of a Computer-Assisted Diagnosis CAD system from the MRI (Magnetic Resonance Imaging) data. In the second part, we present some existing CAD systems to detect Alzheimer's disease (AD) at an early stage.
Suppressor of clathrin deficiency (Scd6)—An emerging RGG‐motif translation repressor

Translation control plays a key role in variety of cellular processes. Translation initiation factors augment translation, whereas translation repressor proteins inhibit translation. Different repressors act by distinct mechanisms to accomplish the repression process. Although messenger RNAs (mRNAs) can be repressed at various steps of translation, most repressors have been reported to target the initiation step. We focus on one such translation repressor, an Arginine–Glycine–Glycine (RGG)‐motif containing protein Scd6. Using this protein as a model, we present a discourse on the known and possible functions of this repressor, its mechanism of action and its recently reported regulation. We suggest a case for conservation of the mechanism employed by Scd6 along with its regulation in orthologs, and propose that Scd6 family of proteins will be an ideal tool to understand translation control and mRNA fate decision mechanisms across biological systems.
OpenKN at TAC KBP 2016

This paper describes the system OpenKN which we established in the TAC KBP 2016. In TAC KBP 2016, we participated in one track: Cold Start KB Track. In order to complete the task, we developed a fivestep system which solves the problem of building knowledge base from a document collection of unstructured text. These five steps to complete this task are documentprocessing, relation extraction, crossdocument co-reference resolution, inference, and post-processing, where the relation extractor is the combination of four methods: rule-based pattern extractor, bootstrapping, OpenIE and an Implicit Relation Information Extractor.
Computational Evaluation of Cochlear Implant Surgery Outcomes Accounting for Uncertainty and Parameter Variability

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process.
Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings

The rise of neural networks, and particularly recurrent neural networks, has produced significant advances in part-of-speech tagging accuracy. One characteristic common among these models is the presence of rich initial word encodings. These encodings typically are composed of a recurrent character-based representation with dynamically and pre-trained word embeddings. However, these encodings do not consider a context wider than a single word and it is only through subsequent recurrent layers that word or sub-word information interacts. In this paper, we investigate models that use recurrent neural networks with sentence-level context for initial character and word-based representations. In particular we show that optimal results are obtained by integrating these context sensitive representations through synchronized training with a meta-model that learns to combine their states.
QIG: Quantifying the Importance and Interaction of GPGPU Architecture Parameters

Graphic processing units (GPUs) are widely used for general-purpose computing—so-called GPGPU computing. GPUs feature a large number of architecture parameters, resulting in a huge design space. To quickly explore this design space and identify the optimum architecture for a group of widely used computing kernels, it is critical to know how important each parameter is and how strongly these parameters interact with each other. This paper proposes an ensemble-learning-based approach, called quantifying the importance and interaction of Gpgpu architecture parameters (QIG), to quantify the importance of architecture parameters and their interactions with respect to performance. QIG employs a stochastic gradient boosted regression tree to construct performance models using performance data from a random set of GPU architectures. Leveraging these models, QIG observes the impact of each architecture parameter on performance, and calculates its importance and interaction intensity with other parameters. Using 25 widely used GPGPU kernels, we demonstrate that QIG accurately ranks the importance and interaction of GPU architecture parameters while the previously proposed Plackett–Burman design does not. Moreover, we show that QIG leads to a substantially more accurate performance model compared to prior work, including Starchart and approaches using artificial neural networks and supported vector machines: average error of 4.2% for QIG versus 23+% for prior work. Finally, QIG reveals a number of interesting insights for GPU architectures running GPGPU workloads.
Estimating Functional Connectivity Symmetry between Oxy- and Deoxy-Haemoglobin: Implications for fNIRS Connectivity Analysis

Functional Near InfraRed Spectroscopy (fNIRS) connectivity analysis is often performed using the measured oxy-haemoglobin (HbO2) signal, while the deoxy-haemoglobin (HHb) is largely ignored. The in-common information of the connectivity networks of both HbO2 and HHb is not regularly reported, or worse, assumed to be similar. Here we describe a methodology that allows the estimation of the symmetry between the functional connectivity (FC) networks of HbO2 and HHb and propose a differential symmetry index (DSI) indicative of the in-common physiological information. Our hypothesis is that the symmetry between FC networks associated with HbO2 and HHb is above what should be expected from random networks. FC analysis was done in fNIRS data collected from six freely-moving healthy volunteers over 16 locations on the prefrontal cortex during a real-world task in an out-of-the-lab environment. In addition, systemic data including breathing rate (BR) and heart rate (HR) were also synchronously collected and used within the FC analysis. FC networks for HbO2 and HHb were established independently using a Bayesian networks analysis. The DSI between both haemoglobin (Hb) networks with and without systemic influence was calculated. The relationship between the symmetry of HbO2 and HHb networks, including the segregational and integrational characteristics of the networks (modularity and global efficiency respectively) were further described. Consideration of systemic information increases the path lengths of the connectivity networks by 3%. Sparse networks exhibited higher asymmetry than dense networks. Importantly, our experimental connectivity networks symmetry between HbO2 and HHb departs from random (t-test: t(509) = 26.39, p < 0.0001). The DSI distribution suggests a threshold of 0.2 to decide whether both HbO2 and HHb FC networks ought to be studied. For sparse FC networks, analysis of both haemoglobin species is strongly recommended. Our DSI can provide a quantifiable guideline for deciding whether to proceed with single or both Hb networks in FC analysis.