ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Lenvatinib rechallenge in a patient with advanced thymic carcinoma: A case report

Advanced thymic carcinomas have limited treatment options. Recently, lenvatinib was approved for advanced thymic carcinoma treatment. However, the clinical benefit of lenvatinib re-administration in patients with advanced thymic carcinoma who developed prior lenvatinib treatment resistance (lenvatinib rechallenge) remains unclear. Here, we present a case treated with lenvatinib rechallenge for advanced thymic carcinoma who was previously treated with lenvatinib as the second-line treatment followed by multiple cytotoxic agents. Disease control rapidly deteriorated after the eighth line of treatment because of uncontrollable right pleural and pericardial effusion, which required repeated thoracic and pericardial drainage. Shortly after lenvatinib re-administration, rapid pleural and pericardial effusion reduction was observed. Thereafter, the patient achieved sustained clinical response with good pleural and pericardial effusion control for approximately 7 months. Our case might suggest lenvatinib rechallenge as a treatment option for patients with advanced thymic carcinoma, especially those with poor pleural and pericardial effusion control.
Dynamic Cross-Task Representation Adaptation for Clinical Targets Co-Segmentation in CT Image-Guided Post-Prostatectomy Radiotherapy

Adjuvant and salvage radiotherapy after radical prostatectomy requires precise delineations of prostate bed (PB), i.e., the clinical target volume, and surrounding organs at risk (OARs) to optimize radiotherapy planning. Segmenting PB is particularly challenging even for clinicians, e.g., from the planning computed tomography (CT) images, as it is an invisible/virtual target after the operative removal of the cancerous prostate gland. Very recently, a few deep learning-based methods have been proposed to automatically contour non-contrast PB by leveraging its spatial reliance on adjacent OARs (i.e., the bladder and rectum) with much more clear boundaries, mimicking the clinical workflow of experienced clinicians. Although achieving state-of-the-art results from both the clinical and technical aspects, these existing methods improperly ignore the gap between the hierarchical feature representations needed for segmenting those fundamentally different clinical targets (i.e., PB and OARs), which in turn limits their delineation accuracy. This paper proposes an asymmetric multi-task network integrating dynamic cross-task representation adaptation (i.e., DyAdapt) for accurate and efficient co-segmentation of PB and OARs in one-pass from CT images. In the learning-to-learn framework, the DyAdapt modules adaptively transfer the hierarchical feature representations from the source task of OARs segmentation to match up with the target (and more challenging) task of PB segmentation, conditioned on the dynamic inter-task associations learned from the learning states of the feed-forward path. On a real-patient dataset, our method led to state-of-the-art results of PB and OARs co-segmentation.
Martial Arts Tourism of the "Europe-Far East" Direction, in the Opinion of Grand Masters

Martial arts tourism is a form of cultural, sports and educational tourism that requires special recognition; particularly important is knowledge about martial arts. The sources of this practical knowledge are especially high-ranking masters. The scientific problem raised here involves the issue of high-ranking martial arts teachers taking trips for their own studies (to acquire knowledge and skills) and teaching others. Some of the questions addressed include how often the trips occur (single, sporadic, or multiple, regular), what their effects are, and what their meaning is-in the opinion of these experts. The "Martial Arts Tourism" questionnaire was addressed to N = 12 people, masters/teachers of high-rank in martial arts (level 7-10 dan/toan) who live and teach in Europe and the USA, but come from Europe. They are the holders of the highest degrees in Chinese, Japanese and Korean styles. Further questions were asked through direct correspondence. The collected statements were usedby means of qualitative analysis-as in the method of 'expert courts'/'competent judges'. The respondents in most cases undertook trips from Europe to East Asia for their own learning. They teach themselves mainly in their own countries and in Europe. Stays rarely lasted over two weeks. The respondents are convinced of the legitimacy of this type of trip, and believe that the trips are very helpful on the way to mastery. None of the respondents mentioned the material forms of cultural heritage pertaining to martial arts as motives for the trips. Therefore, the ability to visit historic places is a marginal concern. The trips were directly linked to a career path and self-improvement in martial arts, learning or teaching.
Rasiella rasia gen. nov. sp. nov. within the family Flavobacteriaceae isolated from seawater recirculating aquaculture system

