Conventional Limit Research Articles

Development and Evaluation of Essential Oil-loaded Interpenetrating Polymer Network-based Gel for the Management of Dandruff

Abstract Introduction: Dandruff, characterized by flaky skin and itching, presents a challenge for effective treatment due to conventional product limitations and side effects. This study aimed to develop an innovative interpenetrating polymer network (IPN) gel system enriched with essential oils and ketoconazole (KTZ) to enhance antifungal activity. Combining these agents in a Carbopol 940-based hydrogel matrix was designed to deliver sustained and targeted treatment, improving the therapeutic outcome for scalp conditions like dandruff caused by Malassezia furfur. Natural oils, such as tea tree and lemongrass, combined with the potent antifungal properties of KTZ, aim to create a more effective and safer alternative to current treatments. Materials and Methods: The IPN gel was formulated by incorporating KTZ and essential oils into a hydrogel base of Carbopol 940 and polyvinyl alcohol (PVA). Nine different formulations (F-1 to F-9) were developed, each varying in the type and concentration of essential oils and polymer ratios. Tea tree oil was included in formulation F-8, whereas lemongrass oil was used in F-9, combined with KTZ. These formulations were evaluated for their physicochemical properties, drug entrapment efficiency, and in vitro drug release profiles, specifically on antifungal efficacy against M. furfur. Results: The IPN gel system showed significant antidandruff efficacy, especially in targeting M. furfur and dermatophytes. Among all formulations, F-8 (tea tree oil based) and F-9 (lemongrass oil based) demonstrated the most favorable sustained drug release profiles, with extended therapeutic effects over time. KTZ was identified as the most potent antifungal agent in the formulations, with the IPN gel system offering enhanced bioavailability and prolonged scalp contact. Conclusion: These findings highlight the potential of this formulation as a promising alternative to traditional dandruff treatments.

A lightweight AuxHex zero Poisson's ratio pressure-resistant sandwich cylindrical shell and its load-bearing and sound insulation behaviors: Design, simulation and experiment

Pressure-resistant hulls are critical components in underwater vehicles and submersible systems. Exploring novel materials and structures has been a growing trend to overcome conventional structural limitations and achieve multifunctionality. Mechanical metamaterials with tunable physical properties can offer promise. Therefore, this study focuses on designing and fabricating a pressure-resistant sandwich cylindrical shell using AuxHex zero Poisson's ratio (ZPR) mechanical metamaterials. Structural optimization is employed to develop a lightweight AuxHex ZPR unit cell to withstand deep-sea pressure. Mechanical and acoustic experiments were then conducted on a 3D-printed Titanium alloy specimen, and the rationality of numerical modeling was validated by the experimental results. Load bearing and sound insulation properties of the designed ZPR sandwich cylindrical shell have been numerically analyzed and compared with its geometrically similar positive Poisson's ratio (PPR) and negative Poisson's ratio (NPR) shells. The designed ZPR structure that yields a mass density ratio of 0.569 g/cm³ can withstand hydrostatic pressure at 1000 m depths without strength or buckling damage, while adequate reserve buoyancy can be maintained. The submerged ZPR shell structure can provide superior protection for inner spaces and its average sound transmission loss (STL) is more than 5 dB higher than the PPR and NPR shells.

Suppression of the Epithelial-Mesenchymal Transition and Maintenance of the Liver Functions in Primary Hepatocytes through Dispersion Culture within a Dome-Shaped Collagen Matrix.

Primary hepatocytes are valuable for studying liver diseases, drug-induced liver injury, and drug metabolism. However, when cultured in a two-dimensional (2D) environment, primary hepatocytes undergo rapid dedifferentiation via an epithelial-mesenchymal transition (EMT) and lose their liver-specific functions. On the other hand, a three-dimensional (3D) culture of primary hepatocyte organoids presents challenges for analyzing cellular functions and molecular behaviors due to strong cell-cell adhesion among heterogeneous cells. In this study, we developed a novel dispersion culture method of hepatocytes within a dome-shaped collagen matrix, overcoming conventional limitations. The expression levels of EMT-related genes were lower in rat primary hepatocytes cultured using this method for 4 d than in cells cultured using the 2D method. Furthermore, albumin production, a marker of liver function, declined sharply in rat primary hepatocytes cultured in two dimensions from 6.40 µg/mL/48 h on day 4 to 1.35 µg/mL/48 h on day 8, and declined gradually from 4.92 µg/mL/48 h on day 8 to 3.89 µg/mL/48 h on day 14 in rat primary hepatocytes cultured using our new method. These findings indicate that the newly developed culture method can suppress EMT and maintain liver functions for 14 d in rat primary hepatocytes, potentially expanding the utility of primary hepatocyte cultured by using conventional 3D methods.

