Atomistic Characterization of Healthy and Damaged Hair Surfaces: A Molecular Dynamics Simulation Study of Fatty Acids on Protein Layer.

Amid the bourgeoning demand for in-silico designed, environmentally sustainable, and highly effective hair care formulations, a growing interest is evident in the exploration of realistic computational model for the hair surface. In this work, we present an atomistic model for the outermost layer of the hair surface derived through molecular dynamics simulations, which comprises 18-Methyleicosanoic acid (18-MEA) fatty acid chains covalently bound onto the keratin-associated protein 10-4 (KAP10-4) at a spacing distance of ~1 nm. Remarkably, this hair surface model facilitates the inclusion of free fatty acids (free 18-MEA) into the gaps between chemically bound 18-MEA chains, up to a maximum number that results in a packing density of 0.22 nm2 per fatty acid molecule, consistent with the optimal spacing identified through free energy analysis. Atomistic insights are provided for the organization of fatty acid chains, structural features, and interaction energies on protein-inclusive hair surface models with varying amounts of free 18-MEA (FMEA) depletion, as well as varying degrees of anionic cysteic acid from damaged bound 18-MEA (BMEA), under both dry and wet conditions. In the presence of FMEA and water, the fatty acid chains in a pristine hair surface prefers to adopt a thermodynamically favored extended chain conformation, forming a thicker protective layer (~3 nm) on the protein surface. Our simulation results reveal that, while the depletion of FMEA can induce a pronounced impact on the thickness, tilt angle, and order parameters of fatty acid chains, the removal of BMEA has a marked effect on water penetration. There is a "sweet spot" spacing between the 18-MEA whereby damaged hair surface properties can be reinstated by replenishing FMEA. Through the incorporation of the protein layer and free fatty acids, the hair surface models presented in this study enables a realistic representation of the intricate details within the hair epicuticle, facilitating a molecular scale assessment of surface properties during the formulation design process.

Aedes albopictus colonies from different geographic origins differ in their sleep and activity levels but not in the time of peak activity.

Mosquitoes occupy a wide range of habitats where they experience various environmental conditions. The ability of some species, such as the tiger mosquito, Aedes albopictus, to adapt to local conditions certainly contributes to their invasive success. Among traits that remain to be examined, mosquitoes' ability to time their activity with that of the local host population has been suggested to be of significant epidemiological importance. However, whether different populations display heritable differences in their chronotype has not been examined. Here, we compared laboratory strains originating from eight populations from three continents, monitored their spontaneous locomotor activity patterns and analysed their sleep-like states. Overall, all strains showed conserved diurnal activity concentrated in the hours preceding the crepuscule. Similarly, they all showed increased sleep levels during the morning and night hours. However, we observed strain-specific differences in the activity levels at each phase of the day. We also observed differences in the fraction of time that each strain spends in a sleep-like state, explained by variations in the sleep architecture across strains. Human population density and the latitude of the site of the geographic origin of the tested strain showed significant effects on sleep and activity patterns. Altogether, these results suggest that Ae. albopictus mosquitoes adapt to local environmental conditions via heritable adaptations of their chronotype.

Intra-species quantification reveals differences in activity and sleep levels in the yellow fever mosquito, Aedes aegypti.

Aedes aegypti is an important mosquito vector of human disease with a wide distribution across the globe. Climatic conditions and ecological pressure drive differences in the biology of several populations of this mosquito species, including blood-feeding behaviour and vector competence. However, no study has compared activity and/or sleep among different populations/lineages of Ae. aegypti. Having recently established sleep-like states in three mosquito species with observable differences in timing and amount of sleep among species, we investigated differences in activity and sleep levels among 17 Ae. aegypti lines drawn from both its native range in Africa and its invasive range across the global tropics. Activity monitoring indicates that all the lines show consistent diurnal activity, but significant differences in activity level, sleep amount, number of sleep bouts and bout duration were observed among the lines. The variation in day activity was associated with differences in host preference and ancestry for the lineages collected in Africa. This study provides evidence that the diurnal sleep and activity profiles for Ae. aegypti are consistent, but there are significant population differences for Ae. aegypti sleep and activity levels and interactions with host species may significantly impact mosquito activity.

