Pancreatic ductal adenocarcinoma (PDAC) patients frequently suffer from undetected micro-metastatic disease. This clinical situation would greatly benefit from additional investigation. Therefore, we set out to identify key signalling events that drive metastatic evolution from the pancreas. We searched for a gene signature that discriminate localised PDAC from confirmed metastatic PDAC and devised a preclinical protocol using circulating cell-free DNA (cfDNA) as an early biomarker of micro-metastatic disease to validate the identification of key signalling events. An unbiased approach identified, amongst actionable markers of disease progression, the PI3K pathway and a distinctive PI3Ka activation signature as predictive of PDAC aggressiveness and prognosis. Pharmacological or tumour-restricted genetic PI3Kaselective inhibition prevented macro-metastatic evolution by hindering tumoural cell migratory behaviour independently of genetic alterations. We found that PI3Ka inhibition altered the quantity and the species composition of the produced lipid second messenger PIP 3 , with a selective decrease of C36:2 PI-3,4,5-P 3 . Tumoural PI3Ka inactivation prevented the accumulation of protumoural CD206-positive macrophages in the tumour-adjacent tissue. Tumour cell-intrinsic PI3Ka promotes pro-metastatic features that could be pharmacologically targeted to delay macrometastatic evolution.
Fatty liver (FL) is one of the risk factors for acute pancreatitis and is also indicative of a worse prognosis as compared to acute pancreatitis without fatty liver (AP). The aim of the present study was to analyze, at the hepatic level, the differentially expressed genes (DEGs) between acute pancreatitis with fatty liver (APFL) rats and AP rats. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses of these DEGs indicated that PPARα signalling pathway and fatty acid degradation pathway may be involved in the pathological process of APFL, which indicated that fatty liver may aggravate pancreatitis through these pathways. Moreover, the excessive activation of JAK/STAT signaling pathway and toll-like receptor signaling pathway was also found in APFL group as shown in heat map. In conclusion, the inhibition of PPARα signaling pathway and the fatty acid degradation pathway may lead to the further disorder of lipid metabolism, which can aggravate pancreatitis.
Pancreatic ductal adenocarcinoma (PDAC) patients frequently suffer from undetected micrometastatic disease. This clinical situation would greatly benefit from additional investigation. Therefore, we set out to identify key signalling events that drive metastatic evolution from the pancreas.We researched a gene signature that could discriminate localised PDAC from confirmed metastatic PDAC and devised a preclinical protocol using circulating cell-free DNA (cfDNA) as an early biomarker of micro-metastatic disease to validate the identification of key signalling events.Amongst actionable markers of disease progression, the PI3K pathway and a distinctive PI3Kα activation signature predict PDAC aggressiveness and prognosis. Pharmacological or tumour-restricted genetic PI3Kα-selective inhibition prevented macro-metastatic evolution by inhibiting tumoural cell migratory behaviour independently of genetic alterations. We found that PI3Kα inhibition altered the quantity and the species composition of the lipid second messenger PIP3 produced, with selective reduction of C36:2 PI-3,4,5-P3. PI3Kα inactivation prevented the accumulation of protumoural CD206-positive macrophages in the tumour-adjacent tissue.Tumour-cell intrinsic PI3Kα therefore promotes pro-metastatic features that could be pharmacologically targeted to delay macro-metastatic evolution.The paper explainedPROBLEM Pancreatic cancer is one of the most lethal solid cancers characterised by rapid progression after primary tumour detection by imaging. Key signalling events that specifically drives this rapid evolution into macro-metastatic disease are so far poorly understood.RESULT With two unbiased approaches to patient data analysis, higher PI3K pathway and more specifically higher PI3Kα activation signature can now be identified in the most aggressive pancreatic cancer primary tumours, that lead to earlier patient death. Our in vitro data showed that PI3Kα is a major positive regulator of tumour cell escape from the primary tumour: tumour-intrinsic PI3Kα activity enables actin cytoskeleton remodelling to escape the pancreatic tumour. We chose to use two preclinical models of pancreatic cancer to validate that PI3Kα is a target for delaying evolution of PDAC. The first one mimicked pancreatic patient micrometastatic disease that is undetected by echography and consisted in treating mice presenting