Precision drug delivery through methotrexate and tofacitinib citrate encapsulated mesoporous silica scaffold

Background: Advancements in drug delivery aim to enhance outcomes while reducing adverse effects. Mesoporous silica nanoparticles (MSN) offer potential for targeted delivery due to their unique properties, including ordered pore structure, large surface area, and biocompatibility. Methods: MSN were synthesized using tetraethyl orthosilicate (TEOS) and Pluronic F127, then amine-functionalized with 3-aminopropyltriethoxysilane. Methotrexate and tofacitinib citrate were loaded via incipient wetness impregnation. Characterization included FTIR, particle size analysis, TEM, SEM, DSC, XRD, and BET analysis. Results: FTIR confirmed surface modification. Particle size analysis showed nanoscale dimensions. TEM and SEM depicted ordered mesoporous structures. DSC indicated drug crystallinity and MSN amorphism. XRD revealed reduced drug crystallinity in MSN. BET analysis demonstrated high MSN surface area and pore volume. Drug-loading efficiency was 62.44%. Conclusion: Comprehensive synthesis and characterization of MSN for targeted drug delivery were achieved successfully, highlighting their potential in overcoming conventional therapy limitations.

Obtaining Heterogeneous Microstructure and Enhanced Mechanical Properties in ECAP-Processed AZ61 Alloys via Single-Pass Rolling with Increased Rolling Reduction

Material design and preparation based on constructing heterogeneous microstructures can break the conventional performance limitations of fine-grained magnesium alloys. In this study, AZ61 alloys processed via multi-pass equal channel angular pressing (ECAP) were subjected to single-pass rolling (SPR) with increased rolling reductions. The effect of rolling reduction on the formation of heterogeneous microstructure and the mechanical properties of the alloy was investigated. Microstructural examinations revealed that a heterogeneous microstructure was formed in the alloy at varied rolling reductions, but the desired heterostructure with higher fine grain contents could only be achieved at increased rolling reduction. This was mainly due to the fact that the alloy underwent partial dynamic recrystallization (PDRX) under SPR, and PDRX more easily occurred with higher rolling reduction. The tensile test results showed that with increased rolling reduction, the strength of the alloy first increased and then decreased slightly, with the ductility steadily increasing. Improved mechanical properties were achieved in the alloy rolled at increased rolling reductions owing to the heterogeneous microstructure with a greater content of fine grains.

A hybrid formulation of porous silicon nanoparticle with carboxymethyl cellulose for enhanced drug loading

Porous silicon nanoparticles (pSiNPs) have received considerable spotlight in drug delivery systems due to their biocompatibility, drug loading capacity, and easy surface modification. Despite these merits, the degradation rate control of pSiNPs in biological environments remains a challenge for sustained-release applications. In this study, we introduce a novel formulation of pSiNPs-based coated with carboxymethyl cellulose (pSiNPs-CMC) for the first time. The drug loading and release behavior of pSiNPs-CMC, featuring representative anticancer drugs such as doxorubicin, gemcitabine, paclitaxel, and SN-38, were extensively characterized. Notably, the CMC coating on pSiNPs resulted in an increase in loading efficiency of over 60% both for hydrophilic and hydrophobic drugs, while ensuring a controlled and tailored drug release profile. Our findings present the potential of the pSiNPs-CMC composite as a robust and versatile platform, overcoming conventional limitations in drug specificity and representing a significant advancement in sustained and personalized drug delivery systems.