Elucidating the Role of Interfacial Hydrogen Bonds on Glass Transition Temperature Change in a Poly(Vinyl Alcohol)/SiO2 Polymer-Nanocomposite by Noncovalent Interaction Characterization and Atomistic Molecular Dynamics Simulations.

A thorough experimental investigation of polymer-glass transition temperature (Tg ) is performed on poly(vinyl alcohol) (PVA) and fumed silica nanoparticle (SiNP) composite. This is done together with atomistic molecular dynamics simulations of PVA systems in contact with bare and fully hydroxylated silica. Experimentally, PVA-SiNP composites are prepared by simple solution casting from aqueous solutions followed by its characterization using Fourier-transform infrared spectroscopy (FTIR), dynamic mechanical analysis (DMA), and dynamic scanning calorimetry (DSC). Both theoretical and experimentally deduced Tg are correlated with the presence of hydrogen bonding interactions involving OH functionality present on the surface of SiNP and along PVA polymer backbone. Further deconvolution of FTIR data show that inter-molecular hydrogen bonding present between PVA and SiNP surface is directly responsible for the increase in Tg . SiNP filler and PVA matrix ratio is also optimized for a desired Tg increase. An optimal loading of SiNP exists, in order to yield the maximum Tg increase arising from the competition between hydrogen bonding and crowding effect of SiNP.

Profilin-1 deficiency leads to SMAD3 upregulation and impaired 3D outgrowth of breast cancer cells.

BACKGROUND: Adhesion-mediated activation of FAK/ERK signalling pathway, enabled by the formation of filopodial protrusions (FLP), has been shown to be an important event for triggering of dormancy-to-proliferation switch and metastatic outgrowth of breast cancer cells (BCC). We studied the role of actin-binding protein profilin1 (Pfn1) in these processes. METHODS: Quantitative immunohistochemistry (IHC) of BC tissue microarray (TMA) and survival analyses of curated transcriptome datasets of BC patients were performed to examine Pfn1's association with certain clinicopathological features. FLP formation and single cell outgrowth of BCC were assessed using a 3D matrigel culture that accurately predicts dormant vs metastatic outgrowth phenotypes of BCC in certain microenvironment. Gene expression studies were performed to identify potential biological pathways that are perturbed under Pfn1-depleted condition. RESULTS: Lower Pfn1 expression is correlated with lower nuclear grade of breast tumours and longer relapse-free survival of BC patients. Pfn1 depletion leads to defects in FLP and outgrowth of BCC but without impairing either FAK or ERK activation. Guided by transcriptome analyses, we further showed that Pfn1 depletion is associated with prominent SMAD3 upregulation. Although knockdown and overexpression experiments revealed that SMAD3 has an inhibitory effect on the outgrowth of breast cancer cells, SMAD3 knockdown alone was not sufficient to enhance the outgrowth potential of Pfn1-depleted BCC suggesting that other proliferation-regulatory pathways in conjunction with SMAD3 upregulation may underlie the outgrowth-deficient phenotype of BCC cells upon depletion of Pfn1. CONCLUSION: Overall, these data suggest that Pfn1 may be a novel biomarker for BC recurrence and a possible target to reduce metastatic outgrowth of BCC.

Induced pluripotent stem cells model personalized variations in liver disease resulting from α1-antitrypsin deficiency.

UNLABELLED: In the classical form of α1-antitrypsin deficiency (ATD), aberrant intracellular accumulation of misfolded mutant α1-antitrypsin Z (ATZ) in hepatocytes causes hepatic damage by a gain-of-function, "proteotoxic" mechanism. Whereas some ATD patients develop severe liver disease (SLD) that necessitates liver transplantation, others with the same genetic defect completely escape this clinical phenotype. We investigated whether induced pluripotent stem cells (iPSCs) from ATD individuals with or without SLD could model these personalized variations in hepatic disease phenotypes. Patient-specific iPSCs were generated from ATD patients and a control and differentiated into hepatocyte-like cells (iHeps) having many characteristics of hepatocytes. Pulse-chase and endoglycosidase H analysis demonstrate that the iHeps recapitulate the abnormal accumulation and processing of the ATZ molecule, compared to the wild-type AT molecule. Measurements of the fate of intracellular ATZ show a marked delay in the rate of ATZ degradation in iHeps from SLD patients, compared to those from no liver disease patients. Transmission electron microscopy showed dilated rough endoplasmic reticulum in iHeps from all individuals with ATD, not in controls, but globular inclusions that are partially covered with ribosomes were observed only in iHeps from individuals with SLD. CONCLUSION: iHeps model the individual disease phenotypes of ATD patients with more rapid degradation of misfolded ATZ and lack of globular inclusions in cells from patients who have escaped liver disease. The results support the concept that "proteostasis" mechanisms, such as intracellular degradation pathways, play a role in observed variations in clinical phenotype and show that iPSCs can potentially be used to facilitate predictions of disease susceptibility for more precise and timely application of therapeutic strategies.

