ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Advances in the treatment of intrahepatic cholangiocarcinoma: An overview of the current and future therapeutic landscape for clinicians

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor and remains a fatal malignancy in the majority of patients. Approximately 20%-30% of patients are eligible for resection, which is considered the only potentially curative treatment; and, after resection, a median survival of 53 months has been reported when sequenced with adjuvant capecitabine. For the 70%-80% of patients who present with locally unresectable or distant metastatic disease, systemic therapy may delay progression, but survival remains limited to approximately 1 year. For the past decade, doublet chemotherapy with gemcitabine and cisplatin has been considered the most effective first-line regimen, but results from the recent use of triplet regimens and even immunotherapy may shift the paradigm. More effective treatment strategies, including those that combine systemic therapy with locoregional therapies like radioembolization or hepatic artery infusion, have also been developed. Molecular therapies, including those that target fibroblast growth factor receptor and isocitrate dehydrogenase, have recently received US Food and Drug Administration approval for a defined role as second-line treatment for up to 40% of patients harboring these actionable genomic alterations, and whether they should be considered in the first-line setting is under investigation. Furthermore, as the oncology field seeks to expand indications for immunotherapy, recent data demonstrated that combining durvalumab with standard cytotoxic therapy improved survival in patients with ICC. This review focuses on the current and future strategies for ICC treatment, including a summary of the primary literature for each treatment modality and an algorithm that can be used to drive a personalized and multidisciplinary approach for patients with this challenging malignancy.
Hydra: An Ensemble of Convolutional Neural Networks for Geospatial Land Classification

In this paper, we describe Hydra, an ensemble of convolutional neural networks (CNNs) for geospatial land classification. The idea behind Hydra is to create an initial CNN that is coarsely optimized but provides a good starting pointing for further optimization, which will serve as the Hydra's body. Then, the obtained weights are fine-tuned multiple times with different augmentation techniques, crop styles, and classes weights to form an ensemble of CNNs that represent the Hydra's heads. By doing so, we prompt convergence to different endpoints, which is a desirable aspect for ensembles. With this framework, we were able to reduce the training time while maintaining the classification performance of the ensemble. We created ensembles for our experiments using two state-of-the-art CNN architectures, residual network (ResNet), and dense convolutional networks (DenseNet). We have demonstrated the application of our Hydra framework in two data sets, functional map of world (FMOW) and NWPU-RESISC45, achieving results comparable to the state-of-the-art for the former and the best-reported performance so far for the latter. Code and CNN models are available at https://github.com/maups/hydra-fmow.
HPV-16 E7 Interacts with the Endocytic Machinery via the AP2 Adaptor μ2 Subunit

Human papillomavirus (HPV) E7 plays a major role in HPV-induced malignancy, perturbing cell cycle regulation, and driving cell proliferation. Major targets of cancer-causing HPV E7 proteins are the pRB family of tumor suppressors, which E7 targets for proteasome-mediated degradation and whose interaction is promoted through an acidic patch, downstream of the LXCXE motif in E7, that is subject to phosphorylation by casein kinase II (CKII). In this study we show that HPV-16 E7 targets the AP2-complex, which plays a critical role in cargo recognition in clathrin-mediated endocytosis. Intriguingly, HPV-16 E7 contains a specific amino acid sequence for AP2 recognition, and this overlaps the pRb LXCXE recognition sequence but involves completely different amino acid residues. HPV-16 E7 does this by binding to the AP2-μ2 adaptor protein subunit via residues 25-YEQL-28 within the LXCXE motif. Point mutations at Y25 within 22-LYCYE-26 suggest that the interaction of E7 with AP2-μ2 is independent from pRB binding. In cells, this interaction is modulated by acidic residues downstream of LXCXE, with the binding being facilitated by CKII-phosphorylation of the serines at positions 31 and 32. Finally, we also show that association of HPV-16 E7 with the AP2 adaptor complex can contribute to cellular transformation under low-nutrient conditions, which appears to be mediated, in part, through inhibition of AP2-mediated internalization of epidermal growth factor receptor (EGFR). This indicates that E7 can modulate endocytic transport pathways, with one such component, EGFR, most likely contributing toward the ability of E7 to induce cell transformation and malignancy. These studies define a new and unexpected role for HPV-16 E7 in targeting clathrin-mediated endocytosis. IMPORTANCE Despite being a very small protein, HPV-E7 has a wide range of functions within the infected cell, many of which can lead to cell transformation. High-risk HPV-E7 deregulates the function of many cellular proteins, perturbing cellular homeostasis. We show that a novel target of HPV-E7 is the clathrin-adaptor protein 2 complex (AP2) μ2 subunit, interacting via residues within E7's pRB-binding region. Mutational studies show that an AP2 recognition motif is present in the CR2 region and is conserved in >50 HPV types, suggesting a common function for this motif in HPV biology. Mutational analysis suggests that this motif is important for cellular transformation, potentially modulating endocytosis of growth factor receptors such as EGFR, and thus being a novel activity of E7 in modulating clathrin-mediated endocytosis and cargo selection. This study has important implications for the molecular basis of E7 function in modulating protein trafficking at the cell surface.
The state of the art in the 1990's: NCRP Report No. 136 on the scientific bases for linearity in the dose-response relationship for ionizing radiation