Indirect prediction of graphene nanoplatelets-reinforced cementitious composites compressive strength by using machine learning approaches

Graphene nanoplatelets (GrNs) emerge as promising conductive fillers to significantly enhance the electrical conductivity and strength of cementitious composites, contributing to the development of highly efficient composites and the advancement of non-destructive structural health monitoring techniques. However, the complexities involved in these nanoscale cementitious composites are markedly intricate. Conventional regression models encounter limitations in fully understanding these intricate compositions. Thus, the current study employed four machine learning (ML) methods such as decision tree (DT), categorical boosting machine (CatBoost), adaptive neuro-fuzzy inference system (ANFIS), and light gradient boosting machine (LightGBM) to establish strong prediction models for compressive strength (CS) of graphene nanoplatelets-based materials. An extensive dataset containing 172 data points was gathered from published literature for model development. The majority portion (70%) of the database was utilized for training the model while 30% was used for validating the model efficacy on unseen data. Different metrics were employed to assess the performance of the established ML models. In addition, SHapley Additve explanation (SHAP) for model interpretability. The DT, CatBoost, LightGBM, and ANFIS models exhibited excellent prediction efficacy with R-values of 0.8708, 0.9999, 0.9043, and 0.8662, respectively. While all the suggested models demonstrated acceptable accuracy in predicting compressive strength, the CatBoost model exhibited exceptional prediction efficiency. Furthermore, the SHAP analysis provided that the thickness of GrN plays a pivotal role in GrNCC, significantly influencing CS and consequently exhibiting the highest SHAP value of + 9.39. The diameter of GrN, curing age, and w/c ratio are also prominent features in estimating the strength of graphene nanoplatelets-based cementitious materials. This research underscores the efficacy of ML methods in accurately forecasting the characteristics of concrete reinforced with graphene nanoplatelets, providing a swift and economical substitute for laborious experimental procedures. It is suggested that to improve the generalization of the study, more inputs with increased datasets should be considered in future studies.

Intravesical instillation-based mTOR-STAT3 dual targeting for bladder cancer treatment

BackgroundRecent intravesical administration of adenoviral vectors, either as a single injection or in combination with immune checkpoint inhibitors, exemplified by cretostimogene grenadenorepvec and nadofaragene firadenovec, has demonstrated remarkable efficacy in clinical trials for non-muscle invasive bladder cancer. Despite their ability to induce an enhanced immune reaction within the lesion, the intracellular survival signaling of cancer cells has not been thoroughly addressed.MethodsAn analysis of the prognostic data revealed a high probability of therapeutic efficacy with simultaneous inhibition of mTOR and STAT3. Considering the challenges of limited pharmaco-accessibility to the bladder due to its pathophysiological structure and the partially undruggable nature of target molecules, we designed a dual siRNA system targeting both mRNAs. Subsequently, this dual siRNA system was encoded into the adenovirus 5/3 (Ad 5/3) to enhance in vivo delivery efficiency.ResultsGene-targeting efficacy was assessed using cells isolated from xenografted tumors using a single-cell analysis system. Our strategy demonstrated a balanced downregulation of mTOR and STAT3 at the single-cell resolution, both in vitro and in vivo. This approach reduced tumor growth in bladder cancer xenograft and orthotopic animal experiments. In addition, increased infiltration of CD8+ T cells was observed in a humanized mouse model. We provided helpful and safe tissue distribution data for intravesical therapy of siRNAs coding adenoviruses.ConclusionsThe bi-specific siRNA strategy, encapsulated in an adenovirus, could be a promising tool to augment cancer treatment efficacy and overcome conventional therapy limitations associated with “undruggability.” Hence, we propose that dual targeting of mTOR and STAT3 is an advantageous strategy for intravesical therapy using adenoviruses.Graphical The current investigation introduces an innovative conceptualization of bispecific short hairpin RNA (bs_shRNA) tailored for the equilibrated modulation of dual genes within a singular cellular context. This novel bs_shRNA was loaded into the genome of an oncolytic adenovirus to augment the therapeutic efficacy of oncolytic viral interventions via the targeted inhibition of mTOR and STAT3 pathways. In addition, the administration of BSV significantly reduced the volume of bladder cancer tumors, concomitantly facilitating an enhanced recruitment of CD8+T lymphocytes in vivo.

Multivariate anomaly detection models enhance identification of errors in routine clinical chemistry testing.