A novel bacterium designated RR4-40T was isolated from a biofilter of seawater recirculating aquaculture system in Busan, South Korea. Cells are strictly aerobic, Gram-negative, irregular short rod, non-motile, and oxidase- and catalase-negative. Growth was observed at 15-30°C, 0.5-6% NaCl (w/v), and pH 5.0-9.5. The strain grew optimally at 28°C, 3% salinity (w/v), and pH 8.5. The phylogenetic analysis based on 16S rRNA gene sequences showed that strain RR4-40T was most closely related to Marinirhabdus gelatinilytica NH83T (94.16% of 16S rRNA gene similarity) and formed a cluster with genera within the family Flavobacteriaceae. The values of the average nucleotide identity (ANI), digital DNA-DNA hybridization (dDDH), and average amino acid identity (AAI) between genomes of strain RR4-40T and M. gelatinilytica NH83T were 72.91, 18.2, and 76.84%, respectively, and the values against the strains in the other genera were lower than those. The major fatty acids were iso-C15:0 (31.34%), iso-C17:0 3-OH (13.65%), iso-C16:0 3-OH (10.61%), and iso-C15:1 G (10.38%). The polar lipids comprised phosphatidylglycerol, diphosphatidylglycerol, aminophospholipid, aminolipid, glycolipid, and sphingolipid. The major respiratory quinone was menaquinone-6 (MK-6) and the DNA G + C content of strain RR4-40T was 37.4 mol%. According to the polyphasic analysis, strain RR4-40T is considered to represent a novel genus within the family Flavobacteriaceae, for which the name Rasiella rasia gen. nov, sp. nov. is proposed. The type strain is RR4-40T (= KCTC 52650T = MCCC 1K04210T).
An efficient biosorbent for the removal of arsenic from a typical urban-generated wastewater

The arousal of environmental concerns due to spike in environmental degradation has necessitated proper waste management and disposal. Arsenic, a potentially toxic element in cassava wastewater, requires treatment prior to the wastewater disposal to minimize environmental pollution and associated health implications. The present study thus addressed the treatment of As5+ heavy metal in cassava wastewater using an efficient biosorbent from chemically pretreated unshelled Moringa oleifera seeds. The effect of various factors influencing the biosorption process for arsenate removal was studied including pH, contact time, biosorbent dosage, and biosorbent pretreatment concentration. The results of Fourier transform infrared spectroscopy clearly suggested that additional functional groups attributed to esters were formed in the pretreated biosorbent, which is responsible for improvement in biosorption. It was found that contact time, biosorbent dosage, and biosorbent pretreatment concentration had statistically significant effect (p values < 0.05) on arsenate removal. A maximum percentage removal of 99.9% was achieved in the synthetic solution at pH 4.0, contact time of 30 min, and dosage of 2 g for biosorbent pretreated with 1 M of chemical solution. Furthermore, through isotherm and kinetics studies, it was discovered that the biosorption process for untreated biosorbent is by ion exchange, while that for treated biosorbents indicated a multifarious adsorption mechanism. Moreover, the biosorption process was exothermic and spontaneous. Also, it is noted that the sorption capability of the biosorbent increases with pretreatment concentration. A statistical model has been developed with prediction R2 of 0.898, which incorporates the effect of treatment concentration on the percentage removal of As5+ from cassava wastewater.
No-Reference JPEG Image Quality Assessment Based on Blockiness and Luminance Change

