Different Types Of Targets Research Articles

Quaternion-based non-singular nonlinear impact angle guidance for three-dimensional engagements

This paper proposes a three-dimensional impact angle-constrained nonlinear guidance strategy against different types of targets. To avoid the occurrence of singularities, in Euler angle-based approaches, the development of this guidance strategy is solely based on quaternion dynamics. An explicit relationship between the quaternions representing impact orientation and line-of-sight orientation at the time of collision is derived. Based on the obtained relation, a guidance law is derived using a sliding mode control technique to track the desired line-of-sight orientation for target interception. The performance of the proposed guidance strategy is evaluated for constant-speed and different time-varying-speed interceptor models accounting for the effect of varying aerodynamic parameters on interceptor speed. The numerical simulations performed show satisfactory results for all engagements, validating the efficacy and robustness of the proposed guidance law.

PROTAC’ING CENTROSOME AMPLIfiCATION PROTEINS: TARGETED PROTEIN DEGRADATION AS A NOVEL THERAPEUTIC STRATEGY IN GLIOBLASTOMA

Abstract AIMS Glioblastomas (GBMs) are the most common and aggressive brain tumours, notoriously difficult to treat with universal treatment resistance. A key feature of cancer cells is centrosome amplification (CA), leading to chromosomal instability and worse patient outcomes, including metastasis development and treatment resistance. In this work, I identified CA proteins overexpressed in GBM and aimed to investigate how the targeted degradation of proteins associated with centrosome amplification can influence the growth and survival of GBM cells. METHOD Based on well-established literature data concerning CA-related genes, I evaluated the expression level of these targets in different types of samples from the Tumour Cancer Genome Atlas dataset of GBM patient samples. Following the identification of CA targets differentially overexpressed, to test the hypothesis that CA proteins could be involved in the survival of GBM cells and be potential therapeutic targets, I used a novel drug modality, named Proteolysis Targeting Chimeras (PROTACs) to degrade two CA proteins. PROTACs can quickly destroy specific proteins, potentially overcoming resistance to treatment. Target degradation was confirmed via immunoblotting and cell viability and cell cycle analysis were performed to evaluate the impact on GBM cells. RESULTS Both primary and recurrent GBM samples display high levels of CA gene signature when compared to noncancerous samples, and some CA genes are particularly upregulated in recurrent samples. The PROTACs were effective in degrading both CA targets in GBM cells, leading to a significant decrease in cell viability and G2 cell cycle arrest. CONCLUSION This study presents initial evidence that CA protein degradation could be a promising avenue for GBM research and therapy. Further research is needed to fully assess the translational potential of PROTACs in GBM treatment.

Proline: A versatile amino acid in the presence of salinity and drought in the Capsicum genus

Abstract Proline (Pro) is a low-molecular-weight cyclic amino acid that plays an important role as a source of energy and reducing power and as a source of carbon and nitrogen compounds for plant development. In most plant species, Pro is considered a stress marker. It is also a common compatible solute and is used cumulatively by plants under osmotic stress. The pepper genus, which includes species of great economic importance distributed throughout the world, is the target of different types of stresses, both biotic and abiotic, and Pro plays an important role in tolerance to some of these stresses. In this work, we discuss the general aspects of the metabolism, transport, and different functions of Pro in the Capsicum genus. Special focus is given to critical investigations that should be conducted with respect to Pro accumulation under stress conditions, such as salinity and water deficit.

Landmine Detection Using Electromagnetic Time Reversal‐Based Methods: 2. Performance Analysis of TR‐MUSIC

AbstractIn this paper, a series of numerical simulations are conducted for various 2D and 3D configurations to demonstrate the performance of the Time Reversal MUltiple SIgnal Classification (TR‐MUSIC) method. The results reveal the excellent performance of TR‐MUSIC, taking into account the effects of noise, soil types (both homogeneous and layered), and their electrical parameters, as well as different types of targets (varying in number, size, shape, and location). Additionally, unlike other electromagnetic TR‐based techniques, TR‐MUSIC offers very high resolution (on the order of /10 or higher) with a reasonable number of sensors, enabling the detection of multiple closely spaced targets. In TR‐based methods, reflections from the object(s) or landmine(s) are crucial and are determined by the difference between the constitutive parameters (e.g., permittivity, permeability, and conductivity) of the landmine(s) and their surrounding medium. Therefore, TR‐based approaches, similar to conventional GPR‐based approaches, are suitable for detecting objects or landmines with significant differences in constitutive parameters compared to their immersion medium. This research primarily focuses on metallic objects or landmines.