A phosphotyrosine switch for cargo sequestration at clathrin-coated buds.

The AP-2 clathrin adaptor complex oversees endocytic cargo selection in two parallel but independent manners. First, by physically engaging peptide-based endocytic sorting signals, a subset of clathrin-dependent transmembrane cargo is directly collected into assembling buds. Synchronously, by interacting with an assortment of clathrin-associated sorting proteins (CLASPs) that independently select different integral membrane cargo for inclusion within the incipient bud, AP-2 handles additional cargo capture indirectly. The distal platform subdomain of the AP-2 ß2 subunit appendage is a privileged CLASP-binding surface that recognizes a cognate, short α-helical interaction motif. This signal, found in the CLASPs ß-arrestin and the autosomal recessive hypercholesterolemia (ARH) protein, docks into an elongated groove on the ß2 appendage platform. Tyr-888 is a critical constituent of this spatially confined ß2 appendage contact interface and is phosphorylated in numerous high-throughput proteomic studies. We find that a phosphomimetic Y888E substitution does not interfere with incorporation of expressed ß2-YFP subunit into AP-2 or alter AP-2 deposition at surface clathrin-coated structures. The Y888E mutation does not affect interactions involving the sandwich subdomain of the ß2 appendage, indicating that the mutated appendage is folded and operational. However, the Y888E, but not Y888F, switch selectively uncouples interactions with ARH and ß-arrestin. Phyogenetic conservation of Tyr-888 suggests that this residue can reversibly control occupancy of the ß2 platform-binding site and, hence, cargo sorting.

Predicting the Antifungal Activity of Small Organic Compounds on Aspergillus niger Mold using Molecular Dynamics Simulations.

Atomistic models of the plasma membrane of the pathogenic mold Aspergillus niger are developed. These models are described with an empirical molecular mechanical (MM) force field in combination with molecular dynamics (MD) simulations. The solvated plasma membrane models are brought into contact with 35 small organic compounds to observe their impact on a variety of membrane properties. All compounds are added at a constant total mass of 1% of the membrane mass. In addition, the ability of these compounds to inhibit the pathogenic cell growth of mold has been measured. Diffusion of compounds into the membrane model is readily observed during MD simulations. Changes in membrane properties found in simulations are not found to correlate with measured antifungal activities of compounds, suggesting that MD simulations of up to 1 µs are not sufficiently long to adequately describe compound-induced membrane disruption. However, properties related to the position and orientation of compounds relative to the membrane surface as well as hydrogen bonds formed between the compounds and the membrane show clear trends that correlate well with measured activities. A combination of these properties enables an activity prediction of compounds in good agreement with measurements. Activity is found predominantly for compounds that can be decomposed into a single continuous hydrophobic and hydrophilic moiety. Such active compounds can be energetically inserted most favorably into the membrane. These insertions destabilize the membrane by disrupting the internal membrane hydrogen bond network and by sliding between neighboring lipids, thereby separating them.

Thermal tolerance of mosquito eggs is associated with urban adaptation and human interactions.

