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Intestinal absorption is an important contributor to systemic cholesterol homeostasis. Niemann-Pick C1 Like 1 (NPC1L1) assists in the initial step of dietary cholesterol uptake, but how cholesterol moves downstream of NPC1L1 is unknown. We show that Aster-B and Aster-C are critical for nonvesicular cholesterol movement in enterocytes. Loss of NPC1L1 diminishes accessible plasma membrane (PM) cholesterol and abolishes Aster recruitment to the intestinal brush border. Enterocytes lacking Asters accumulate PM cholesterol and show endoplasmic reticulum cholesterol depletion. Aster-deficient mice have impaired cholesterol absorption and are protected against diet-induced hypercholesterolemia. Finally, the Aster pathway can be targeted with a small-molecule inhibitor to manipulate cholesterol uptake. These findings identify the Aster pathway as a physiologically important and pharmacologically tractable node in dietary lipid absorption.

Lipoprotein lipase (LPL), the enzyme that carries out the lipolytic processing of triglyceride-rich lipoproteins (TRLs), is synthesized by adipocytes and myocytes and secreted into the interstitial spaces. The LPL is then bound by GPIHBP1, a GPI-anchored protein of endothelial cells (ECs), and transported across ECs to the capillary lumen. The assumption has been that the LPL that is moved into capillaries remains attached to GPIHBP1 and that GPIHBP1 serves as a platform for TRL processing. In the current studies, we examined the validity of that assumption. We found that an LPL-specific monoclonal antibody (mAb), 88B8, which lacks the ability to detect GPIHBP1-bound LPL, binds avidly to LPL within capillaries. We further demonstrated, by confocal microscopy, immunogold electron microscopy, and nanoscale secondary ion mass spectrometry analyses, that the LPL detected by mAb 88B8 is located within the EC glycocalyx, distant from the GPIHBP1 on the EC plasma membrane. The LPL within the glycocalyx mediates the margination of TRLs along capillaries and is active in TRL processing, resulting in the delivery of lipoprotein-derived lipids to immediately adjacent parenchymal cells. Thus, the LPL that GPIHBP1 transports into capillaries can detach and move into the EC glycocalyx, where it functions in the intravascular processing of TRLs.

GPIHBP1, a protein of capillary endothelial cells (ECs), is a crucial partner for lipoprotein lipase (LPL) in the lipolytic processing of triglyceride-rich lipoproteins. GPIHBP1, which contains a three-fingered cysteine-rich LU (Ly6/uPAR) domain and an intrinsically disordered acidic domain (AD), captures LPL from within the interstitial spaces (where it is secreted by parenchymal cells) and shuttles it across ECs to the capillary lumen. Without GPIHBP1, LPL remains stranded within the interstitial spaces, causing severe hypertriglyceridemia (chylomicronemia). Biophysical studies revealed that GPIHBP1 stabilizes LPL structure and preserves LPL activity. That discovery was the key to crystallizing the GPIHBP1-LPL complex. The crystal structure revealed that GPIHBP1's LU domain binds, largely by hydrophobic contacts, to LPL's C-terminal lipid-binding domain and that the AD is positioned to project across and interact, by electrostatic forces, with a large basic patch spanning LPL's lipid-binding and catalytic domains. We uncovered three functions for GPIHBP1's AD. First, it accelerates the kinetics of LPL binding. Second, it preserves LPL activity by inhibiting unfolding of LPL's catalytic domain. Third, by sheathing LPL's basic patch, the AD makes it possible for LPL to move across ECs to the capillary lumen. Without the AD, GPIHBP1-bound LPL is trapped by persistent interactions between LPL and negatively charged heparan sulfate proteoglycans (HSPGs) on the abluminal surface of ECs. The AD interrupts the HSPG interactions, freeing LPL-GPIHBP1 complexes to move across ECs to the capillary lumen. GPIHBP1 is medically important; GPIHBP1 mutations cause lifelong chylomicronemia, and GPIHBP1 autoantibodies cause some acquired cases of chylomicronemia.

GPIHBP1, an endothelial cell (EC) protein, captures lipoprotein lipase (LPL) within the interstitial spaces (where it is secreted by myocytes and adipocytes) and transports it across ECs to its site of action in the capillary lumen. GPIHBP1's 3-fingered LU domain is required for LPL binding, but the function of its acidic domain (AD) has remained unclear. We created mutant mice lacking the AD and found severe hypertriglyceridemia. As expected, the mutant GPIHBP1 retained the capacity to bind LPL. Unexpectedly, however, most of the GPIHBP1 and LPL in the mutant mice was located on the abluminal surface of ECs (explaining the hypertriglyceridemia). The GPIHBP1-bound LPL was trapped on the abluminal surface of ECs by electrostatic interactions between the large basic patch on the surface of LPL and negatively charged heparan sulfate proteoglycans (HSPGs) on the surface of ECs. GPIHBP1 trafficking across ECs in the mutant mice was normalized by disrupting LPL-HSPG electrostatic interactions with either heparin or an AD peptide. Thus, GPIHBP1's AD plays a crucial function in plasma triglyceride metabolism; it sheathes LPL's basic patch on the abluminal surface of ECs, thereby preventing LPL-HSPG interactions and freeing GPIHBP1-LPL complexes to move across ECs to the capillary lumen.

Due to the new development stage, it is especially important to improve the education quality of private undergraduate universities. As a result, it is a new hot issue for the construction of mechanisms and assessment systems for the quality improvement of private undergraduate education. In this paper, after analyzing and researching the quality of undergraduate education in present-day universities, the mechanism of deep learning is applied to the establishment of the assessment system. Finally, 1082 samples collected from the data center platform of a private university are analyzed as the research object. From the results, the final size of the combined weights of the seven evaluation items constituting the assessment system differed little. They were 12.81%, 15.78%, 15.28%, 14.38%, 12.83%, 12.81%, 15.01%, and 13.27%, respectively. In the comparison of this paper’s method with FAHP+TOPSIS combined evaluation, euclidean map method, and genetic algorithm assignment, the difference between the seven weight values of the Euclidean map method is larger, 5.56%. The evaluation times of the four methods were 41 s, 38 s, 47 s, and 118 s. Compared with the other three methods, the genetic algorithm assignment took the most time.

University is an inevitable product of a city’s development to a specific stage. In different social environments and historical stages, universities always develop symbiotically with cities, and the integration of the higher education system and emerging technologies can accelerate the regional economic development of universities and cities. Based on data mining technology, this study uses a neural network algorithm to establish an algorithmic model and sigmoid function as the incentive function to analyze the integration development of the emerging technology industry and university in Dongguan city and provide an optimization path for the integration development of the city and university. The research results show that in the field of scientific and technological research results, the universities in Dongguan City applied for 49,726 patents in 2021 and authorized 25,523, with an efficiency rate of 51.33%. In the area of urban economic development, Dongguan’s GDP in 2021 showed strong momentum, achieving a regional GDP of 108.554 billion yuan, up 8.2% over the previous year.