ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Targeting TNF-α-producing macrophages activates antitumor immunity in pancreatic cancer via IL-33 signaling

Pancreatic ductal adenocarcinoma (PDA) remains resistant to immune therapies, largely owing to robustly fibrotic and immunosuppressive tumor microenvironments. It has been postulated that excessive accumulation of immunosuppressive myeloid cells influences immunotherapy resistance, and recent studies targeting macrophages in combination with checkpoint blockade have demonstrated promising preclinical results. Yet our understanding of tumor-associated macrophage (TAM) function, complexity, and diversity in PDA remains limited. Our analysis reveals significant macrophage heterogeneity, with bone marrow-derived monocytes serving as the primary source for immunosuppressive TAMs. These cells also serve as a primary source of TNF-α, which suppresses expression of the alarmin IL-33 in carcinoma cells. Deletion of Ccr2 in genetically engineered mice decreased monocyte recruitment, resulting in profoundly decreased TNF-α and increased IL-33 expression, decreased metastasis, and increased survival. Moreover, intervention studies targeting CCR2 with a new orthosteric inhibitor (CCX598) rendered PDA susceptible to checkpoint blockade, resulting in reduced metastatic burden and increased survival. Our data indicate that this shift in antitumor immunity is influenced by increased levels of IL-33, which increases dendritic cell and cytotoxic T cell activity. These data demonstrate that interventions to disrupt infiltration of immunosuppressive macrophages, or their signaling, have the potential to overcome barriers to effective immunotherapeutics for PDA.
Preventing Aerosol Emissions in a CO2 Capture System: Combining Aerosol Formation Inhibition and Wet Electrostatic Precipitation

Aerosol emission from the CO2 capture system has raised great concern for causing solvent loss and serious environmental issues. Here, we propose a comprehensive method for reducing aerosol emissions in a CO2 capture system under the synergy of aerosol formation inhibition and wet electrostatic precipitation. The gas-solvent temperature difference plays a vital role in aerosol formation, with aerosol emissions of 740.80 mg/m3 at 50 K and 119.36 mg/m3 at 0 K. Different effects of SO2 and SO3 on aerosol formation are also found in this research; the aerosol mass concentration could reach 2341.25 mg/m3 at 20 ppm SO3 and 681.01 mg/m3 at 50 ppm SO2 with different aerosol size distributions. After the CO2 capture process, an aerosol removal efficiency of 98% can be realized by electrostatic precipitation under different CO2 concentrations. Due to the high concentration of aerosols and aerosol space charge generated by SO2 and SO3, the removal performance of the wet electrostatic precipitator decreases, resulting in a high aerosol emission concentration (up to 130.26 mg/m3). Thus, a heat exchanger is installed before the electrostatic precipitation section to enhance aerosol growth and increase aerosol removal efficiency. Under the synergy of aerosol formation inhibition and electrostatic precipitation, an aerosol removal efficiency of 99% and emission concentrations lower than 5 mg/m3 are achieved, contributing to global warming mitigation and environmental protection.
Fully-differential flipped-source-follower low-pass analogue filter in CMOS 28nm bulk

This study presents a novel low-pass continuous-time filter based on the voltage flipped-source-follower (SF). The filter efficiently operates in CMOS 28nm and improves the SF filters state-of-the-art thanks to a dedicated circuit that operates in fully-differential fashion (instead of the pseudo-differential typically used in state-of-the-art SF filters) with a dedicated Common-Mode-Feedback circuit. Thus this work extends the application of the SF filtering stages to the nm-range technologies where threshold voltage (V-TH) is only two times lower than the supply voltage (V-DD) for what regards standard-process MOS transistors. In order to validate the design concept, the proposed filter has been designed in CMOS 28nm technology. Extensive simulation results of a 131MHz -3dB frequency proof-of-concept second-order filter are proposed. The device consumes 510 mu W power from a single 1V supply-voltage. In-band integrated noise is 160 mu V-RMS and IIP3 is 19dBm for 20 and 21MHz input tones frequencies. Simulation results lead to 166J(-1) figure-of-merit, outperforming the analogue filter state-of-the-art.
Efficient Multiple Organ Localization in CT Image Using 3D Region Proposal Network