Underwater Bubble Plume Recognition Algorithm Based on Multi-Feature Fusion Understanding

Underwater bubble plume images contain a wealth of information on wave field and flow characteristics, which can provide valuable research data for marine development, environmental protection, and underwater surveys. However, based on fusing image features and wave field environment features, identifying accurately the underwater bubble plume is still very difficult. In order to improve the accuracy and robustness of bubble plume identification in complex underwater environments, an underwater bubble plume recognition algorithm based on multi-feature fusion understanding is proposed. In this paper, a weight-independent dual-channel residual convolutional neural network (CNN) for feature extraction of the original optical images and the nonsubsampled contourlet transform (NSCT) low-frequency images, and the multi-scale composite feature map groups are generated. Then adaptive fusion is performed based on the feature contribution of the target in different types of images. Next, logical region of interest (ROI) masks are generated by the attention mechanism and superimposed on the fused image to further highlight the target features. Finally, the multi-scale dual-channel fused feature maps containing ROI masks are used for underwater bubble plume target recognition. The experimental results show that the designed recognition network can effectively fuse the features of the original optical images and the NSCT low-frequency imagers, improve the depth of information fusion, and retain the target texture features and the morphological features while reducing the interference of the background information, and have good recognition accuracy and robustness for multi-scale bubble targets in the underwater environment.

Identification and functionalization of thyrotropin receptor antibodies with different antigenic epitopes.

One of the sensitive markers for autoimmune thyroid disease (AITD) clinical identification is thyroid-stimulating hormone receptor antibodies (TRAbs). To quickly distinguish TRAb with distinct antigenic epitopes, a straightforward and uncomplicated technique has not yet been created. The objective of this study is to search for molecular diagnostic targets for different types of AITD {Graves' disease (GD), Graves' orbitopathy (GO), GD with third-degree goiter [GD(3)], hypothyroidism combined with positive TRAb [HT(TRAb+)]} as molecular diagnostic targets. Following action on thyroid cells, differential genes (DEGs) generated by TRAb with distinct antigenic epitopes were detected and identified by RNA sequencing (RNA-Seq), bioinformatics analysis, and quantitative reverse transcription-polymerase chain reaction (RT-qPCR) in the serum of patients with AITD. Using the 5-ethynyl-2'-deoxyuridine (EdU) assay, the effect of coculturing thyroid cells with different antigenic TRAb epitopes on the cells' capacity to proliferate was investigated. Bioinformatics analysis and RT-qPCR validation identified one GD key gene alpha 2-HS glycoprotein (AHSG), two GO key genes [adrenoceptor alpha 1D (ADRA1D) and H2B clustered histone 18 (H2BC18)], two GD(3) key genes [suppressor of cytokine signaling 1 (SOCS1) and cytochrome b-245 beta (CYBB)], and one HT(TRAb+) key gene (MASP2). Correlation analysis and ROC curves showed that the abovementioned genes could be used as molecular diagnostic targets for different types of AITD. Finally, EdU results showed that TRAb inhibited thyroid cell proliferation in the HT(TRAb+) group compared with the normal control group, whereas the remaining three groups promoted thyroid cell proliferation, with a statistically significant difference (P < 0.05). We identified six key genes for different types of AITD, which have diagnostic value for different types of AITD. Meanwhile, we found that TRAbs with different antigenic epitopes in AITD have different biological functions.NEW & NOTEWORTHY We identified six molecular targets of different types of AITD [GD, GO, GD(3), and HT(TRAb+)], which have diagnostic value for different types of AITD. Meanwhile, we found that TRAb with different antigenic epitopes extracted from the sera of patients with AITD had different biological functions, which also provided a new idea for further research on the mechanism of action of TRAb with different antigenic epitopes in AITD.

