ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
CgIκB3, the third novel inhibitor of NF-kappa B (IκB) protein, is involved in the immune defense of the Pacific oyster, Crassostrea gigas

Inhibitor of NF-κB (IκB), the important regulator of NF-κB/Rel signaling pathway, plays the crucial role in immune response of both vertebrates and invertebrates. Here, a novel homologue of IκB was cloned from Crassostrea gigas, and designated as CgIκB3. The complete CgIκB3 cDNA was 1282 bp in length, including a 942 bp open reading frame (ORF), a 51 bp 5' UTR and a 289 bp 3' UTR. The ORF encodes a putative protein of 313 amino acids with a predicted molecular weight of approximately 34.7 kDa. Sequence analysis reveals that CgIκB3 contains a conserved degradation motif but with only five ankyrin repeats. Neither a PEST domain nor a C-terminal casein kinase II phosphorylation site was identified through either alignment or bioinformatic prediction. Phylogenetic analysis suggested that CgIκB3 shares common ancestor with CgIκB1 rather CgIκB2, and theoretically it may originate from one duplication event prior to divergence of CgIκB1 and CgIκB2. Tissue expression analyses demonstrated that CgIκB3 mRNA is the most abundant in gills and heart. The expression following PAMP infection showed that CgIκB3 was significantly up-regulated in a similar pattern when challenged with LPS, HKLM or HKVA, respectively. Moreover, similar to CgIκB1 and CgIκB2, CgIκB3 can also inhibit Rel dependent NF-κB activation in HEK293 cells in a dose-dependent manner. In summary, these findings suggest that CgIκB3 can be as the functional inhibitor of NF-κB/Rel and involved in the host defense of C. gigas. The discovery of the third IκB emphasizes the complexity and importance of the regulation on NF-κB activation.
A phase 1/2, open-label, multicenter study of isatuximab in combination with cemiplimab in patients with lymphoma

Patients with relapsed or refractory lymphoma have limited treatment options, requiring newer regimens. In this Phase 1/2 study (NCT03769181), we assessed the safety, efficacy, and pharmacokinetics of isatuximab (Isa, anti-CD38 antibody) in combination with cemiplimab (Cemi, anti-programmed death-1 [PD-1] receptor antibody; Isa + Cemi) in patients with classic Hodgkin lymphoma (cHL), diffuse large B-cell lymphoma (DLBCL), and peripheral T-cell lymphoma (PTCL). In Phase 1, we characterized the safety and tolerability of Isa + Cemi with planned dose de-escalation to determine the recommended Phase 2 dose (RP2D). Six patients in each cohort were treated with a starting dose of Isa + Cemi to determine the RP2D. In Phase 2, the primary endpoints were complete response in Cohort A1 (cHL anti-PD-1/programmed death-ligand 1 [PD-L1] naïve), and objective response rate in Cohorts A2 (cHL anti-PD-1/PD-L1 progressors), B (DLBCL), and C (PTCL). An interim analysis was performed when the first 18 (Cohort A1), 12 (Cohort A2), 17 (Cohort B), and 11 (Cohort C) patients in Phase 2 had been treated and followed up for 24 weeks. Isa + Cemi demonstrated a manageable safety profile with no new safety signals. No dose-limiting toxicities were observed at the starting dose; thus, the starting dose of each drug was confirmed as the RP2D. Based on the Lugano 2014 criteria, 55.6% (Cohort A1), 33.3% (Cohort A2), 5.9% (Cohort B), and 9.1% (Cohort C) of patients achieved a complete or partial response. Pharmacokinetic analyses suggested no effect of Cemi on Isa exposure. Modest clinical efficacy was observed in patients with cHL regardless of prior anti-PD-1/PD-L1 exposure. In DLBCL or PTCL cohorts, interim efficacy analysis results did not meet prespecified criteria to continue enrollment in Phase 2 Stage 2. Isa + Cemi did not have a synergistic effect in these patient populations.
Self-adaptive Algorithm for Simulating Sand Painting in Real-Time

Sand painting is a form of combination of arts and modern aesthetic, which relies on profound cultural heritage and cultural connotation. To provide the public and artists with an opportunity to better understand sand painting and make art creations surprisingly, this paper proposes a self-adaptive algorithm to simulate sand painting in a real-time way. Our simulation system exploits the height field to simulate sand flow to achieve a fast even real-time target. Seven frequently-used styles of painting techniques are elaborately defined and successfully simulated in our system, including pouring, seeping, dotting, stroking, sweeping, multi-stroking, and pinching. The procedure of sand flow is mainly consist of two key parts: sand accumulation and collapse. The direction field is introduced into the system to control a similar appearance of a normal distribution, which will be of benefit to sand accumulation algorithm. A self-adaptive approach is taken advantage of into sand collapse algorithm to present certain appearances with various details. A color factor is also considered for realistic simulation in this paper in two ways: one is the background color of sand table/canvas and the other is the natural color of sand particles themselves. User feedbacks and experimental results reveal that the algorithm of sand painting simulation in this paper can realize kinds of sand painting arts of creations easily, realistically, effectively and interactively.
Integration of Remote-Sensing Techniques for the Preventive Conservation of Paleolithic Cave Art in the Karst of the Altamira Cave