Organ localization is an essential preprocessing step for many medical image analysis tasks, such as image registration, organ segmentation, and lesion detection. In this paper, we propose an efficient method for multiple organ localization in CT image using a 3D region proposal network. Compared with other convolutional neural network-based methods that successively detect the target organs in all slices to assemble the final 3D bounding box, our method is fully implemented in a 3D manner, and thus, it can take full advantages of the spatial context information in CT image to perform efficient organ localization with only one prediction. We also propose a novel backbone network architecture that generates high-resolution feature maps to further improve the localization performance on small organs. We evaluate our method on two clinical datasets, where 11 body organs and 12 head organs (or anatomical structures) are included. As our results shown, the proposed method achieves higher detection precision and localization accuracy than the current state-of-the-art methods with approximate 4 to 18 times faster processing speed. Additionally, we have established a public dataset dedicated for organ localization on http://dx.doi.org/10.21227/df8g-pq27. The full implementation of the proposed method has also been made publicly available on https://github.com/superxuang/caffe_3d_faster_rcnn.
Friction-resilient position control for machine tools-Adaptive and sliding-mode methods compared

Robust trajectory tracking and increasing demand for high-accuracy tool positioning have motivated research in advanced control design for machine tools. State-of-the-art industry solutions employ cascades of Proportional (P) and Proportional Integral (PI) controllers for closed-loop servo control of position and velocity of the machine axes. Although these schemes provide the required positioning accuracy in nominal conditions, performance deteriorates with increased friction and wear of the machine. With conventional control, re-tuning is necessary during the lifetime if specified accuracy shall be maintained. This paper investigates whether nonlinear and adaptive controllers can cope with typical levels of friction increase without loss of performance. It evaluates the performance of a state-of-art industry solution with that obtainable with adaptive and sliding mode positioning controls. The main finding is that an adaptive backstepping control is resilient to unknown and increasing friction at realistic levels of wear, where the P-PI control fall short with respect to accuracy. A single-axis test rig with adjustable friction is used to assess the performance of different controllers.
Blockade of CD127 Exerts a Dichotomous Clinical Effect in Marmoset Experimental Autoimmune Encephalomyelitis

Non-human primate models of human disease have an important role in the translation of a new scientific finding in lower species into an effective treatment. In this study, we tested a new therapeutic antibody against the IL-7 receptor α chain (CD127), which in a C57BL/6 mouse model of experimental autoimmune encephalomyelitis (EAE) ameliorates disease, demonstrating an important pathogenic function of IL-7. We observed that while the treatment was effective in 100 % of the mice, it was only partially effective in the EAE model in common marmosets (Callithrix jacchus), a small-bodied Neotropical primate. EAE was induced in seven female marmoset twins and treatment with the anti-CD127 mAb or PBS as control was started 21 days after immunization followed by weekly intravenous administration. The anti-CD127 mAb caused functional blockade of IL-7 signaling through its receptor as shown by reduced phosphorylation of STAT5 in lymphocytes upon stimulation with IL-7. Group-wise analysis showed no significant effects on the clinical course and neuropathology. However, paired twin analysis revealed a delayed disease onset in three twins, which were high responders to the immunization. In addition, we observed markedly opposite effects of the antibody on pathological changes in the spinal cord in high versus low responder twins. In conclusion, promising clinical effect of CD127 blockade observed in a standard inbred/SPF mouse EAE model could only be partially replicated in an outbred/non-SPF non-human primate EAE model. Only in high responders to the immunization we found a positive response to the treatment. The mechanism underpinning this dichotomous response will be discussed.
State of art of biomass fast pyrolysis for bio-oil in China: a review

This paper presents a review of biomass fast pyrolysis for the production of bio-oil in Mainland China. The main contents are as follows. The feedstock for fast pyrolysis and main pyrolysis reactor developed in Mainland China are introduced. The process of fast pyrolysis for each pyrolysis reactor mentioned in this paper is described. The effects of key parameters of fast pyrolysis on fluidised bed reactor are illustrated. Finally, the properties, upgrading and application of bio-oil are discussed.
Premenopausal and postmenopausal women during the COVID-19 pandemic

The current global COVID-19 mortality rate is estimated to be around 3.4%; however, it is dependent on age, sex, and comorbidities. Epidemiological evidence shows gender disparities in COVID-19 severity and fatality, with non-menopausal females having milder severity and better outcomes than age-matched males. However, the difference vanishes when comparing postmenopausal women with age-matched men. It has been suggested that, to some extent, this is due to the protective role of female hormones, such as anti-Müllerian hormone and oestradiol (E2), in non-menopausal women. Oestrogens have been hypothesized to be crucial in modulating viral infection and the progression of the disease via an action on immune/inflammatory responses and angiotensin-converting enzyme type 2 expression. Hence, the most likely explanation is that, because the levels of oestrogen in females after menopause decrease, oestrogen no longer offers a beneficial effect as seen in younger females. The COVID-19 pandemic has highlighted the serious negative effects arising from the state of E2 deficiency. Therefore, hormone replacement therapy gains further support as the damaging effect of the decline in ovarian function affects many biological systems, and recently with the COVID-19 pandemic, oestrogen's vital role within the immune system has become quite clear. However, additional clinical investigations regarding hormone replacement therapy are urgently needed to further verify the protective and therapeutic effects of E2 on menopausal women with COVID-19.
A fast framework construction and visualization method for particle-based fluid

Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those issues, we present a fast framework for 3D fluid fast constructing and visualization which parallelizes the fluid algorithm based on the GPU computing framework and designs a direct surface visualization method for particle-based fluid data such as WCSPH, IISPH, and PCISPH. Considering on conventional polygonization or adaptive mesh methods may incur high computing costs and detail losses, an improved particle-based method is provided for real-time fluid surface rendering with the screen-space technology and the utilities of the modern graphics hardware to achieve the high performance rendering; meanwhile, it effectively protects fluid details. Furthermore, to realize the fast construction of scenes, an optimized design of parallel framework and interface is also discussed in our paper. Our method is convenient to enforce, and the results demonstrate a significant improvement in the performance and efficiency by being compared with several examples.
CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in the cardiovascular system or shear-wave elastography. The accuracy achievable with these motion estimation techniques is strongly contingent upon two contradictory requirements: a high quality of consecutive frames and a high frame rate. Indeed, the image quality can usually be improved by increasing the number of steered ultrafast acquisitions, but at the expense of a reduced frame rate and possible motion artifacts. To achieve accurate motion estimation at uncompromised frame rates and immune to motion artifacts, the proposed approach relies on single ultrafast acquisitions to reconstruct high-quality frames and on only two consecutive frames to obtain 2-D displacement estimates. To this end, we deployed a convolutional neural network-based image reconstruction method combined with a speckle tracking algorithm based on cross-correlation. Numerical and in vivo experiments, conducted in the context of plane-wave imaging, demonstrate that the proposed approach is capable of estimating displacements in regions where the presence of side lobe and grating lobe artifacts prevents any displacement estimation with a state-of-the-art technique that relies on conventional delay-and-sum beamforming. The proposed approach may therefore unlock the full potential of ultrafast ultrasound, in applications such as ultrasensitive cardiovascular motion and flow analysis or shear-wave elastography.
Local Phase Velocity Based Imaging: A New Technique Used for Ultrasound Shear Wave Elastography

Ultrasound shear wave elastography is an imaging modality for noninvasive evaluation of tissue mechanical properties. However, many current techniques overestimate lesions dimension or shape especially when small inclusions are taken into account. In this paper, we propose a new method called local phase velocity-based imaging (LPVI) as an alternative technique to measure tissue elasticity. Two separate acquisitions with ultrasound push beams focused once on the left side and once on the right side of the inclusion were generated. A local shear wave velocity is then recovered in the frequency domain (for a single frequency or frequency band) for both acquired data sets. Finally, a two-dimensional shear wave velocity map is reconstructed by combining maps from two separate acquisitions. Robust and accurate shear wave velocity maps are reconstructed using the proposed LPVI method in calibrated liver fibrosis tissue mimicking homogeneous phantoms, a calibrated elastography phantom with stepped cylinder inclusions and a homemade gelatin phantom with ex vivo porcine liver inclusion. Results are compared with an existing phase velocity-based imaging approach and a group velocity-based method considered as the state of the art. Results from the phantom study showed that increased frequency improved the shape of the reconstructed inclusions and contrast-to-noise ratio between the target and background.
The influence of 5-fluorouracil on the α-ketoglutarate dehydrogenase complex in rat's cardiac muscle - a preliminary study

5-fluorouracil (5-FU), which is a commonly used chemotherapy agent exerts undesired cardiac toxicity. Mitochondrial dysfunction is thought to be one of potentially important mechanisms of 5-FU- induced cardiotoxicity. α-ketoglutarate dehydrogenase (α-KGDHC) is the key regulatory enzyme of TCA cycle. The complex consists of multiple copies of three catalytic subunits: α-ketoglutarate dehydrogenase (E1), dihydrolipoamide succinyltransferase (E2) and dihydrolipoamide dehydrogenase (E3). α-KGDHC together with branched chain α-ketoacid dehydrogenase (BCKDH) and pyruvate dehydrogenase (PDH), are the members of 2-oxoacid dehydrogenases family that share some structural and functional similarities. Recently, it has been found that 5-FU stimulates BCKDH in rat's cardiac muscle. Therefore, we hypothesize that 5-FU modifies α-KGDHC activity and affects cardiac muscle metabolism. The aim of this study was to determine the effect of 5-FU on α-KGDHC activity and protein levels of E1 and E2 subunits of the complex in rat's cardiac muscle. Wistar male rats were administered with 4 doses of 5-FU, 150 mg/ kg b.wt. each (study group) or 0.3% methylcellulose (control group). α-KGDHC activity was assayed spectrophotometrically. The E1 and E2 proteins levels were quantified by Western blot. 5-FU administration resulted in stimulation of myocardial α-KGDHC activity in rats. In addition, E2 protein level increased in response to 5-FU treatment, while the E1 protein level remained unchanged. Up-regulation of α-KGDHC appears to result from change in E2 subunit protein level. However, the effect of 5-FU on factors modifying α-KGDHC activity at post-translational level cannot be excluded.
Computational Approaches and Challenges in Spatial Transcriptomics