The activation of Piezo1 channel promotes invasion and migration via the release of extracellular ATP in cervical cancer

BackgroundThe mechanosensitive ion channel Piezo1 has emerged as a potential prognostic and therapeutic target in different types of cancers. The aim of this study was to determine the expression levels and underlying mechanisms of Piezo1 in the invasion and migration processes in cervical cancer. MethodsInitially, we employed qRT-PCR, western blot, and immunohistochemical staining techniques to assess the disparity in Piezo1 expression in cervical cancer tissues and cells. Subsequently, we conducted wound healing, transwell assays and phalloidin staining to observe the effects of stable Piezo1 silencing and Piezo1 selective agonist Yoda1 on the invasion and migration capabilities. The release of extracellular ATP was assessed using the enhanced ATP assay kit. Furthermore, we conducted rescue experiments to investigate whether the activation of Piezo1 facilitates cervical cancer invasion and migration through extracellular ATP. Finally, we constructed xenograft tumor models to determine weather the Piezo1 selective agonist Yoda1 influenced the tumor growth in vivo. ResultsIn our study, we found that Piezo1 expression was elevated in both cervical cancer tissues and cells, with the highest levels observed in patients with lymph node metastasis. Knocking down Piezo1 resulted in a significant reduction in the invasion and migration capabilities of cervical cancer cells, whereas the use of the Piezo1 selective agonist Yoda1 enhanced these capabilities. Moreover, the activation of Piezo1 channels was found to regulate the release of extracellular ATP. Mechanistically, the activation of Piezo1 might facilitate cervical cancer invasion, migration, and pseudopodium formation through the release of extracellular ATP. And Piezo1 was an important molecule for the tumor growth of cervical cancer in vivo. ConclusionOur findings revealed that Piezo1 facilitated the invasion and migration of cervical cancer by releasing extracellular ATP, which might hold potential as a valuable target for prognostic and therapeutic interventions in cervical cancer.

Discrimination of Multiple Homologous Sequences Based on DNA Logic Gate and Elemental Labeling Technology.

The simultaneous discrimination of multiple homologous sequences faces challenges due to the high similarity of sequences and the complexity of the discrimination system in most reported works. Herein, a simple and ingenious analysis method was developed to identify eight miRNAs of the let-7 family by combining logic gates and entropy-driven catalytic (EDC)-based lanthanide labeling inductively coupled plasma mass spectrometry (ICP-MS) technology. Specifically, eight miRNAs were first divided into four types according to the difference of bases in the domains 2 and 3 on sequences. To identify the type of targets, a DNA logic gate was constructed with two strand displacement reactions on magnetic beads that could be initiated by different types of targets. Based on the difference of the output signals after two strand displacement reactions, the type of targets was distinguished preliminarily. Then, the discrimination of a specific target was achieved with EDC-based lanthanide labeling ICP-MS detection. By labeling the different magnetic probes with different elemental tags, a specific element signal released from magnetic beads after EDC could be detected by ICP-MS, and therefore, simultaneous detection of homologous sequences was completed. This work provided a novel and simple method for highly specific identification of homologous sequences with the assistance of a logic gate and can promote further development of elemental labeling ICP-MS in the field of multiple analysis.

Analysis of Various Machine Learning Algorithms for Using Drone Images in Livestock Farms

With the development of artificial intelligence, the intelligence of agriculture has become a trend. Intelligent monitoring of agricultural activities is an important part of it. However, due to difficulties in achieving a balance between quality and cost, the goal of improving the economic benefits of agricultural activities has not reached the expected level. Farm supervision requires intensive human effort and may not produce satisfactory results. In order to achieve intelligent monitoring of agricultural activities and improve economic benefits, this paper proposes a solution that combines unmanned aerial vehicles (UAVs) with deep learning models. The proposed solution aims to detect and classify objects using UAVs in the agricultural industry, thereby achieving independent agriculture without human intervention. To achieve this, a highly reliable target detection and tracking system is developed using Unmanned Aerial Vehicles. The use of deep learning methods allows the system to effectively solve the target detection and tracking problem. The model utilizes data collected from DJI Mirage 4 unmanned aerial vehicles to detect, track, and classify different types of targets. The performance evaluation of the proposed method shows promising results. By combining UAV technology and deep learning models, this paper provides a cost-effective solution for intelligent monitoring of agricultural activities. The proposed method offers the potential to improve the economic benefits of farming while reducing the need for intensive hum.