Rock art offers traces of our most remote past and was made with mineral and organic substances in shelters, walls, or the ceilings of caves. As it is notably fragile, it is fortunate that some instances remain intact-but a variety of natural and anthropogenic factors can lead to its disappearance. Therefore, as a valuable cultural heritage, rock art requires special conservation and protection measures. Geomatic remote-sensing technologies such as 3D terrestrial laser scanning (3DTLS), drone flight, and ground-penetrating radar (GPR) allow us to generate exhaustive documentation of caves and their environment in 2D, 2.5D, and 3D. However, only its combined use with 3D geographic information systems (GIS) lets us generate new cave maps with details such as overlying layer thickness, sinkholes, fractures, joints, and detachments that also more precisely reveal interior-exterior interconnections and gaseous exchange; i.e., the state of senescence of the karst that houses the cave. Information of this kind is of great value for the research, management, conservation, monitoring, and dissemination of cave art.
Prime Editing: An Emerging Tool in Cancer Treatment

Prime Editing is a CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) based genome editing technique having promising potential in terms of reducing off target activity. It introduces fragments of DNA sequences into the target site using a guide RNA (gRNA) molecule, composed of both the sequence that is to be inserted into the target site along with an inactive Cas9 nickase and a reverse transcriptase. Prime Editing can cause insertions, deletions, and various point mutations for reverting the phenetic characteristics of a disease specially tested in human adult stem cells and cancer cell lines. The main aim of our review is to explore how Prime Editing and its various forms are being utilized as an emerging tool to cure deleterious diseases like cancer, also as a delivery strategy of the tool into cells. There are almost five generations of Prime Editors (PE) with increasing levels of efficiency from one level to another that have huge clinical potential in correcting mutations; however, the necessity for a pegRNA design is extremely significant. But besides having such advantages, the limitations of this technology particularly include generation of double nicks while optimizing the efficiency of PE3. So, it is important to consider all such consequences and customize PE as per requirements.
Hyperspectral Face Recognition With Spatiospectral Information Fusion and PLS Regression

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition. We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.
A review on state-of-the-art applications of data-driven methods in desalination systems

The substitution of conventional mathematical models with fast and accurate modeling tools can result in the further development of desalination technologies and tackling the need for freshwater. Due to the great capability of data-driven methods in analyzing complex systems, several attempts have been made to study various desalination systems using data-driven approaches. In this state-of-the-art review, the application of various artificial intelligence and design of experiment data-driven methods for analyzing different desalination technologies have been thoroughly investigated. According to the applications of data-driven methods in the field of desalination, the reviewed investigations are classified into five categories namely performance prediction using operational parameters, performance prediction using design parameters, optimization and correlation development, maintenance, and control of desalination systems. For each category, valuable information about the data-driven methods such as inputs, outputs, hyper-parameter tuning methods, and size of datasets have been provided and the main remarks are reported. The findings showed that data-driven methods can play a vital role in each aforementioned application for both thermal and membrane-based desalination technologies. Eventually,
Continuous Histone Deacylase Activity Assays

Protein lysine acylation represents one of the most common post-translational modifications. Obviously, highly reactive metabolic intermediates, like thioesters and mixed anhydrides between phosphoric acid and organic acids, modify lysine residues spontaneously. Additionally, enzymes using acyl-CoAs as co-substrates transfer the acyl residue specifically to defined sequences within proteins. The counteracting enzymes are called histone deacetylases (HDACs), releasing the free lysine side chain. Such enzymatic activities are involved in different cellular processes like tumor progression, immune response, regulation of metabolism, and aging. Modulators of such enzymatic activities represent valuable tools in drug discovery. Therefore, direct and continuous assays to monitor enzymatic activity of HDACs are needed. Here we describe different assay formats allowing both monitoring of Zn2+-dependent HDACs via UV-Vis-spectroscopy and NAD+-dependent HDACs (sirtuins) by fluorescence-based assay formats. Additionally, we describe methods enabling efficient screening of HDAC-inhibitors via fluorescence displacement assays.
Agent alliance formation using ART-networks as agent belief models

