ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
miRNome-transcriptome analysis unveils the key regulatory pathways involved in the tumorigenesis of tongue squamous cell carcinoma

Tongue squamous cell carcinoma (TSCC) is considered the most common malignant tumor among the oral squamous cell carcinomas with a poor prognosis. Understanding the underlying molecular mechanisms that underpin TSCC and its treatments is the focus of the research. Deregulated expression of microRNAs (miRNAs) has recently been implicated in various biological processes linked to cancer. Therefore, in this study, we attempted to investigate miRNAs and their targets expressed in TSCC, which could be involved in its oncogenesis. We performed next-generation sequencing of small RNAs and transcriptomes in H357 TSCC cell line and human oral keratinocytes as a control to find miRNAs and mRNAs that are differentially expressed (DE), which were then supplemented with additional expression datasets from databases, yielding 269 DE miRNAs and 2094 DE genes. The target prediction followed by pathway and disease function analysis revealed that the DE targets were significantly associated with the key processes and pathways, such as apoptosis, epithelial-mesenchymal transition, endocytosis and vascular endothelial growth factor signaling pathways. Furthermore, the top 12 DE targets were chosen based on their involvement in more than one cancer-related pathway, of which 6 genes are targeted by miR-128-3p. Real-time quantitative PCR validation of this miRNA and its targets in H357 and SCC9 TSCC cells confirmed their possible targeting from their reciprocal expression, with MAP2K7 being a critical target that might be involved in oncogenesis and progression of TSCC by acting as a tumor suppressor. Further research is underway to understand how miR-128-3p regulates oncogenesis in TSCC via MAP2K7 and associated pathways.
The Impact of Cache and Dynamic Memory Management in Static Dataflow Applications

Dataflow is a parallel and generic model of computation that is agnostic of the underlying multi/many-core architecture executing it. State-of-the-art frameworks allow fast development of dataflow applications providing memory, communicating, and computing optimizations by design time exploration. However, the frameworks usually do not consider cache memory behavior when generating code. A generally accepted idea is that bigger and multi-level caches improve the performance of applications. This work evaluates such a hypothesis in a broad experiment campaign adopting different multi-core configurations related to the number of cores and cache parameters (size, sharing, controllers). The results show that bigger is not always better, and the foreseen future of more cores and bigger caches do not guarantee software-free better performance for dataflow applications. Additionally, this work investigates the adoption of two memory management strategies for dataflow applications: Copy-on-Write (CoW) and Non-Temporal Memory transfers (NTM). Experimental results addressing state-of-the-art applications show that NTM and CoW can contribute to reduce the execution time to -5.3% and -15.8%, respectively. CoW, specifically, shows improvements up to -21.8% in energy consumption with -16.8% of average among 22 different cache configurations.
Does the concept of "ultra-processed foods" help inform dietary guidelines, beyond conventional classification systems? Debate consensus

The participants in this debate agree that food processing vitally affects human health, and that the extent of food processing significantly affects diet quality and health outcomes. They disagree on the significance of ultra-processing, as defined within the Nova food classification system. The YES position holds that the concept is well-founded, clear, and supported by a wealth of investigations, as demonstrated by systematic association between ultra-processed food (UPF) intake and various diseases and disorders, and the persistence of these associations with control for critical nutrients. The NO position argues that the concept of UPF is poorly defined; gives rise to misclassification of foods; is without clear mechanisms of action; and that the observed associations with obesity are likely confounded. The YES position argues that the Nova system is therefore crucial to inform dietary guidelines and also public policies designed to reduce production and consumption of UPFs, whereas the NO position argues that the system adds no value to conventional nutrient metrics and existing nutrient profiling systems, pointing instead to the need to develop an evidence-based system to characterize obesogenic foods.
Hematopoietic Stem and Progenitor Cell Identification and Transplantation in Zebrafish

The zebrafish as a model organism is well known for its versatile genetics, rapid development, and straightforward live imaging. It is an excellent model to study hematopoiesis because of its highly conserved ontogeny and gene regulatory networks. Recently developed highly specific transgenic reporter lines have allowed direct imaging and tracking of hematopoietic stem and progenitor cells (HSPCs) in live zebrafish. These reporter lines can also be used for fluorescence-activated cell sorting (FACS) of HSPCs. Similar to mammalian models, HSPCs can be transplanted to reconstitute the entire hematopoietic system of zebrafish recipients. However, the zebrafish provides unique advantages to study HSPC biology, such as transplants into embryos and high-throughput chemical screening. This chapter will outline the methods needed to identify, isolate, and transplant HSPCs in zebrafish.
Molecular Epidemiology of Methicillin-Resistant Staphylococcus aureus in a Tertiary Hospital from the Comunidad Valenciana (Spain)