SIRT3: A Potential Target of Different Types of Osteoporosis.

Osteoporosis (OP) is a common age-related disease. OP is mainly a decrease in bone density and mass caused by the destruction of bone microstructure, which leads to an increase in bone fragility. SIRT3 is a mitochondrial deacetylase that plays critical roles in mitochondrial homeostasis, metabolic regulation, gene transcription, stress response, and gene stability. Studies have shown that the higher expression levels of SIRT3 are associated with decreased levels of oxidative stress in the body and may play important roles in the prevention of age-related diseases. SIRTs can enhance the osteogenic potential and osteoblastic activity of bone marrow mesenchymal stromal cells not only by enhancing PGC-1α, FOXO3, SOD2, and oxidative phosphorylation, but also by anti-aging and reducing mitochondrial autophagy. SIRT3 is able to upregulate antioxidant enzymes to exert an inhibitory effect on osteoclasts, however, it has been shown that the inflammatory cascade response can in turn increase SIRT3 and inhibit osteoclast differentiation through the AMPK-PGC-1β pathway. SIRT3 plays an important role in different types of osteoporosis by affecting osteoblasts, osteoclasts, and bone marrow mesenchymal cells. In this review, we discuss the classification and physiological functions of SIRTs, the effects of SIRT3 on OCs osteoblasts, and BMSCs, and the roles and mechanisms of SIRT3 in different types of OP, such as diabetic OP, glucocorticoid-induced OP, postmenopausal OP, and senile OP.

Expression heterogeneity, tumor immune characteristics and the prognosis effects of OPRL1 in patients with tumors: a pan-cancer study combined with bioinformation analyses and in vitro validation

PurposeOpioids are currently the most frequently prescribed analgesics in clinical practice. However, their effect on cancer progression remains a topic of debate. Opioid receptors (ORs) are present in various types of tumor cells and their expression levels vary depending on the type of tumor. This study aims to explore and preliminarily characterize the association between four different ORs (μ, δ, κ, and nociception/orphanin FQ peptide receptor) and the prognosis of different types of tumors for comparison, with a focus on nociception/ orphanin FQ peptide receptor.MethodsThe expression levels of four ORs in normal tissues and immune cells were obtained from Human Protein Atlas (HPA) RNA-seq dataset, Monaco dataset, and Consensus dataset. Pan-cancer analysis was performed using the The Cancer Genome Atlas (TCGA) dataset, which included the expression of four ORs in different cancer types, significant copy-number alterations (sCNA), gene mutations of the four ORs, survival analysis, co-expression genes analysis, functional enrichment analyses, and correlations between ORs and immune cell infiltration levels. Based on the results of bioinformatic analysis, we selected 10 cancer cell lines for validation in vitro using specific agonists for the four ORs.ResultsOPRL1 (opioid related nociceptin receptor 1 gene) exhibited the highest abundance across different types of cancers, while OPRM1 (opioid receptor mu 1 gene) and OPRD1 (opioid receptor delta 1 gene) were barely detectable in multiple cancer types. Pan-cancer survival analysis revealed the overall worse/better prognosis of the four ORs in certain cancer types. Elevated levels of OPRM1 appear to be associated with poorer outcomes in breast invasive carcinoma and kidney renal clear cell carcinoma. Elevated OPRD1 levels are connected to worsen outcomes in kidney renal clear cell carcinoma and liver hepatocellular carcinoma, but better prognosis in bladder urothelial carcinoma. Increased OPRK1 (opioid receptor kappa 1 gene) expression is linked to a poorer prognosis in kidney renal papillary cell carcinoma. Furthermore, high OPRL1 expression relates to worse outcomes in bladder urothelial carcinoma and liver hepatocellular carcinoma, but better outcomes in breast invasive carcinoma and pancreatic adenocarcinoma. Functional enrichment analyses found that immune-related pathways were enriched in OPRK1 and OPRL1, with OPRL1 exhibiting the highest correlation with immune cell infiltration. Different effects on cell growth, migration, and invasion were observed in different cancer types upon the administration of agonists for the four ORs.ConclusionOPRL1 may play a vital role in monocytes and regulating the immune response and tumor-infiltrating macrophages. Due to its high abundance in different types of tumors, it may hold greater clinical significance for oncology patients. OPRK1 also participates in immune-related pathways. OPRL1 could potentially serve as therapeutic targets for different types of cancers.Graphical