To reassess the use of the linear-nonthreshold dose-response model in the light of advancing knowledge, the National Council on Radiation Protection and Measurements formed Scientific Committee 1-6 and charged it to evaluate the evidence for and against the linear-nonthreshold dose-response hypothesis without reference to any associated policy ramifications. To accomplish this task, the Committee reviewed the relevant theoretical, experimental, and epidemiological data on those effects of ionizing radiation that are generally postulated to be stochastic in nature (i.e., genetic and carcinogenic effects). From its review of the data, the Committee concluded that the weight of evidence suggests that lesions that are precursors to cancer (i.e., mutations and chromosome aberrations), and certain types of cancer as well, may increase in frequency linearly with the dose in the low-dose domain. On this basis, the Committee concluded that no alternative dose-response model is more plausible than the linear-nonthreshold model although other dose-response relationships cannot be excluded, especially in view of growing evidence that the dose-response relationship may be modified by adaptive responses, bystander effects, and other variables.
Deep Compartment Syndrome Without Myonecrosis: A Case Report on a Rare Complication of Sickle Cell Disease

Compartment syndrome is a rare manifestation of vaso-occlusive crisis, a serious complication of sickle cell disease (SCD), which is an inherited hemoglobinopathy. During a visit to Norway, an otherwise healthy, 20-year-old male from Ghana was admitted to Oslo University Hospital (Day 1) because of increasing pain in the hip and thighs that did not respond adequately to non-opioid painkillers. Despite initial treatment with intravenous fluids and opioids, his pain intensified. Careful clinical inspection supported by an MRI examination revealed focal, high-signal-intensity muscle edema of the anterior compartment of the thigh, almost exclusively limited to the vastus intermedius muscles. There were no MRI findings or blood biochemistry evidence for myonecrosis or rhabdomyolysis, and a diagnosis of deep compartment syndrome appeared to be the most likely explanation for his pain. We decided to continue with a conservative treatment approach, and the patient did not undergo a fasciotomy or blood transfusion therapy. On Day 7 after admission, his condition improved markedly, and he was discharged on Day 11 whereupon he returned to Ghana. This case is a reminder that, although rare, deep compartment syndrome can be a severe manifestation of vaso-occlusive crisis in SCD and should be considered in patients with severe, deep muscular pain in the absence of other explanatory factors.
Multimodal medical image fusion using non-subsampled shearlet transform and pulse coupled neural network incorporated with morphological gradient

This research proposes a novel fusion scheme for non-subsampled shearlet transform (NSST) which is based on simplified model of pulse coupled neural network (PCNN). The images to be fused are acquired from Postgraduate Institute of Medical Education and Research, Chandigarh, India, and internet repository. The image database contains computed tomography and T2-weighted magnetic resonance images. The images to be fused are decomposed into approximation and detail sub-bands using NSST. The regional energy-based activity measure with consistency verification is applied to fuse the approximation sub-band of NSST. The novel morphological gradient of detail sub-bands is fed as external stimulus to PCNN to fuse detail sub-bands. The proposed method is compared with five state-of-the-art fusion schemes visually and using five fusion performance parameters. It is observed that the resultant images of the proposed fusion scheme show appropriate fusion characteristics and retain the bone, CSF and edema details in the clinical format required for disease evaluation by the radiologists. The proposed scheme requires lesser computational time than other state-of-the-art PCNN-based fusion schemes.
Optimized Block-Based Connected Components Labeling With Decision Trees

In this paper, we define a new paradigm for eight-connection labeling, which employes a general approach to improve neighborhood exploration and minimizes the number of memory accesses. First, we exploit and extend the decision table formalism introducing OR-decision tables, in which multiple alternative actions are managed. An automatic procedure to synthesize the optimal decision tree from the decision table is used, providing the most effective conditions evaluation order. Second, we propose a new scanning technique that moves on a 2 x 2 pixel grid over the image, which is optimized by the automatically generated decision tree. An extensive comparison with the state of art approaches is proposed, both on synthetic and real datasets. The synthetic dataset is composed of different sizes and densities random images, while the real datasets are an artistic image analysis dataset, a document analysis dataset for text detection and recognition, and finally a standard resolution dataset for picture segmentation tasks. The algorithm provides an impressive speedup over the state of the art algorithms.
Fast and accurate light field saliency detection through deep encoding