To reduce the high rates of morbidity and mortality caused by methicillin-resistant Staphylococcus aureus (MRSA) strains, it is essential to prevent their transmission. This can be achieved through molecular surveillance of the infecting strains, for which the detection of the entry of new strains, the analysis of antimicrobial resistance, and their containment are essential. In this study, we have analyzed 190 MRSA isolates obtained at the Consorcio Hospital General Universitario de Valencia (Spain) from 2013 to 2018 with three approaches: Multilocus Sequence Typing, spa, and SCCmec typing. Although the incidence of S. aureus infections detected in the hospital increased in the study period, the frequency of MRSA isolates decreased from 33% to 18%. One hundred seventy-two MRSA isolates were resistant to three or more classes of antimicrobials, especially to fluoroquinolones. No relevant temporal trend in the distribution of antibiotic susceptibility was observed. The combination of the three typing schemes allowed the identification of 74 different clones, of which the combination ST125-t067-IV was the most abundant in the study (27 cases). Members of three clonal complexes, CC5, CC8, and CC22, comprised 91% of the isolates, and included 32 STs and 32 spa types. The emergence of low incidence strains throughout the study period and a large number of isolates resistant to different classes of antibiotics shows the need for epidemiological surveillance of this pathogen. Our study demonstrates that epidemiological and molecular surveillance is a powerful tool to detect the emergence of clinically important MRSA clones.
Method development for the determination of seven ginsenosides in three Panax ginseng reference materials via liquid chromatography with tandem mass spectrometry

A new liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed for the analysis of ginsenosides in three Panax ginseng reference materials (RMs). Extraction procedures were optimized to recover neutral and malonyl-ginsenosides using a methanol-water extraction under basic conditions. Optimized mass fragmentation transitions were obtained for the development of a multiple reaction monitoring (MRM) detection method with electrospray ionization in negative and positive ion mode. Mass fraction values were determined for ginsenosides Rb1, Rb2, Rc, Rd, Re, Rf, and Rg1 in the three ginseng materials (rhizomes, extract, and an oral dosage form). Quantitation of these seven compounds was accomplished with 4-methylestradiol and SRM 3389 Ginsenoside Calibration Solution serving as an internal standard (IS) and calibration standards, respectively. Mass fraction values for the seven ginsenosides ranged from 1.27 mg/g to 21.42 mg/g, 3.25 mg/g to 35.81 mg/g, and 0.56 mg/g to 2.51 mg/g for SRM 3384, SRM 3385, and RM 8664, respectively.
The influence of journal submission guidelines on authors' reporting of statistics and use of open research practices: Five years later

Changes in statistical practices and reporting have been documented by Giofrè et al. PLOS ONE 12(4), e0175583 (2017), who investigated ten statistical and open practices in two high-ranking journals (Psychological Science [PS] and Journal of Experimental Psychology-General [JEPG]): null hypothesis significance testing; confidence or credible intervals; meta-analysis of the results of multiple experiments; confidence interval interpretation; effect size interpretation; sample size determination; data exclusion; data availability; materials availability; and preregistered design and analysis plan. The investigation was based on an analysis of all papers published in these journals between 2013 and 2015. The aim of the present study was to follow up changes in both PS and JEPG in subsequent years, from 2016 to 2020, adding code availability as a further open practice. We found improvement in most practices, with some exceptions (i.e., confidence interval interpretation and meta-analysis). Despite these positive changes, our results indicate a need for further improvements in statistical practices and adoption of open practices.
Bag of words KAZE (BoWK) with two-step classification for high-resolution remote sensing images

The bag-of-words (BoW) model has been widely used for scene classification in recent state-of-the-art methods. However, inter-class similarity among scene categories and very high spatial resolution imagery makes its performance limited in the remote-sensing domain. Therefore, this research presents a new KAZE-based image descriptor that makes use of the BoW approach to substantially increase classification performance. Specifically, a novel multi-neighbourhood KAZE is proposed for small image patches. Secondly, the spatial pyramid matching and BoW representation can be adopted to use the extracted features and make an innovative BoW KAZE (BoWK) descriptor. Third, two bags of multi-neighbourhood KAZE features are selected in which each bag is regarded as separated feature descriptors. Next, canonical correlation analysis is introduced as a feature fusion strategy to further refine the BOWK features, which allows a more effective and robust fusion approach than the traditional feature fusion strategies. Experiments on three challenging remote-sensing data sets show that the proposed BoWK descriptor not only surpasses the conventional KAZE descriptor but also yields significantly higher classification performance than the state-of-the-art methods used now. Moreover, the proposed BoWK approach produces rich informative features to describe the scene images with low-computational cost and a much lower dimension.
Resistance to Multiple Insecticide Classes in the Vinegar Fly Drosophila melanogaster (Diptera: Drosophilidae) in Michigan Vineyards