Abstract B017: VCP extracts the chromatin remodeler SNF2H from nascent DNA to stabilize stressed replication forks

Abstract Valosin-containing protein (VCP) is an evolutionarily conserved AAA+ ATPase which plays pleiotropic roles in global proteostasis by extracting polyubiquitinated proteins from various cellular organelles and structures and facilitating their turnover. Our recent work demonstrated that nuclear VCP activity during DNA damage response specifically depends on ATM/ATR/DNA-PK-mediated Ser784 phosphorylation. Ser784phosphorylation increases VCP ability to facilitate chromatin-associated protein degradation and is required for DNA repair, checkpoint signaling, and cell survival. Clinically, high nuclear pSer784-VCP levels are significantly associated with poor survival outcome among chemotherapy-treated breast and pancreatic cancer patients. Thus, pSer784-VCP is a broadly important and therapeutically relevant genome stabilizer. Here, we focused specifically on the role of pSer784-VCP in DNA replication fork stability during stress, a known source of DNA damage if not properly regulated. By performing single-molecule DNA fiber analysis using human cell lines with genetic gain and loss-of-function of VCP, we observed that VCP protects nascent DNA from hydroxyurea (HU)-induced over-resection and this activity requires Ser784 phosphorylation. Using proximity ligation assay (PLA), we detected HU-induced pSer784-VCP on nascent DNA, suggesting that it may protect stressed forks by extracting functionally important regulators. Consistent with this theory, we detected an interaction of pSer784-VCP with SNF2H, a nucleosome-sliding enzyme which we recently found essential for nascent DNA over-resection at unprotected forks. In support of the hypothesis that SNF2H is a novel substrate of pSer784-VCP at stressed forks, we observed SNF2H retention on nascent DNA upon VCP knockdown in HU-treated cells, and the functional rescue of SNF2H retention by VCP re-expression requires Ser784phosphorylation. In support of their epistatic relationship, SNF2H depletion fully rescued fork over-resection caused by VCP loss. Similarly, blocking fork reversal by depleting SMARCAL1 or FBH1 also rescued fork over-resection caused by VCP loss. Importantly, mutating the ATPase activity of SNF2H abolished its ability to promote fork over-resection, suggesting that nucleosome remodeling by SNF2H underlies its effect on fork stability and may be a key molecular event enabling fork reversal upstream of fork degradation. Collectively, our data suggest that pSer784-VCP is a previously unrecognized stabilizer of stressed DNA replication forks, and it does so at least in part via its physical extraction of SNF2H from nascent DNA and the consequent attenuation of nucleosome remodeling needed for fork reversal and over-resection. More experiments are currently underway to further dissect the mechanistic aspects of this working model as well as to evaluate the potential of developing pSer784-VCP into a clinically relevant chemo-predictive biomarker and chemo-sensitizing target for different types of cancer. Citation Format: Jieya Shao, Mari Iwase, Rong Xu, Shuyang Lin. VCP extracts the chromatin remodeler SNF2H from nascent DNA to stabilize stressed replication forks [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr B017.