When scoring the quality of JPEG images, the two main considerations for viewers are blocking artifacts and improper luminance changes, such as blur. In this letter, we first propose two measures to estimate the blockiness and the luminance change within individual blocks. Then, a no-reference image quality assessment (NR-IQA) method for JPEG images is proposed. Our method obtains the quality score by considering the blocking artifacts and the luminance changes from all nonoverlapping 8 x 8 blocks in one JPEG image. The proposed method has been tested on five public IQA databases and compared with five state-of-the-art NR-IQA methods for JPEG images. The experimental results show that our method is more consistent with subjective evaluations than the state-of-the-art NR-IQA methods. The MATLAB source code of our method is available at http://image.ustc.edu.cn/IQA.html.
Inferring Optimal Species Trees in the Presence of Gene Duplication and Loss: Beyond Rooted Gene Trees

Estimating species trees from multiple genes is complicated and challenging due to gene tree-species tree discordance. One of the basic approaches to understanding differences between gene trees and species trees is gene duplication and loss events. Minimize Gene Duplication and Loss (MGDL) is a popular technique for inferring species trees from gene trees when the gene trees are discordant due to gene duplications and losses. Previously, exact algorithms for estimating species trees from rooted, binary trees under MGDL were proposed. However, gene trees are usually estimated using time-reversible mutation models, which result in unrooted trees. In this article, we propose a dynamic programming (DP) algorithm that can be used for an exact but exponential time solution for the case when gene trees are not rooted. We also show that a constrained version of this problem can be solved by this DP algorithm in time that is polynomial in the number of gene trees and taxa. We have proved important structural properties that allow us to extend the algorithms for rooted gene trees to unrooted gene trees. We propose a linear time algorithm for finding the optimal rooted version of an unrooted gene tree given a rooted species tree so that the duplication and loss cost is minimized. Moreover, we prove that the optimal rooting under MGDL is also optimal under the MDC (minimize deep coalescence) criterion. The proposed methods can be applied to both orthologous genes and gene families that by definition include both paralogs and orthologs. Therefore, we hope that these techniques will be useful for estimating species trees from genes sampled throughout the whole genome.
ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation

Semantic segmentation is a challenging task that addresses most of the perception needs of intelligent vehicles (IVs) in an unified way. Deep neural networks excel at this task, as they can be trained end-to-end to accurately classify multiple object categories in an image at pixel level. However, a good tradeoff between high quality and computational resources is yet not present in the state-of-the-art semantic segmentation approaches, limiting their application in real vehicles. In this paper, we propose a deep architecture that is able to run in real time while providing accurate semantic segmentation. The core of our architecture is a novel layer that uses residual connections and factorized convolutions in order to remain efficient while retaining remarkable accuracy. Our approach is able to run at over 83 FPS in a single Titan X, and 7 FPS in a Jetson TX1 (embedded device). A comprehensive set of experiments on the publicly available Cityscapes data set demonstrates that our system achieves an accuracy that is similar to the state of the art, while being orders of magnitude faster to compute than other architectures that achieve top precision. The resulting tradeoff makes our model an ideal approach for scene understanding in IV applications. The code is publicly available at: https://github.com/Eromera/erfnet
Highly chlorinated toxic contaminants in pesticide-treated wooden art objects

Although the contamination of wooden art objects with pesticides is well known, to the authors' knowledge Do attempt has yet been made to investigate the eventual presence of other toxic compounds that have been produced during the degradation of pesticides or that may be present in the technical formulations. Here, the authors report on the presence of polychlorinated biphenyls (PCBs) and polychlorinated terphenyls (PCTs) in scrapings from wooden antique art objects, namely printing blocks, sculptures, and masks. These antiques belong to 2 fine art museums in Belgium-Antwerp's Ethnographic Museum and the Plantin-Moretus Museum. It is documented that these art objects were treated with pesticides in the 1950s. In addition, 2-heptachlorodibenzo-p-dioxin (HpCDD) isomers and octachlorodibenzo-p-dioxin (OCDD) were also identified. The presence of these toxic compounds in these antiques requires a better understanding of safety for the persons (conservators, museum employees, restorers, and visitors) coming in contact with these objects.
MADET: a Manually Curated Knowledge Base for Microbiomic Effects on Efficacy and Toxicity of Anticancer Treatments