Climate change is expected to profoundly affect mosquito distributions and their ability to serve as vectors for disease, specifically with the anticipated increase in heat waves. The rising temperature and frequent heat waves can accelerate mosquito life cycles, facilitating higher disease transmission. Conversely, higher temperatures could increase mosquito mortality as a negative consequence. Warmer temperatures are associated with increased human density, suggesting a need for anthropophilic mosquitoes to adapt to be more hardy to heat stress. Mosquito eggs provide an opportunity to study the biological impact of climate warming as this stage is stationary and must tolerate temperatures at the site of female oviposition. As such, egg thermotolerance is critical for survival in a specific habitat. In nature, Aedes mosquitoes exhibit different behavioral phenotypes, where specific populations prefer depositing eggs in tree holes and prefer feeding non-human vertebrates. In contrast, others, particularly human-biting specialists, favor laying eggs in artificial containers near human dwellings. This study examined the thermotolerance of eggs, along with adult stages, for Aedes aegypti and Ae. albopictus lineages associated with known ancestry and shifts in their relationship with humans. Mosquitoes collected from areas with higher human population density, displaying increased human preference, and having a human-associated ancestry profile have increased egg viability following high-temperature stress. Unlike eggs, thermal tolerance among adults showed no significant correlation based on the area of collection or human-associated ancestry. This study highlights that the egg stage is likely critical to mosquito survival when associated with humans and needs to be accounted when predicting future mosquito distribution.

Aedes albopictus colonies from different geographic origins differ in their sleep and activity levels but not in the time of peak activity.

Mosquitoes occupy a wide range of habitats where they experience various environmental conditions. The ability of some species, such as the tiger mosquito, Aedes albopictus, to adapt to local conditions certainly contributes to their invasive success. Among traits that remain to be examined, mosquitoes' ability to time their activity with that of the local host population has been suggested to be of significant epidemiological importance. However, whether different populations display heritable differences in their chronotype has not been examined. Here, we compared laboratory strains originating from 8 populations from 3 continents, monitored their spontaneous locomotor activity patterns, and analyzed their sleep-like states. Overall, all strains showed conserved diurnal activity concentrated in the hours preceding the crepuscule. Similarly, they all showed increased sleep levels during the morning and night hours. However, we observed strain-specific differences in the activity levels at each phase of the day. We also observed differences in the fraction of time that each strain spends in a sleep-like state, explained by variations in the sleep architecture across strains. Human population density and the latitude of the site of geographic origin of the tested strain showed significant effects on sleep and activity patterns. Altogether, these results suggest that Ae. albopictus mosquitoes adapt to local environmental conditions via heritable adaptations of their chronotype.

Inhibition of Human Colorectal Cancer by a Natural Product 7-Acetylhorminone and Interactions with BSA/HSA: Multispectral Analysis and In Silico and In Vitro Studies.

We have semi-synthesized a natural product 7-acetylhorminone from crude extract of Premna obtusifolia (Indian headache tree), which is active against colorectal cancer after probation through computational screening methods as it passed through the set parameters of pharmacokinetics (most important nonblood-brain barrier permeant) and drug likeliness (e.g., Lipinski's, Ghose's, Veber's rule) which most other phytoconstituents failed to pass combined with docking with EGFR protein which is highly upregulated in the colorectal carcinoma cell. The structure of 7-acetylhorminone was confirmed by single crystal X-ray diffraction studies and 1H NMR, 13C NMR, and COSY studies. To validate the theoretical studies, first, in vitro experiments were carried out against human colorectal carcinoma cell lines (HCT116) which revealed the potent cytotoxic efficacy of 7-acetylhorminone and verified preliminary investigation. Second, the drugability of 7-acetylhorminone interaction with serum albumin proteins (HSA and BSA) is evaluated both theoretically and experimentally via steady-state fluorescence spectroscopic studies, circular dichroism, isothermal titration calorimetry, and molecular docking. In summary, this study reveals the applicability of 7-acetylhorminone as a potent drug candidate or as a combinatorial drug against colorectal cancer.

Reprogrammable, Sustainable, and 3D-Printable Cellulose Hydroplastic.

Modern human societies are highly dependent on plastic materials, however, the bulk of them are non-renewable commodity plastics that cause pollution problems and consume large amounts of energy for their thermal processing activities. In this article, a sustainable cellulose hydroplastic material and its composites, that can be shaped repeatedly into various 2D/3D geometries using just water are introduced. In the wet state, their high flexibility and ductility make it conducive for the shaping to take place. In the ambient environment, the wet hydroplastic transits spontaneously into rigid materials with its intended shape in a short time of <30 min despite a thickness of hundreds of microns. They also possess humidity resistance and are structurally stable in highly humid environments. Given their excellent mechanical properties, geometry reprogrammability, bio-based, and biodegradable nature, cellulose hydroplastic poses as a sustainable alternative to traditional plastic materials and even "green" thermoplastics. This article also demonstrates the possibility of 3D-printing these hydroplastics and the potential of employing them in electronics applications. The demonstrated hydroshapable structural electronic components show capability in performing electronic functions, load-bearing ability and geometry versatility, which are attractive features for lightweight, customizable and geometry-unique electronic devices.