In today's hyper-competitive business environments virtual organisations are becoming highly dynamic and unpredictable. Individuals may want to work together across organisation boundaries but do not have much prior knowledge about potential partners. The semantic web and its associated new standards appear very promising as candidates to support a new generation of virtual organisations. Whilst knowledge can be represented in a machine interpretable way, social-like behaviours can be expected in a virtual organisation. In this paper ontology definition techniques from the semantic web are applied to define a virtual state space of a virtual organisation. Actors involved in an organisation, from high level strategy making members to low level physical devices, advertise their skills and local knowledge in a community. A task initiator, with a virtual sensor to perceive the advertised skills and with an adaptive belief model about the community, seeks for the best matched partners for cooperation. The belief model is a fuzzy neural network based on Adaptive Resonance Theory which takes the advertisements of actors as its initial belief and learns actors' actual capabilities through interaction experience. Dynamic alliances can then take place in an automated/semi-automated way that exhibit adaptive ability, self-organisation, unsupervised learning and competition ability. The alliances thus exhibit the inherent characteristics of realistic enterprises or human societies.
Efficient Computer-Aided Design of Dental Inlay Restoration: A Deep Adversarial Framework

Restoring the normal masticatory function of broken teeth is a challenging task primarily due to the defect location and size of a patient's teeth. In recent years, although some representative image-to-image transformation methods (e.g. Pix2Pix) can be potentially applicable to restore the missing crown surface, most of them fail to generate dental inlay surface with realistic crown details (e.g. occlusal groove) that are critical to the restoration of defective teeth with varying shapes. In this article, we design a computer-aided Deep Adversarial-driven dental Inlay reStoration (DAIS) framework to automatically reconstruct a realistic surface for a defective tooth. Specifically, DAIS consists of a Wasserstein generative adversarial network (WGAN) with a specially designed loss measurement, and a new local-global discriminator mechanism. The local discriminator focuses on missing regions to ensure the local consistency of a generated occlusal surface, while the global discriminator aims at defective teeth and adjacent teeth to assess if it is coherent as a whole. Experimental results demonstrate that DAIS is highly efficient to deal with a large area of missing teeth in arbitrary shapes and generate realistic occlusal surface completion. Moreover, the designed watertight inlay prostheses have enough anatomical morphology, thus providing higher clinical applicability compared with more state-of-the-art methods.
Synthesis, characterization of Ag-WO3/bentonite nanocomposites and their application in photocatalytic degradation of humic acid in water

In this study, Ag-WO3/bentonite nanocomposites were synthesized through a sol-gel process, a microwave irradiation technique, and a sol-immobilization process to examine their impact on the photocatalytic activity in the degradation of humic acids. The optical and structural properties of the synthesized materials were characterized using X-ray diffraction (XRD), Fourier-transform-infrared spectra (FTIR), field emission scanning electron microscope (FE-SEM) with energy dispersive X-ray (EDX), UV-Vis diffused reflectance spectra (UV-Vis DRS), Brunauer-Emmett-Teller (BET) method, and transmission electron microscope (TEM). The presence of Ag and WO3 peaks in the XRD and EDX spectra confirmed the synthesis of Ag-WO3 nanoparticles in the composite. The monoclinic structure of the produced WO3 samples are shown by powder X-ray diffraction patterns. The WO3-based nanocomposites' photocatalytic activity was improved by the composition of Ag and bentonite, which reduced the optical bandgap energy of WO3. The binary (Ag-WO3) nanocomposite showed improved photocatalytic activity towards the degradation of humic acid (HA) from 58% (pristine WO3) to 82% (Ag-WO3) when compared with the pristine WO3 sample under the visible light irradiation. Notably, the ternary (Ag-WO3/bent) nanocomposite demonstrated an outstanding photocatalytic efficiency of HA degradation (91.0%) under normal conditions (pH = 7.0 and 25 °C). Humic acid degradation in Ag-WO3/bent was expressed by the pseudo-first-order kinetic. To summarize, integrating Ag, WO3, bentonite, and visible light radiation to activate HA efficiently can be offered as a successful and promising technique for wastewater treatment.
Generic integration tools for reconfigurable laser micromachining systems

Laser micro-machining (LMM) is an attractive manufacturing process due to its intrinsic machining characteristics such as such as non-contact processing and capabilities to machine complex free-form surfaces in a wide range of materials. Nevertheless, state-of-art LMM platforms still do not offer the repeatability, reproducibility and operability of conventional machining centres, e.g. the flexibility to realise complex machining configurations and also to combine LMM with other complementary processes in hybrid manufacturing systems and production lines. The paper presents the development of three generic integration tools for improving the system-level performance of reconfigurable LMM platforms. In particular, the research reports the design and implementation of modular workpiece holding device, automated work piece setting up routine and automated strategy for multi-axis LMM machining employing rotary stages. An experimental validation of their accuracy, repeatability and reproducibility (ARR) are performed on a representative state-of-art LMM platform. The results demonstrate the flexibility and operability of the proposed tools to address important system-level issues in LMM by creating the necessary pre-requisites for achieving machining ARR better than +/- 10 mu m. (C) 2015 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
Assessing Climate Change Impact on the US East Coast Hurricane Hazard: Temperature, Frequency, and Track