Conventional autoverification rules evaluate analytes independently, potentially missing unusual patterns of results indicative of errors such as serum contamination by collection tube additives. This study assessed whether multivariate anomaly detection algorithms could enhance the detection of such errors. Multivariate Gaussian, k-nearest neighbours (KNN) distance, and one-class support vector machine (SVM) anomaly detection models, along with conventional limit checks, were developed using a training dataset of 127,451 electrolyte, urea, and creatinine (EUC) results, with a 5 % flagging rate targeted for all approaches. The models were compared with limit checks for their ability to detect atypical EUC results from samples spiked with additives from collection tubes: EDTA, fluoride, sodium citrate, or acid citrate dextrose (n=200 per contaminant). The study additionally assessed the ability of the models to identify 127,449 single-analyte errors, a potential weakness of multivariate models. The KNN distance and SVM models outperformed limit checks for detecting all contaminants (p-values <0.05). The multivariate Gaussian model did not surpass limit checks for detecting EDTA contamination but was superior for detecting the other additives. All models surpassed limit checks for identifying single-analyte errors, with the KNN distance model demonstrating the highest overall sensitivity. Multivariate anomaly detection models, particularly the KNN distance model, were superior to the conventional approach for detecting serum contamination and single-analyte errors. Developing multivariate approaches to autoverification is warranted to optimise error detection and improve patient safety.

Accurate Internal Monitoring of Batteries by Embedded Piezoelectric Sensors.

Advancements in operando techniques have unraveled the complexities of the Electrode Electrolyte Interface (EEI) in electrochemical energy storage devices. However, each technique has inherent limitations, often necessitating adjustments to experimental conditions, which may compromise accuracy. To address this challenge, a novel battery cell design is introduced, integrating piezoelectric sensors with electrochemical analysis for surface-sensitive operando measurements. This innovative approach aims to overcome conventional limitations by accommodating commercial-grade battery electrodes within a single body, alongside a piezoelectric sensor. This enables operando electrogravimetric measurements to be realized, and the electrochemistry of a battery to be more faithfully reproduced at the sensor level. A proof of concept is carried out on both Li-ion (LiFePO4//Graphite) and Na-ion (Na3V2(PO4)2F3//Hard carbon) systems, utilizing commercially available powder electrodes. In both cases, the results reveal rational mass variations at the sensor level during the cycling of commercial electrodes with mass loadings several orders of magnitude higher, while performing Galvanostatic Charge Discharge (GCD) tests across various C-rates. This innovative design opens up possibilities for a broader application of operando electrogravimetry within the battery community, to enhance the understanding of EEI behavior and facilitate the development of more efficient energy storage solutions.

Inter-turn Short Circuit Fault Diagnosis and Severity Estimation for Wind Turbine Generators

While preventive maintenance is crucial in wind turbine operation, conventional condition monitoring systems face limitations in terms of cost and complexity when compared to innovative signal processing techniques and artificial intelligence. In this paper, a cascading deep learning framework is proposed for the monitoring of generator winding conditions, specifically to promptly detect and identify inter-turn short circuit faults and estimate their severity in real time. This framework encompasses the processing of high-resolution current signal samples, coupled with the extraction of current signal features in both time and frequency domains, achieved through discrete wavelet transform. By leveraging long short-term memory recurrent neural networks, our aim is to establish a cost-efficient and reliable condition monitoring system for wind turbine generators. Numeral experiments show an over 97% accuracy for fault diagnosis and severity estimation. More specifically, with the intrinsic feature provided by wavelet transform, the faults can be 100% identified by the diagnosis model.

Transferosomes: Advancing Vesicular Drug Delivery Systems for Dermatological Disorders - A Comprehensive Review

Abstract: The human skin is the largest organ, is a vital interface with the external environment, and maintains homeostasis through its layered structure of epidermis, dermis, and hypodermis. The epidermis forms a strong barrier against microorganisms, and the dermis consists of essential components like collagen and melanin, and the hypodermis aids in insulation and energy storage. The skin diseases, spanning the epidermis, dermis, and subcutaneous tissue, include psoriasis, dermatitis, acne, hyperpigmentation, and aging. The nanocarrier-based drug delivery, particularly transferosomes, shows promise in treating dermatological conditions. Transfersomes are composed of phospholipids and edge activators, and navigate skin structures with flexibility, enhancing drug permeation. They offer continuous drug release, accommodating both lipophilic and hydrophilic drugs, and respond to osmotic gradients, optimizing transdermal delivery. Despite being non-invasive, formulation challenges and stability issues require attention. Studies demonstrate transferosomes' efficacy in treating conditions like acne, psoriasis, and melasma, demonstrating their potential for targeted drug delivery and overcoming conventional limitations in dermatology.