Multiple bouts of blood feeding in mosquitoes allow prolonged survival and are predicted to increase viral transmission during drought.

Survival through periods of drought is critical for mosquitoes to reside in semi-arid regions with humans, but water sources may be limited. Previous studies have shown that dehydrated mosquitoes will increase blood feeding propensity, but how this would occur over extended dry periods is unknown. Following a bloodmeal, prolonged exposure to dry conditions increased secondary blood feeding in mosquitoes by nearly two-fold, and chronic blood feeding allowed mosquitoes to survive twenty days without access to water sources. This refeeding did not alter the number of eggs generated, suggesting this refeeding is for hydration and nutrient replenishment. Exposure to desiccating conditions following a bloodmeal resulted in increased activity, decreased sleep levels, and prompted a return of CO2 sensing before egg deposition. The increased blood feeding during the vitellogenic stage and higher survival during dry periods are predicted to increase pathogen transmission and explain the elevated levels of specific arbovirus cases during dry conditions. These results solidify our understanding of the role of dry periods on mosquito blood feeding and how mosquito dehydration contributes to vectorial capacity and disease transmission dynamics.

A wavelet neural operator based elastography for localization and quantification of tumors.

BACKGROUND AND OBJECTIVES: The application of intelligent imaging techniques and deep learning in the field of computer-aided diagnosis and medical imaging have improved and accelerated the early diagnosis of many diseases. Elastography is an imaging modality where an inverse problem is solved to extract the elastic properties of tissues and subsequently mapped to anatomical images for diagnostic purposes. In the present work, we propose a wavelet neural operator-based approach for correctly learning the non-linear mapping of elastic properties directly from measured displacement field data. METHODS: The proposed framework learns the underlying operator behind the elastic mapping and thus can map any displacement data from a family to the elastic properties. The displacement fields are first uplifted to a high-dimensional space using a fully connected neural network. On the lifted data, certain iterations are performed using wavelet neural blocks. In each wavelet neural block, the lifted data are decomposed into low, and high-frequency components using wavelet decomposition. To learn the most relevant patterns and structural information from the input, the neural network kernels are directly convoluted with the outputs of the wavelet decomposition. Thereafter the elasticity field is reconstructed from the outputs from convolution. The mapping between the displacement and the elasticity using wavelets is unique and remains stable during training. RESULTS: The proposed framework is tested on several artificially fabricated numerical examples, including a benign-cum-malignant tumor prediction problem. The trained model was also tested on real Ultrasound-based elastography data to demonstrate the applicability of the proposed scheme in clinical usage. The proposed framework reproduces the highly accurate elasticity field directly from the displacement inputs. CONCLUSIONS: The proposed framework circumvents different data pre-processing and intermediate steps utilized in traditional methods, hence providing an accurate elasticity map. The computationally efficient framework requires fewer epochs for training, which bodes well for its clinical usability for real-time predictions. The weights and biases from pre-trained models can also be employed for transfer learning, which reduces the effective training time with random initialization.

Genome sequence of Asaia bogorensis strain SC1 isolated from an Aedes aegypti mosquito crop.

Understanding microbe-host interactions is key to combating disease transmission by mosquitoes. Here, we report the genome sequence of Asaia bogorensis strain SC1 isolated from a human-blood-fed Aedes aegypti mosquito crop. Metabolic pathway characteristics of aerobic respiration were present in the genome, along with multiple putative antibiotic resistance mechanisms.

Designing an Energy-Efficient Transportation Network to Transport Perishable Crops: An Aggregated VRP and X-means Clustering Approach.