A plethora of studies have reported the associations between microbiota and multiple diseases, leading to the development of at least four databases to demonstrate microbiota-disease associations, i.e., gutMDisorder, mBodyMap, Gmrepo, and Amadis. Moreover, gut microbiota mediates drug efficacy and toxicity, whereas a comprehensive database to elucidate the microbiota-drug associations is lacking. Here, we report an open-access knowledge base, MADET (Microbiomics of Anticancer Drug Efficacy and Toxicity), which harbors 483 manually annotated microbiota-drug associations from 26 studies. MADET provides user-friendly functions allowing users to freely browse, search, and download data conveniently from the database. Users can customize their search filters in MADET using different types of keywords, including bacterial name (e.g., Akkermansia muciniphila), anticancer treatment (e.g., anti-PD-1 therapy), and cancer type (e.g., lung cancer) with different types of experimental evidence of microbiota-drug association and causation. We have also enabled user submission to further enrich the data documented in MADET. The MADET database is freely available at https://www.madet.info. We anticipate that MADET will serve as a useful resource for a better understanding of microbiota-drug associations and facilitate the future development of novel biomarkers and live biotherapeutic products for anticancer therapies. IMPORTANCE Human microbiota plays an important role in mediating drug efficacy and toxicity in anticancer treatment. In this work, we developed a comprehensive online database, which documents over 480 microbiota-drug associations manually curated from 26 research articles. Users can conveniently browse, search, and download the data from the database. Search filters can be customized using different types of keywords, including bacterial name (e.g., Akkermansia muciniphila), anticancer treatment (e.g., anti-PD-1 therapy), and cancer type (e.g., lung cancer), with different types of experimental evidence of microbiota-drug association. We anticipate that this database will serve as a convenient platform for facilitating research on microbiota-drug associations, including the development of novel biomarkers for predicting drug outcomes as well as novel live biotherapeutic products for improving the outcomes of anticancer drugs.
Structure-Aware Long Short-Term Memory Network for 3D Cephalometric Landmark Detection

Detecting 3D landmarks on cone-beam computed tomography (CBCT) is crucial to assessing and quantifying the anatomical abnormalities in 3D cephalometric analysis. However, the current methods are time-consuming and suffer from large biases in landmark localization, leading to unreliable diagnosis results. In this work, we propose a novel Structure-Aware Long Short-Term Memory framework (SA-LSTM) for efficient and accurate 3D landmark detection. To reduce the computational burden, SA-LSTM is designed in two stages. It first locates the coarse landmarks via heatmap regression on a down-sampled CBCT volume and then progressively refines landmarks by attentive offset regression using multi-resolution cropped patches. To boost accuracy, SA-LSTM captures global-local dependence among the cropping patches via self-attention. Specifically, a novel graph attention module implicitly encodes the landmark's global structure to rationalize the predicted position. Moreover, a novel attention-gated module recursively filters irrelevant local features and maintains high-confident local predictions for aggregating the final result. Experiments conducted on an in-house dataset and a public dataset show that our method outperforms state-of-the-art methods, achieving 1.64 mm and 2.37 mm average errors, respectively. Furthermore, our method is very efficient, taking only 0.5 seconds for inferring the whole CBCT volume of resolution 768 x 768 x 576.
4D printing - revolution or fad?

Purpose - This feature article aims to review state-of-the-art developments in additive manufacture, in particular, 4D printing. It discusses what it is, what research has been carried out and maps potential applications and its future impact. Design/methodology/approach - The article first defines additive manufacturing technologies and goes on to describe the state-of-the-art. Following which the paper examines several case studies and maps a trend that shows an emergence of 4D printing. Findings - The case studies highlight a particular specialization within additive manufacture where the use of adaptive, biomimetic composites can be programmed to reshape, or have embedded properties or functionality that transform themselves when subjected to external stimuli. Originality/value - This paper discusses the state-of-the-art of additive manufacture, discussing strategies that can be used to reduce the print process (such as through kinematics); and the use of smart materials where parts adapt themselves in response to the surrounding environment supporting the notion of self-assemblies.
Fertilizing ability and survivability of rooster sperm diluted with a novel semen extender supplemented with serine for practical use on smallholder farms