This paper presents a study to assess the impact of possible future climate change on the hurricane wind hazard along the eastern coastline of the United States. Initially, climate change scenarios were coupled with state-of-the-art hurricane genesis, wind field, and tracking models to examine possible changes in hurricane intensity (maximum wind speed) and hurricane size (radius to maximum winds). A number of different postulated climate change models (IPCC scenarios) were considered. Each scenario suggested changes in sea surface temperature (SST), which is the driving parameter in most modern hurricane models. The evolution of hurricane genesis frequency was then considered both independently and jointly with hurricane intensification. State-of-the-art probabilistic event modeling and simulation techniques were used to generate 10,000 years of hurricane events under the 2005 and future climate conditions. The annual maximum wind speed distribution and the joint distribution of maximum wind speed and storm size, under 2005 and future climate scenarios, are then compared. Finally, the evolution of hurricane tracks was examined in an effort to establish a trend over time. (C) 2014 American Society of Civil Engineers.
Assessing the Feasibility and Implementation of Palliative Care Triggers in a Surgical Intensive Care Unit to Improve Interdisciplinary Collaboration for Patient and Family Care

Although palliative care focuses on supporting patients and families through serious illness, it is underutilized in the surgical intensive care unit (SICU). In 2020, patients in the SICU represented only 2.75% of our palliative team's consults. We hypothesize that utilization of palliative care triggers in the SICU will increase collaboration between SICU and palliative care teams and improve patient/family experiences. After reviewing our team's consultation records and the published literature, a consult trigger program was implemented for patients with a SICU length of stay >10 days, unplanned SICU readmission, or new diagnosis of metastatic cancer. A pre-intervention survey assessed SICU providers' perceptions of palliative care. Retrospective analysis evaluated qualitative and quantitative measures. 97% of SICU providers felt increased palliative care would be helpful. During the 6-month project, January 1, 2021 - June 30, 2021, our palliative team performed 27 triggered consults, representing 3.3% of the total 818 consults performed during this period and thus a 20% increase in SICU palliative consults. Triggered consults represented many primary surgical services and the most common consult reason was length-of-stay. All consults included discussions about goals of care and 16 of the 27 patients/families expressed restorative goals. Numerous notes documented family appreciation.
Efficacy of Olanzapine for Symptom Relief in Cancer Patients

Olanzapine is an atypical antipsychotic and is widely used for prophylaxis of chemotherapy-induced nausea and vomiting in cancer patients. Previous studies have suggested its potential efficacy for the relief of various symptoms in cancer patients, especially gastrointestinal and psychiatric symptoms. We retrospectively reviewed the prescription of olanzapine to cancer patients at our hospital. Between 2008 and 2020, olanzapine was prescribed to 41 patients for relief of symptoms associated with cancer other than prophylaxis of chemotherapy-induced nausea and vomiting. Of those patients, symptom relief was seen in 53.7%. Notably, olanzapine was effective in 13 of 14 patients with chemotherapy-induced nausea and vomiting refractory to guideline-recommended prophylaxis. Of 16 patients in whom this symptom was not relieved by olanzapine, 13 (81.3%) continued taking olanzapine even after it was judged ineffective. No treatment-related adverse events were seen in this study. Our observation implies good efficacy of olanzapine for refractory chemotherapy-induced nausea and vomiting and a tendency to continue olanzapine even in those for whom it was ineffective.
Cognitive and encrypted communications: state of the art and a new approach for frequency-agile filters

Several communication techniques are investigated in the first part of this paper: software radio, cognitive radio and encrypted communications. State of the art of research on agile and reconfigurable filters, passive as well as active, necessary for transceivers is then made and various tables for comparison are given. In the third part, a new theory for a 2(nd)-order frequency-agile filter is introduced. The center frequency of the filter is proportional to the gain of a feedback amplifier and thus can be tuned over a wide frequency range. This new theory is thereafter generalized to the n(th)-class leading to a center frequency proportional to (A)(n/2). Simulation results of band pass agile filters in current mode and made from second-generation current controlled conveyors (CCCII+) in 0.25 mu m SiGe BiCMOS technology are given for n = 1 and n = 2. These simulation results along with results of measurements carried out on the fabricated filters entirely confirm the new approach. They also highlight the improvements to be expected for cognitive and encrypted communications.