Almost all perishable crops deteriorate due to improper and tardy transportation and storage. Vehicle Routing Problem, or VRP, might be of great aid since it takes into account a number of aspects of any transportation and storage issues and optimizes them in such a way as to reduce the overall cost of the carrier. This study attempts to widen the scope of the commonly used VRP model by including traffic and energy consumption features and transforming it into the Aggregated Vehicle Routing Problem (AVRP). Traditional VRP focuses on minimizing distance. Generally, it is unable to find out the optimal number of aggregation points required to serve a system. So, cost optimization of the AVRP approach was designed with two specialized steps. Firstly, the destination data are divided into multiple clusters employing the X-means clustering. And then the best route was found to execute the delivery thus minimizing cost, required time, and carbon footprint. The study was implemented on the Chattogram zone and discovered that the optimal number of aggregation points (AP) required to serve Chattogram is only three namely- AP 1, AP 2, and AP 3. VRP analysis was stretched further with AVRP model using AP 1 and found to reduce the operating cost by 10.96%.

Presence, origins and effect of stable surface hydration on regenerated cellulose for underwater oil-repellent membranes.

HYPOTHESIS: Underwater oil-repellency of polyelectrolyte brushes has been attributed mainly to electric double-layer repulsion forces based on Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. Many non-polyelectrolyte materials also exhibit oil-repellent behaviour, but it is not clear if there exist similar electric double-layer repulsion and if it is the sole mechanism governing their underwater oil-repellency. EXPERIMENTS/SIMULATIONS: In this article, the oil-repellency of highly amorphous cellulose exhibiting is investigated in detail, through experiments and molecular dynamics simulations (MDS). FINDINGS: It was found that the stable surface hydration on regenerated cellulose was due to a combination of long-range electrostatic repulsions (DLVO theory) and short-range interfacial hydrogen bonding between cellulose and water molecules (as revealed by MDS). The presence of a stable water layer of about 200 nm thick (similar to that of polyelectrolyte brushes) was confirmed. Such stable surface hydration effectively separates cellulose surface from oil droplets, resulting in extremely low adhesion between them. As a demonstration of its practicality, regenerated cellulose membranes were fabricated via electrospinning, and they exhibit high oil/water separation efficiencies (including oil-in-water emulsions) as well as self-cleaning ability.

QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors.

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.

AMN directs endocytosis of the intrinsic factor-vitamin B(12) receptor cubam by engaging ARH or Dab2.

Cubam is a multi-ligand receptor involved in dietary uptake of intrinsic factor-vitamin B(12) in the small intestine and reabsorption of various low-molecular-weight proteins (such as albumin, transferrin, apolipoprotein A-I and vitamin D-binding protein) in the kidney. Cubam is composed of two proteins: cubilin and amnionless. Cubilin harbors ligand binding capabilities, while amnionless provides membrane anchorage and potential endocytic capacity via two FXNPXF signals within the cytosolic domain. These signals are similar to the FXNPXY signals found in members of the low-density lipoprotein receptor superfamily, which associate with clathrin-associated sorting proteins, including Disabled-2 (Dab2) and autosomal recessive hypercholesterolemia (ARH), during endocytosis. We therefore investigated the functionality of each amnionless FXNPXF signal and their respective interaction with sorting proteins. By sequential mutation and expression of a panel of amnionless mutants combined with yeast two-hybrid analyses, we demonstrate that the signals are functionally redundant and both are able to mediate endocytosis of cubam through interaction with Dab2 and ARH.

Learning the stress-strain fields in digital composites using Fourier neural operator.

Increased demands for high-performance materials have led to advanced composite materials with complex hierarchical designs. However, designing a tailored material microstructure with targeted properties and performance is extremely challenging due to the innumerable design combinations and prohibitive computational costs for physics-based solvers. In this study, we employ a neural operator-based framework, namely Fourier neural operator (FNO), to learn the mechanical response of 2D composites. We show that the FNO exhibits high-fidelity predictions of the complete stress and strain tensor fields for geometrically complex composite microstructures with very few training data and purely based on the microstructure. The model also exhibits zero-shot generalization on unseen arbitrary geometries with high accuracy. Furthermore, the model exhibits zero-shot super-resolution capabilities by predicting high-resolution stress and strain fields directly from low-resolution input configurations. Finally, the model also provides high-accuracy predictions of equivalent measures for stress-strain fields, allowing realistic upscaling of the results.