Semen extenders are essential for maintaining the quality of sperm during storage and assuring the success of fertility after insemination. The objective of this study was to examine the effect of a new rooster semen extender (hereinafter, NCAB) supplemented with serine on the survivability and fertilizing ability of sperm following storage. NaCl solution, the NCAB extender, and IGGKPh extender were used as treatments. In Experiment 1, different storage temperatures (5°C and 25°C) and durations of storage (0, 12, and 24 h) were used to compare the semen quality and determine the suitable storage temperature. The fertility test was performed in in-station tests and on-farm experimental trials in Experiments 2 and 3, respectively. The results indicated that the interaction effect of duration, treatment, and storage temperature on all sperm parameters was highly significant. The NCAB extender significantly improved rooster semen quality during storage for 24 h at 5°C (P < 0.01). The sperm diluted in saline solution could not survive 24 h of storage at 25°C. The fertility and hatchability rates obtained for sperm diluted with the NCAB extender were higher than those diluted with other extenders. In addition, the fertilizing capacity of the NCAB extender-diluted sperm under field conditions was significantly higher than that of the saline solution-treated sperm. In conclusion, the NCAB extender supplemented with serine and stored at a low temperature (5°C) positively affects sperm quality and fertilization.
Morphological markers of chromosomal instability in bone marrow aspiration and trephine biopsy of acute leukemia and myelodysplastic syndrome

The role of chromosomal instability (CI) in oncogenesis is very well described in solid tumours, but there are a lack of studies on haematology malignancy, especially with multiple morphological markers. The study aims to analyze seven morphological markers of CI- chromatin bridges (CB), multipolar mitosis (MPM), nuclear budding (NB), micronuclei (MN), nuclear heterogeneity (NH), laggards, chromatin strings (CS) in bone marrow aspirate (BMA) and biopsy of acute leukaemia (AL), and myelodysplastic syndrome (MDS). It is a retrospective cross-sectional analytical study where BMA and biopsy were reviewed for CI markers. We compared CI markers in five categories. CI markers were further correlated with clinical manifestations and outcomes of patients. The study included 54 samples of 37 patients. Overall, the median (IQR) of markers were as follows: MN 3.5 (1,7), NB 5 (1,18), MPM 1 (0,4), CB 1(0,2), Laggards 0 (0,1), and CS 2.5 (0,6). NH was noted in 65.4% of samples. All CI markers except laggards were significantly increased in B-ALL, AML, and MDS compared to other categories. Many CI markers were significantly raised with a few clinical features. The MN, MPM, Laggard, and NH markers were significantly increased in the dead patients compared to those who survived. The study, one of the first to analyze multiple CI markers, revealed that the CI markers were significantly increased in AL and MDS patients and significantly associated with clinical manifestations and outcomes. Morphology markers of CI are valuable and cost-effective in diagnostic strategy, type of malignancies, and assessing prognosis.
Uniform Color Space-Based High Dynamic Range Video Compression

Recently, there has been a significant progress in the research and development of the high dynamic range (HDR) video technology and the state-of-the-art video pipelines are able to offer a higher bit depth support to capture, store, encode, and display HDR video content. In this paper, we introduce a novel HDR video compression algorithm, which uses a perceptually uniform color opponent space, a novel perceptual transfer function to encode the dynamic range of the scene, and a novel error minimization scheme for accurate chroma reproduction. The proposed algorithm was objectively and subjectively evaluated against four state-of-the-art algorithms. The objective evaluation was conducted across a set of 39 HDR video sequences, using the latest x265 10-bit video codec along with several perceptual and structural quality assessment metrics at 11 different quality levels. Furthermore, a rating-based subjective evaluation (n = 40) was conducted with six sequences at two different output bitrates. Results suggest that the proposed algorithm exhibits the lowest coding error amongst the five algorithms evaluated. Additionally, the rate-distortion characteristics suggest that the proposed algorithm outperforms the existing state-of-the-art at bitrates >= 0.4 bits/pixel.