The development of spatial transcriptomics (ST) technologies has transformed genetic research from a single-cell data level to a two-dimensional spatial coordinate system and facilitated the study of the composition and function of various cell subsets in different environments and organs. The large-scale data generated by these ST technologies, which contain spatial gene expression information, have elicited the need for spatially resolved approaches to meet the requirements of computational and biological data interpretation. These requirements include dealing with the explosive growth of data to determine the cell-level and gene-level expression, correcting the inner batch effect and loss of expression to improve the data quality, conducting efficient interpretation and in-depth knowledge mining both at the single-cell and tissue-wide levels, and conducting multi-omics integration analysis to provide an extensible framework toward the in-depth understanding of biological processes. However, algorithms designed specifically for ST technologies to meet these requirements are still in their infancy. Here, we review computational approaches to these problems in light of corresponding issues and challenges, and present forward-looking insights into algorithm development.
A Fast Superresolution Image Reconstruction Algorithm

In a previous paper we have proposed two new superresolution image reconstruction algorithms, based on a non-parametric numerical integration Bayesian inference method, the Integrated Nested Laplace Approximation (INLA). Despite achieving superior image reconstruction results compared to other state-of-the-art methods, such algorithms manipulate huge matrices (although sparse). Therefore, the demand for memory usage and computation is high. In this paper, review such algorithms, solving these problems through relaxing one equation in the original mathematical model and involving the high-resolution (HR) image in a Torus. The result is a meaningful reduction in the computation cost of such algorithms and in the dimensions of the matrices handled as well (from n(2)-by-n(2) to n-byn, the size of the HR image). The result is a new algorithm, much faster than its previous version and other meaningful state-of-the-art algorithms.
Atrazine exposure induces necroptosis through the P450/ROS pathway and causes inflammation in the gill of common carp (Cyprinus carpioL.)

Atrazine (ATR) is used worldwide and has been confirmed be hazardous materials that harmful to the health of organisms. Since ATR was more persistent in the water, the specific damage caused by ATR to aquatic organisms should be concern. The role of P450/ROS has been proposed in many pathomechanisms. To explore whether P450/ROS mediated necroptosis and promote inflammatory response caused by ATR exposure, 120 common carp (Cyprinus carpio L.) were randomly divided into four groups which were exposed to 0 μg/L, 4 μg/L, 40 μg/L and 400 μg/L ATR respectively. The residual levels of ATR and its metabolites increased, signs of necrosis and inflammation were found in the gills of the ATR-treatment groups. The levels of ROS and cytochrome P450 content were increased, and P450 enzymes were activated. The expression levels of the core components of necroptosis (RIPK1, RIPK3 and MLKL) increased. Moreover, gene expression of inflammatory factors (TNF-α, NF-κB, iNOS, COX-2, IL-1β and PTGE) increased significantly in the ATR-spiked group. Our results suggested that ATR exposure triggered necroptosis through the P450/ROS pathway and causes inflammation of common carp gill. This study provides valuable clue about the mechanism by which ATR causes injury to common carp gill.
Boronates as hydrogen peroxide-reactive warheads in the design of detection probes, prodrugs, and nanomedicines used in tumors and other diseases

Hydrogen peroxide (H2O2) has always been a topic of great interests attributed to its vital role in biological process. H2O2 is known as a major reactive oxygen species (ROS) which is involve in numerous physiological processes such as cell proliferation, signal transduction, differentiation, and even pathogenesis. A plenty of diseases development such as chronic disease, inflammatory disease, and organ dysfunction are found to be relevant to abnormality of H2O2 production. Thus, imminent and feasible strategies to modulate and detect H2O2 level in vitro and in vivo have gained great importance. To date, the boronate-based chemical structure probes have been widely used to address the problems from the above aspects because of the rearranged chemical bonding which can detect and quantify ROS including hydrogen peroxide (H2O2) and peroxynitrite (ONOO-). This present article discusses boronate-based probes based on the chemical structure difference as well as reactivities to H2O2 and ONOO-. In this review, we also focus on the application of boronate-based probes in the field of cell imaging, prodrugs nanoplatform, nanomedicines, and electrochemical biosensors for disease diagnosis and treatment. In a nutshell, we outline the recent application of boronate-based probes and represent the prospective potentiality in biomedical domain in the future.