echography detected primary tumours combined with increased circulating DNA as a blood biomarker of the most aggressive tumours. The second model consisted in studying the tumour cell implantation and their early proliferation in metastatic organ after injection in blood. We treated both preclinical models with a clinically relevant PI3K α-selective inhibitor (BYL-719/Alpelisib), that is currently being tested in pancreatic cancer patients (without any patient selection). We found that PI3Kα activity drives evolution of micrometastatic disease towards macro-metastatic stage in both models: inhibition of PI3Kα delayed primary tumour and micro-metastasis evolution. Finally, PI3Kα activity increases protumoural characteristics in peritumoural immune cells via tumour cell-intrinsic cytokine production that could facilitate metastatic evolution.IMPACT Circulating tumour DNA represents a strong independent biomarker linked to relapse and poor survival in solid cancer patients. A clinical study in resected PDAC patients with micrometastatic disease characterised by high circulating tumoural DNA levels is needed to assess if PI3Kα-selective inhibitors significantly delay metastatic progression and death.Graphical AbstractPancreatic ductal adenocarcinoma requires tumour-intrinsic PI3Kα activity to accelerate inflammatory metastatic disease.Biorender illustration.
Rail transportation is regarded as a reliable, quick, and secure mode of transportation. The wheel-rail contact interaction is crucial to the railway operation since it is responsible for supporting, traction, braking, and steering of railway vehicles. Improper wheel-rail interactions may produce or exacerbate wheel-rail interface issues such as rolling contact fatigue (RCF) and wear, which can threaten the vehicle’s running safety and stability. A review of the evolution and recent literature on wheel-rail contact mechanics and tribology is presented here. Topics covered include the basics of wheel-rail contact problem and methodologies for modeling both the normal contact (Hertzian and non-Hertzian) and tangential contact (Kalker’s theories including CONTACT and FASTSIM algorithms, Polach’s theory, USETAB program, etc.). The paper also reviewed various effects of contaminants and environmental conditions (water, leaves, sand, temperature, humidity, etc.) in wheel-rail contact. Various wheel-rail empirical adhesion models like the Water-induced low adhesion creep force model (WILAC) model and adhesion models based on elastohydrodynamic lubrication (EHL) theory (Greenwood-Tripp [GT] and Greenwood-Williamson [GW] models) are also reviewed. Lastly, the paper discusses the need and challenges for developing and integrating the wheel-rail non-Hertz contact model and adhesion model, as well as open areas for further research.
Identifying and detecting the loading size of heavy-duty railway freight cars is crucial in modern railway freight transportation. Due to contactless and high-precision characteristics, light detection and ranging-assisted unmanned aerial vehicle stereo vision detection is significant for ensuring out-of-gauge freight transportation security. However, the precision of unmanned aerial vehicle flight altitude control and feature point mismatch significantly impact stereo matching, thus affecting the accuracy of railway freight measurement. In this regard, the altitude holding control strategy equipped with a laser sensor and SURF_rBRIEF image feature extraction and matching algorithm are proposed in this article for railway freight car loading size measurement. Moreover, an image segmentation technique is used to quickly locate and dismantle critical parts of freight cars to achieve a rapid 2-dimension reconstruction of freight car contours and out-of-gauge detection. The robustness of stereo matching has been demonstrated by external field experiment. The precision analysis and fast out-of-gauge judgment confirm the measurement accuracy and applicability.
To address the issues of not accurately identifying ice types and thickness in current fiber-optic ice sensors, in this paper, we design a novel fiber-optic ice sensor based on the reflected light intensity modulation method and total reflection principle. The performance of the fiber-optic ice sensor was simulated by ray tracing. The low-temperature icing tests validated the performance of the fiber-optic ice sensor. It is shown that the ice sensor can detect different ice types and the thickness from 0.5 to 5 mm at temperatures of −5 °C, −20 °C, and −40 °C. The maximum measurement error is 0.283 mm. The proposed ice sensor provides promising applications in aircraft and wind turbine icing detection.
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