ATOMISTIC CHARACTERIZATION OF HEALTHY AND DAMAGED HAIR SURFACES: A MOLECULAR DYNAMICS STUDY OF FATTY ACIDS ON PROTEIN LAYER.

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 bonded onto the keratin-associated protein 10-4 (KAP10-4) at a spacing distance of ~ 1 nm. Remarkably, this 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 into 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. 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.

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.

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.

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.

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.

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.

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%.

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.

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.

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.

Dual assessment of transcriptional and metabolomic responses in the American dog tick following exposure to different pesticides and repellents.

The American dog tick, Dermacentor variabilis, is a major pest to humans and animals, serving as a vector to Rickettsia rickettsii, a bacterium responsible for Rocky Mountain spotted fever, and Francisella tularensis, which is responsible for tularemia. Although several tactics for management have been deployed, very little is known about the molecular response following pesticidal treatments in ticks. In this study, we used a combined approach utilizing transcriptomics and metabolomics to understand the response of the American dog tick to five common pesticides (amitraz, chlorpyrifos, fipronil, permethrin, and propoxur), and analyzed previous experimental data utilizing DEET repellent. Exposure to different chemicals led to significant differential expression of a varying number of transcripts, where 42 were downregulated and only one was upregulated across all treatments. A metabolomic analysis identified significant changes in acetate and aspartate levels following exposure to chlorpyrifos and propoxur, which was attributed to reduced cholinesterase activity. Integrating the metabolomics study with RNA-seq analysis, we found the physiological manifestations of the combined metabolic and transcriptional differences, revealing several novel biomolecular pathways. In particular, we discovered the downregulation of amino sugar metabolism and methylhistidine metabolism after permethrin exposure, as well as an upregulation of glutamate metabolism in amitraz treated samples. Understanding these altered biochemical pathways following pesticide and repellent exposure can help us formulate more effective chemical treatments to reduce the burden of ticks.

Novel Gels: An Emerging Approach for Delivering of Therapeutic Molecules and Recent Trends.

Gels are semisolid, homogeneous systems with continuous or discrete therapeutic molecules in a suitable lipophilic or hydrophilic three-dimensional network base. Innovative gel systems possess multipurpose applications in cosmetics, food, pharmaceuticals, biotechnology, and so forth. Formulating a gel-based delivery system is simple and the delivery system enables the release of loaded therapeutic molecules. Furthermore, it facilitates the delivery of molecules via various routes as these gel-based systems offer proximal surface contact between a loaded therapeutic molecule and an absorption site. In the past decade, researchers have potentially explored and established a significant understanding of gel-based delivery systems for drug delivery. Subsequently, they have enabled the prospects of developing novel gel-based systems that illicit drug release by specific biological or external stimuli, such as temperature, pH, enzymes, ultrasound, antigens, etc. These systems are considered smart gels for their broad applications. This review reflects the significant role of advanced gel-based delivery systems for various therapeutic benefits. This detailed discussion is focused on strategies for the formulation of different novel gel-based systems, as well as it highlights the current research trends of these systems and patented technologies.

Robust topological designs for extreme metamaterial micro-structures.

We demonstrate that the consideration of material uncertainty can dramatically impact the optimal topological micro-structural configuration of mechanical metamaterials. The robust optimization problem is formulated in such a way that it facilitates the emergence of extreme mechanical properties of metamaterials. The algorithm is based on the bi-directional evolutionary topology optimization and energy-based homogenization approach. To simulate additive manufacturing uncertainty, combinations of spatial variation of the elastic modulus and/or, parametric variation of the Poisson's ratio at the unit cell level are considered. Computationally parallel Monte Carlo simulations are performed to quantify the effect of input material uncertainty to the mechanical properties of interest. Results are shown for four configurations of extreme mechanical properties: (1) maximum bulk modulus (2) maximum shear modulus (3) minimum negative Poisson's ratio (auxetic metamaterial) and (4) maximum equivalent elastic modulus. The study illustrates the importance of considering uncertainty for topology optimization of metamaterials with extreme mechanical performance. The results reveal that robust design leads to improvement in terms of (1) optimal mean performance (2) least sensitive design, and (3) elastic properties of the metamaterials compared to the corresponding deterministic design. Many interesting topological patterns have been obtained for guiding the extreme material robust design.