Light field saliency detection - important due to utility in many vision tasks - still lacks speed and can improve in accuracy. Due to the formulation of the saliency detection problem in light fields as a segmentation task or a memorizing task, existing approaches consume unnecessarily large amounts of computational resources for training, and have longer execution times for testing. We solve this by aggressively reducing the large light field images to a much smaller three-channel feature map appropriate for saliency detection using an RGB image saliency detector with attention mechanisms. We achieve this by introducing a novel convolutional neural network based features extraction and encoding module. Our saliency detector takes 0.4 s to process a light field of size 9 x 9 x 512 x 375 in a CPU and is significantly faster than state-of-the-art light field saliency detectors, with better or comparable accuracy. Furthermore, model size of our architecture is significantly lower compared to state-of-the-art light field saliency detectors. Our work shows that extracting features from light fields through aggressive size reduction and the attention mechanism results in a faster and accurate light field saliency detector leading to near real-time light field processing.
Environmental impacts and benefits of state-of-the-art technologies for E-waste management

This study aims to evaluate the environmental impacts and benefits of state-of-the-art technologies for proper e-waste handling using Jordan as a case study. Life Cycle Assessment (LCA) was employed to evaluate five advanced management systems represent staterof-the-art treatment technologies, including sanitary landfilling; proper recycling of metals, materials, and precious metals (PMs); and incineration of plastic and the hazardous portion of printed circuit boards (PCBs). Six e-waste products that contribute the most to the e-waste in Jordan were included in the assessment of each scenario, which resulted in 30 total cases of e-waste management. The findings indicated that landfills for the entire components of the e-waste stream are the worst option and should be avoided. The most promising e-waste management scenario features integrated e-waste processes based on the concept of Integrated Waste Management (IWM), including recycling materials such as non-PMs and PMs, incinerating plastic and the hazardous content of PCBs using the energy recovered from incineration, and using sanitary landfills of residues. For this scenario, the best environmental performance was obtained for the treatment of mobile phones. Incineration of the portion of hazardous waste using energy recovery is an option that deserves attention. Because scenario implementation depends on more than just the environmental benefits (e.g., economic cost and technical aspects), the study proposes a systematic approach founded on the IWM concept for e-waste management scenario selection. (C) 2017 Elsevier Ltd. All rights reserved.
A 1.5-pJ/bit, 9.04-Mbit/s Carrier-Width Demodulator for Data Transmission Over an Inductive Link Supporting Power and Data Transfer

This brief relates to a novel approach for downlink data transmission based on a carrier-width modulation (CWM). This modulation technique offers high performances and allows simultaneous data and power transmission over a single 27.12-MHz inductive link. A CWM demodulator is designed and fabricated in 130-nm CMOS technology. The proposed demodulator is intended for implantable medical devices, but can be applicable to other wireless systems. Excellent measurement results are obtained in comparison with state-of-the-art demodulators used in inductive communication systems. The proposed demodulator that was designed, fabricated, and tested provides high data rates at an ultra-low power budget and a very small silicon area of 2100 mu m(2). More specifically, a data rate of 9.04 Mb/s can be achieved at a cost of only 13.68 mu W power consumption. This represents an energy efficiency of 1.5 pJ/bit, which is 8 times smaller than the best state-of-the-art competitive demodulator.
The Effect of Destination Brand Identity on Tourism Experience: The Case of the Pier-2 Art Center in Taiwan

This paper examines the tourism destination brand identity and brand experiences which can influence visitors' intention to recommend. The study of the importance of destination brand identity and brand experiences in the context of Taiwan has shaped some important insights with the potential to enhance the attractiveness of cultural and creative sectors. In this study, this paper explores perceptions of destination brand identity (tourism brand perception and tourism brand self-concept) and brand experiences. The analysis draws upon data collected at the Pier-2 Art Center in Taiwan in 2019, using a self-administrated questionnaire survey. Both confirmatory factor analysis (CFA) and structural equation modeling (SEM) were applied. It has been found that the role of various constructs of a brand perception and a brand self-concept of the tourism brand identity during a visit to cultural and creative parks is on top of the list of concerns associated with visitors' brand experience. An examination of the research comments concluded that the cultural and creative tourism sector about consumer demands and update the development of appropriate marketing strategies, thereby providing visitors to experience the brand characteristics within the creative arts sector.
[Penile glans amputation during non-hospital circumcision: about two cases]