Subjective measurement of resolution of image intensifier tubes

Limiting resolution is traditionally defined as a spatial frequency of smallest resolvable element of a resolution target that can be distinguish by a human observer. This definition and measurement method have been criticized in a series of literature sources due to its subjectivity and low repeatability/accuracy. Such criticism looks reasonable as it is commonly known that results of measurement of resolution of the same tubes carried out by several test teams can differ significantly. This paper presents a detail analysis of classical subjective measurement method of limiting resolution of image intensifier tubes implemented by real test systems. The findings show that in spite of a common opinion, subjectivity of measurement is not the main reason for differences of test results carried out by different test teams. The main reasons are differences in performance of optics of test systems, use of resolution targets of different types and polarity, and inherent spatial non-uniformity of performance of image intensifier tubes. The paper also shows that due to spatial non-uniformity it is very difficult to design automatic test systems that could produce the same results as human observers using classical subjective measurement method.

Spectral uncertainty analysis of grassland and its camouflage materials based on land-based hyperspectral images

Abstract Spectral uncertainty is one of the most prominent spectral characteristics of hyperspectral images. Compared to the process of remote sensing hyperspectral imaging, hyperspectral imaging under land-based imaging conditions has the characteristics of variable detection directions, random imaging times, and complex environmental conditions, resulting in increased spectral uncertainty of targets in land-based hyperspectral images. The spectral uncertainty of the target mainly refers to the phenomenon of “Same spectral reflectance but different objects” and “Same object but different spectral reflectance” which poses significant difficulties for subsequent hyperspectral image target detection and recognition. In order to analyze the spectral uncertainty of hyperspectral images in land-based applications and address the issue of spectral uncertainty in similar targets, a spectral uncertainty evaluation index based on standard deviation vector was proposed. For the overall spectral separability between different types of targets, a quantitative index based on Jaccard Distance (JD-SSI) is proposed to measure the spectral separability of different kinds of targets. The experiment focused on grassland and its four typical camouflage materials, analyzing the spectral intra class differences and inter class separability of each target with grassland. It is a fundamental work for studying the spectral characteristics of land-based hyperspectral images, providing a new approach for subsequent spectral band extraction, hyperspectral image classification, and target detection tasks.

A Spatially Controlled Proximity Split Tweezer Switch for Enhanced DNA Circuit Construction and Multifunctional Transduction.

DNA strand displacement reactions are vital for constructing intricate nucleic acid circuits, owing to their programmability and predictability. However, the scarcity of effective methods for eliminating circuit leakages has hampered the construction of circuits with increased complexity. Herein, a versatile strategy is developed that relies on a spatially controlled proximity split tweezer (PST) switch to transduce the biomolecular signals into the independent oligonucleotides. Leveraging the double-stranded rigidity of the tweezer works synergistically with the hindering effect of the hairpin lock, effectively minimizing circuit leakage compared with sequence-level methods. In addition, the freely designed output strand is independent of the target binding sequence, allowing the PST switch conformation to be modulated by nucleic acids, small molecules, and proteins, exhibiting remarkable adaptability to a wide range of targets. Using this platform, established logical operations between different types of targets for multifunctional transduction are successfully established. Most importantly, the platform can be directly coupled with DNA catalytic circuits to further enhance transduction performance. The uniqueness of this platform lies in its design straightforwardness, flexibility, scalable intricacy, and system compatibility. These attributes pave a broad path toward nucleic acid-based development of sophisticated transduction networks, making them widely applied in basic science research and biomedical applications.

Integrative Proteomic Analysis Reveals the Cytoskeleton Regulation and Mitophagy Difference Between Ischemic Cardiomyopathy and Dilated Cardiomyopathy

Ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM) are the two primary etiologies of end-stage heart failure. However, there remains a dearth of comprehensive understanding the global perspective and the dynamics of the proteome and phosphoproteome in ICM and DCM, which hinders the profound comprehension of pivotal biological characteristics as well as differences in signal transduction activation mechanisms between these two major types of heart failure. We conducted high-throughput quantification proteomics and phosphoproteomics analysis of clinical heart tissues with ICM or DCM, which provided us the system-wide molecular insights into pathogenesis of clinical heart failure in both ICM and DCM. Both protein and phosphorylation expression levels exhibit distinct separation between heart failure and normal control heart tissues, highlighting the prominent characteristics of ICM and DCM. By integrating with omics results, Western blots, phosphosite-specific mutation, chemical intervention, and immunofluorescence validation, we found a significant activation of the PRKACA–GSK3β signaling pathway in ICM. This signaling pathway influenced remolding of the microtubule network and regulated the critical actin filaments in cardiac construction. Additionally, DCM exhibited significantly elevated mitochondria energy supply injury compared to ICM, which induced the ROCK1–vimentin signaling pathway activation and promoted mitophagy. Our study not only delineated the major distinguishing features between ICM and DCM but also revealed the crucial discrepancy in the mechanisms between ICM and DCM. This study facilitates a more profound comprehension of pathophysiologic heterogeneity between ICM and DCM and provides a novel perspective to assist in the discovery of potential therapeutic targets for different types of heart failure.

Targeting sphingosine kinase 1 in p53KO thymic lymphoma.

Sphingosine kinase 1 (SK1) is a key sphingolipid enzyme that is upregulated in several types of cancer, including lymphoma which is a heterogenous group of malignancies. Treatment for lymphoma has improved significantly by the introduction of new therapies; however, subtypes with tumor protein P53 (p53) mutations or deletion have poor prognosis, making it critical to explore new therapeutic strategies in this context. SK1 has been proposed as a therapeutic target in different types of cancer; however, the effect of targeting SK1 in cancers with p53 deletion has not been evaluated yet. Previous work from our group suggests that loss of SK1 is a key event in mediating the tumor suppressive effect of p53. Employing both genetic and pharmacological approaches to inhibit SK1 function in Trp53KO mice, we show that targeting SK1 decreases tumor growth of established p53KO thymic lymphoma. Inducible deletion of Sphk1 or its pharmacological inhibition drive increased cell death in tumors which is accompanied by selective accumulation of sphingosine levels. These results demonstrate the relevance of SK1 in the growth and maintenance of lymphoma in the absence of p53 function, positioning this enzyme as a potential therapeutic target for the treatment of tumors that lack functional p53.

Teenage pregnancy and Violence: A current public health problem.

Every year, an estimated 21 million teenage girls aged 15–19 years become pregnant, and at least 777,000 births occur to adolescent girls younger than 15 years in developing countries. 1 Latin America has the world's second highest teenage pregnancy rate, with about 18 % of births to mothers under 20. Each year, one and a half million adolescent women aged 15 and 19 have babies in the region.2 Injuries, Violence, self-harm, and maternal conditions are the leading causes of death among adolescents and young adults. Pregnant teenagers are prime targets of different types of Violence. Violence and adolescent pregnancy are public health problems and risk factors for maternal and fetal morbidity and mortality. The United Nations Sustainable Development Cooperation Framework (UNSDCF) prioritizes ending Violence against girls and child marriage.3,4

Analysis of micron size space debris impacts on materials: comparison of ground-based testing and in-flight results

A new experimental facility has been built in ESA-ESTEC to simulate orbital debris impacts. The facility uses a laser driven flyer plate technique to accelerate small aluminium particles to high velocities. The area of interest is the population of small sized debris objects (<700 μm) with impact velocities up to 10 kms-1. Impact damage has been observed on different types of thin foils, but fragmentation is very noticeable, both at impact and at the creation of the flyer. The size distribution seems random and velocities between 1 and 6 kms-1 have been established. Results from different types of targets are presented, including a new type of flyer plate target. The flyer plate method appears to be promising and the new targets show a limited fragmentation on each laser beam shot compared to the others.

Remote Sensing Image Classification using Machine Learning Algorithms

Abstract: The classification of images can be influenced by various factors. When multiple sources of data are available for earth exploration, extracting valuable information or achieving effective outcomes can be both fascinating and challenging. Remote Sensing Images (RSI) classification plays a crucial role in remote sensing applications and serves as the foundation for efficient classification. Various classifiers are employed to classify different types of targets in remote sensing images. Achieving improved target classification is of utmost importance in both military and civilian domains. This paper focuses on summarizing advanced approaches used to enhance classification accuracy. The findings indicate that the Convolutional Neural Network surpasses all other conventional classification methods.