Vinegar flies are vectors of pathogens causing fruit rots of grapes, so control of these insects is important for preventing vineyard yield loss. Recent outbreaks of sour rots may be linked to greater challenges controlling vinegar flies, so we investigated the insecticide susceptibility of populations collected from commercial vineyards across Michigan. We first determined the discriminating concentration for phosmet, malathion, methomyl, and zeta-cypermethrin using a laboratory susceptible (Canton-S) strain of D. melanogaster females. The discriminating concentrations were determined as 252.08, 2.58, 0.96, and 1.68 ppm of the four insecticides, respectively. These concentrations were first tested in 2020 against populations from the two major counties for grape production. In 2021, we expanded monitoring to twenty-three populations collected from vineyards across six counties. All populations had significantly lower sensitivity to all four insecticides compared with Canton-S strain, with up to 98.8% lower mortality for phosmet. The LC50, LC90, and LC99 values of the four insecticides for the two populations tested in 2020 were 7-1,157-fold higher than the Canton-S strain. For the twenty-three populations collected in 2021, mortality ranged from 56.3 to 100% when the flies were screened using a 10x concentration of the discriminating concentration of the insecticides, whereas it ranged from 82.4 to 100% when the flies were screened using a 20x concentration. Our results suggest variable levels of resistance to insecticides from multiple chemical classes in D. melanogaster populations in Michigan vineyards, highlighting the need to implement integrated sour rot management approaches that are less dependent on insecticides for control of this species.
Multifeature Landmark-Free Active Appearance Models: Application to Prostate MRI Segmentation

Active shape models (ASMs) and active appearance models (AAMs) are popular approaches for medical image segmentation that use shape information to drive the segmentation process. Both approaches rely on image derived landmarks (specified either manually or automatically) to define the object's shape, which require accurate triangulation and alignment. An alternative approach to modeling shape is the levelset representation, defined as a set of signed distances to the object's surface. In addition, using multiple image derived attributes (IDAs) such as gradient information has previously shown to offer improved segmentation results when applied to ASMs, yet little work has been done exploring IDAs in the context of AAMs. In this work, we present a novel AAM methodology that utilizes the levelset implementation to overcome the issues relating to specifying landmarks, and locates the object of interest in a new image using a registration based scheme. Additionally, the framework allows for incorporation of multiple IDAs. Our multifeature landmark-free AAM(MFLAAM) utilizes an efficient, intuitive, and accurate algorithm for identifying those IDAs that will offer the most accurate segmentations. In this paper, we evaluate our MFLAAM scheme for the problem of prostate segmentation from T2-w MRI volumes. On a cohort of 108 studies, the levelset MFLAAM yielded a mean Dice accuracy of 88% +/- 5%, and a mean surface error of 1.5 mm +/-.8 mm with a segmentation time of 150/s per volume. In comparison, a state of the art AAM yielded mean Dice and surface error values of 86% +/- 9% and 1.6 mm +/- 1.0 mm, respectively. The differences with respect to our levelset-basedMFLAAM model are statistically significant (p < .05). In addition, our results were in most cases superior to several recent state of the art prostate MRI segmentation methods.
Molecular phenotyping of malignant canine mammary tumours: Detection of high-risk group and its relationship with clinicomolecular characteristics

Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high-throughput technologies such as microarray and next-generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA-sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) (n = 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high-risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2-C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates (ps <.05). The high-risk subtype (C5) was further characterized through the development of a cell cycle-based gene signature, which comprised 37 proliferation-related genes according to the support vector machine algorithm. This signature identified the high-risk group in both training and validation datasets (ps <.001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.
Bio-surfaces and geometric references for mass customization in bio-interface design

Mass customization of products that interface with the human body poses unique problems due to the complexities of bio-interface design, the lack of biomechanical techniques in traditional mechanical design, and the absence of specific parametric strategies. Current biomechanical design often follows craftsman-like design processes using less than state-of-the-art tools and techniques. Thus, products that interface with the human body are not readily parameterized or automated. This paper presents a strategy for implementing mass customization in the design of mechanical devices that interface with the human body. This strategy is based on three methods that include: a method for capturing and representing the human body so that the model can be used with state-of-the-art tools and solid modeling techniques, a design methodology based on feature structure planning allowing the design process to be reused and automated, and a strategy for identifying parametric variables tied to the human body. A case study is presented to illustrate the proposed process.
Exploiting the Largest Available Zone: A Proactive Approach to Adaptive Random Testing by Exclusion