Penile glans amputation during circumcision is a tragic operator-related complication. Standard treatment is based on microsurgical reimplantation with vascular and nerve anastomosis. We here report two cases of penile glans amputation in two children. The first patient was aged five years and was admitted urgently after circumcision. Penile glans was reimplanted without microsurgical anastomosis within one hour of the date of the accident. The other patient was aged 11 years and was received 3 years of the date of the accident. During these three years he had received psychological therapy. He was scheduled for plastic surgery. In the first patient, urinary, sensitivity and cosmetic results of the glans were good as well as erectile function.
Integration of transcriptomic and metabolomic analyses provides insights into response mechanisms to nitrogen and phosphorus deficiencies in soybean

Nitrogen (N) and phosphorus (P) are two essential plant macronutrients that can limit plant growth by different mechanisms. We aimed to shed light on how soybean respond to low nitrogen (LN), low phosphorus (LP) and their combined deficiency (LNP). Generally, these conditions triggered changes in gene expression of the same processes, including cell wall organization, defense response, response to oxidative stress, and photosynthesis, however, response was different in each condition. A typical primary response to LN and LP was detected also in soybean, i.e., the enhanced uptake of N and P, respectively, by upregulation of genes for the corresponding transporters. The regulation of genes involved in cell wall organization showed that in LP roots tended to produce more casparian strip, in LN more secondary wall biosynthesis occurred, and in LNP reduction in expression of genes involved in secondary wall production accompanied by cell wall loosening was observed. Flavonoid biosynthesis also showed distinct pattern of regulation in different conditions: more anthocyanin production in LP, and more isoflavonoid production in LN and LNP, which we confirmed also on the metabolite level. Interestingly, in soybean the nutrient deficiencies reduced defense response by lowering expression of genes involved in defense response, suggesting a role of N and P nutrition in plant disease resistance. In conclusion, we provide detailed information on how LN, LP, and LNP affect different processes in soybean roots on the molecular and physiological levels.
Enhancement of SSVEPs Classification in BCI-Based Wearable Instrumentation Through Machine Learning Techniques

This work addresses the adoption of Machine Learning classifiers and Convolutional Neural Networks to improve the performance of highly wearable, single-channel instrumentation for Brain-Computer Interfaces. The proposed measurement system is based on the classification of Steady-State Visually Evoked Potentials (SSVEPs). In particular, Head-Mounted Displays for Augmented Reality are used to generate and display the flickering stimuli for the SSVEPs elicitation. Four experiments were conducted by employing, in turn, a different Head-Mounted Display. For each experiment, two different algorithms were applied and compared with the state-of-the-art-techniques. Furthermore, the impact of different Augmented Reality technologies in the elicitation and classification of SSVEPs was also explored. The experimental metrological characterization demonstrates (i) that the proposed Machine Learning-based processing strategies provide a significant enhancement of the SSVEP classification accuracy with respect to the state of the art, and (ii) that choosing an adequate Head-Mounted Display is crucial to obtain acceptable performance. Finally, it is also shown that the adoption of inter-subjective validation strategies such as the Leave-One-Subject-Out Cross Validation successfully leads to an increase in the inter-individual 1-sigma reproducibility: this, in turn, anticipates an easier development of ready-to-use systems.
Towards the Sustainable Development of Young Children: Impact of After-School Tutoring on Chinese Preschoolers' Social Behavior

This study aimed to examine whether participation in more types of after-school tutoring for 3- to 6-year-old preschool children is more beneficial to their social behavior. The study was based on survey data collected from 823 children aged between 3 and 6 years in Beijing City, the Guangdong Province and the Jiangxi province, China. Binary logistic regression and hierarchical multiple regression results revealed that: (1) gender, age, and family socioeconomic status were important factors that affected whether preschool children participated in after-school tutoring; (2) in terms of the types of after-school tutoring, participation in the arts and health-related activities was beneficial to the development of children's social skills, participation in arts and science ameliorated children's problem behavior, but participation in arts, science, and health-related activities simultaneously posed a negative impact on children's problem behavior; (3) in terms of the breadth of participation, children's social skills were weakly strengthened if the participation breadth is greater, but this, however, did not reduce problem behavior; (4) parental involvement and individual factors were important in determining children's social behavior. Based on the findings of this study, we suggest that parents should carefully consider the impact of after-school tutoring on preschool children's social behavior and choose after-school tutoring appropriately.