Multi-level analysis of reproduction in an Antarctic midge identifies female and male accessory gland products that are altered by larval stress and impact progeny viability.

The Antarctic midge, Belgica antarctica, is a wingless, non-biting midge endemic to Antarctica. Larval development requires at least 2 years, but adults live only 2 weeks. The nonfeeding adults mate in swarms and females die shortly after oviposition. Eggs are suspended in a gel of unknown composition that is expressed from the female accessory gland. This project characterizes molecular mechanisms underlying reproduction in this midge by examining differential gene expression in whole males, females, and larvae, as well as in male and female accessory glands. Functional studies were used to assess the role of the gel encasing the eggs, as well as the impact of stress on reproductive biology. RNA-seq analyses revealed sex- and development-specific gene sets along with those associated with the accessory glands. Proteomic analyses were used to define the composition of the egg-containing gel, which is generated during multiple developmental stages and derived from both the accessory gland and other female organs. Functional studies indicate the gel provides a larval food source as well as a buffer for thermal and dehydration stress. All of these function are critical to juvenile survival. Larval dehydration stress directly reduces production of storage proteins and key accessory gland components, a feature that impacts adult reproductive success. Modeling reveals that bouts of dehydration may have a significant impact on population growth. This work lays a foundation for further examination of reproduction in midges and provides new information related to general reproduction in dipterans. A key aspect of this work is that reproduction and stress dynamics, currently understudied in polar organisms, are likely to prove critical in determining how climate change will alter their survivability.

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.

A balanced level of profilin-1 promotes stemness and tumor-initiating potential of breast cancer cells.

Profilin-1 (Pfn1) is an important actin-regulatory protein that is downregulated in human breast cancer and when forcibly elevated, it suppresses the tumor-initiating ability of triple-negative breast cancer cells. In this study, we demonstrate that Pfn1 overexpression reduces the stem-like phenotype (a key biologic feature associated with higher tumor-initiating potential) of MDA-MB-231 (MDA-231) triple-negative breast cancer cells. Interestingly, the stem-like trait of MDA-231 cells is also attenuated upon depletion of Pfn1. A comparison of cancer stem cell gene (CSC) gene expression signatures between depleted and elevated conditions of Pfn1 further suggest that Pfn1 may be somehow involved in regulating the expression of a few CSC-related genes including MUC1, STAT3, FZD7, and ITGB1. Consistent with the reduced stem-like phenotype associated with loss-of-function of Pfn1, xenograft studies showed lower tumor-initiating frequency of Pfn1-depleted MDA-231 cells compared to their control counterparts. In MMTV:PyMT mouse model, homozygous but not heterozygous deletion of Pfn1 gene leads to severe genetic mosaicism and positive selection of Pfn1-proficient tumor cells further supporting the contention that a complete lack of Pfn1 is likely not conducive for efficient tumor initiation capability of breast cancer cells. In summary, these findings suggest that the maintenance of optimal stemness and tumor-initiating ability of breast cancer cells requires a balanced expression of Pfn1.

Cryotherapy as a conservative treatment modality for gingival enlargement in a patient with Sturge-Weber Syndrome.

This case report describes a case of Sturge-Weber syndrome reported for unilateral gingival enlargement and bleeding from gingiva in maxillary left region. Initial treatment in the form of scaling and root planing was done but recurrence was observed after one year of follow up. Instead of performing conventional surgery, an alternative conservative treatment was planned in the form of cryotherapy with the help of closed nitrous oxide probe. Seeing the satisfactory results obtained, cryotherapy can be suggested as an atraumatic, bloodless and effective chair side procedure for treating vascular gingival enlargement.