Adaptive random testing (ART) has been proposed to enhance the effectiveness of random testing (RT) through more even spreading of the test cases. In particular, restricted random testing (RRT) is an ART algorithm based on the intuition of skipping all the candidate test cases that are within the neighborhoods (or zones) of previously executed test cases. RRT has higher effectiveness than RT in terms of failure detection but incurs a higher time cost. In this paper, we aim to further reduce the time costs for RRT and improve the effectiveness for RT and ART methods. We propose a proactive technique known as & x201C;RRT by largest available zone & x201D; (RRT-LAZ). Like RRT, RRT-LAZ first defines an exclusion zone around every executed test case in order to determine the available zones. Unlike the original RRT, RRT-LAZ then compares all the available zones to proactively pick the largest one, from which the next test case is randomly generated. Both simulation analyses and empirical studies have been employed to investigate the efficiency and effectiveness of RRT-LAZ in relation to RT and related ART algorithms. The results show that RRT-LAZ has significantly lower time costs than RRT. Furthermore, RRT-LAZ is more effective than RT and related ART methods for block failure patterns in low-dimensional input spaces. In general, since RRT-LAZ employs a proactive technique instead of a passive one in generating next cases, it is much more cost-effective than RRT. RRT-LAZ is also more cost-effective than RT and other ART methods that we have studied.
A PID controller for synchronization between master-slave neurons in fractional-order of neocortical network model

Modeling of the biological neurons is a way to understand the architecture of neural networks of the brain. A complex brain network includes the synchronization between some groups of neurons. The dynamic behavior of interactions between groups of slave-master neurons in the neocortical network is unpredictable and challenging. The purpose of synchronizing a neural interaction is to reduce the synchronization error between the chaotic slave-master neurons. This paper uses a proportional-integral-derivative (PID) controller to synchronize master-slave neurons in the fractional-order of the neocortical network model based on dendritic spike frequency adaptation (DSFA) uncertainties and unknown disturbance effects. The purpose of this article is in two parts: First, we implemented the effect of previous states of the neuron conditions by fractional-order of the differential equations in the neocortical network model. Second, by synchronizing the FO neocortical master-slave model by PID controller, we investigated the connection strength of the complex network in chaotic point of view. The optimized PID coefficients and fractional-order were calculated using root mean square error (RMSE) criteria to control the membrane voltage synchronization. The chaotic behavior of the system was evaluated by numerical techniques such as attractor analysis and time series diagrams. The optimal RMSE value for master-slave neurons occurred at fractional-orders 0.89. It is shown that the synchronization of master-slave neurons improves over time, and eventually they are fully synchronized while the controller error is reduced.
Synthesis, Biochemical, and Cellular Evaluation of HDAC6 Targeting Proteolysis Targeting Chimeras

Histone deacetylases are considered promising epigenetic targets for chemical protein degradation due to their diverse roles in physiological cellular functions and in the diseased state. Proteolysis-targeting chimeras (PROTACs) are bifunctional molecules that hijack the cell's ubiquitin-proteasome system (UPS). One of the promising targets for this approach is histone deacetylase 6 (HDAC6), which is highly expressed in several types of cancers and is linked to the aggressiveness of tumors. In the present work, we describe the synthesis of HDAC6 targeting PROTACs based on previously synthesized benzohydroxamates selectively inhibiting HDAC6 and how to assess their activities in different biochemical in vitro assays and in cellular assays. HDAC inhibition was determined using fluorometric assays, while the degradation ability of the PROTACs was assessed using western blot analysis.
Wide/Multiband Linearization of TWTAs Using Predistortion

This paper discusses the state of the art in achieving wideband (>1 GHz) linearization of TWTAs. Multioctave bandwidth linearization has been achieved at frequencies from L- to Ka-band. The trades between using a single predistortion linearizer and multiband linearizers are discussed. The effect of harmonies (both even and odd-order-distortion products) and their correction for applications that cover more than an octave are considered.
Sound Coding Color to Improve Artwork Appreciation by People with Visual Impairments

The recent development of color coding in tactile pictograms helps people with visual impairments (PVI) appreciate the visual arts. The auditory sense, in conjunction with (or possibly as an alternative to) the tactile sense, would allow PVI to perceive colors in a way that would be difficult to achieve with just a tactile stimulus. Sound coding colors (SCCs) can replicate three characteristics of colors, i.e., hue, chroma, and value, by matching them with three characteristics of sound, i.e., timbre, intensity, and pitch. This paper examines relationships between sound (melody) and color mediated by tactile pattern color coding and provides sound coding for hue, chroma, and value to help PVI deepen their relationship with visual art. Our two proposed SCC sets use melody to improve upon most SCC sets currently in use by adding more colors (18 colors in 6 hues). User experience and identification tests were conducted with 12 visually impaired and 8 sighted adults, and the results suggest that the SCC sets were helpful for the participants.