Activating MnO2 nanosheet arrays for accelerated water oxidation through the synergic effect of Ni loading and O vacancies

Birnessite (δ-MnO2), inspired by biological photosynthesis, holds promise as oxygen evolution reaction (OER) catalysts in water electrolysis for clean energy. Given that Mn3+ serves as the active sites, various strategies have been employed to increase the Mn3+ content to boost the OER activity. To surpass the limitations of the traditional adsorbate evolution mechanism (AEM), we have adopted an electrochemical reduction method to introduce metallic Ni and enrich oxygen vacancies onto δ-MnO2 nanosheets. The resulting Ni/MnO2v/CC exhibits exceptional OER performance, with a reduction in overpotential by 190 mV (from 478 mV to 289 mV) at 10 mA cm−2 and a Tafel slope as low as 45 mV dec-1, indicating accelerated catalytic activity. Experimental and theoretical analyses attribute this enhancement to a transition from the traditional AEM to lattice oxygen mechanism (LOM) mechanism. Moreover, the dual modification also enhances electronic conductivity, electrochemical surface area, and charge transfer ability of δ-MnO2. Our work offers a pathway to overcome conventional limitations in OER electrocatalysts, applicable not only to Mn-based catalysts but also to a range of other transition metal oxides.

Impact of NaOH based perfusion-decellularization protocol on mechanical resistance of structural bone allografts

ABSTRACT Introduction To mitigate the post-operative complication rates associated with massive bone allografts, tissue engineering techniques have been employed to decellularize entire bones through perfusion with a sequence of solvents. Mechanical assessment was performed in order to compare conventional massive bone allografts and perfusion/decellularized massive bone allografts. Material and methods Ten porcine femurs were included. Five were decellularized by perfusion. The remaining 5 were left untreated as the “control” group. Biomechanical testing was conducted on each bone, encompassing five different assessments: screw pull-out, 3-points bending, torsion, compression and Vickers indentation. Results Under the experimental conditions of this study, all five destructive tested variables (maximum force until screw pull-out, maximum elongation until screw pull-out, energy to pull out the screw, fracture resistance in flexion and maximum constrain of compression) were statistically significantly superior in the control group. All seven nondestructive variables (Young’s modulus in flexion, Young’s modulus in shear stress, Young’s modulus in compression, Elastic conventional limit in compression, lengthening to rupture in compression, resilience in compression and Vickers Hardness) showed no significant difference. Discussion Descriptive statistical results suggest a tendency for the biomechanical characteristics of decellularized bone to decrease compared with the control group. However, statistical inferences demonstrated a slight significant superiority of the control group with destructive mechanical stresses. Nondestructive mechanical tests (within the elastic phase of Young’s modulus) were not significantly different.

Architecture for sub-100 ms liquid crystal reconfigurable intelligent surface based on defected delay lines

AbstractReconfigurable intelligent surfaces, comprised of passive tunable elements, are emerging as an essential device for upcoming millimeter wave and terahertz wireless systems. A fundamental aspect of the device involves the tuning technology used to achieve reconfigurability. Among alternatives such as semiconductors and micro-electromechanical systems, liquid crystal offers advantages including cost- and power-effective large-panel scalability. In this context, conventional liquid crystal-based reconfigurable intelligent surface approaches face limitations in optimizing for bandwidth, response time and loss simultaneously, requiring trade-offs between them. Here we detail an architecture for a liquid crystal-based reconfigurable intelligent surface with compact defected delay lines that provide continuous, 360-degree tunability, enabling fast response time, wide bandwidth and low loss. A reconfigurable intelligent surface with a thin 4.6μm liquid crystal layer is designed, fabricated, and characterized, exhibiting response times of 72 milliseconds, insertion losses below 7 dB, and a 6.8 GHz (10.9%) bandwidth at 62 GHz, all while utilizing a lossy glass substrate and gold as a conductor.

A novel approach for measuring large magnetic anisotropy energy with a limited magnetic field range

Here we propose an experimental method for determining the magnetic anisotropy field in ferromagnetic materials. Our method involves examining the small-angle variation of spontaneous magnetization by the external magnetic field and interpreting the experimental result within the framework of the Stoner-Wohlfarth model applicable to ferromagnetic materials. This method allows for the extrapolation of magnetic anisotropy fields, even when they surpass conventional measurement limits. As a result, a broad range of magnetic anisotropy fields can be ascertained using a single experimental setup. Our proposed method serves as a versatile tool for analyzing large magnetic anisotropy energy which is an important parameter for future spintronic devices.

An autotransferable alloy overlayer toward stable sodium metal anodes

Sodium (Na) metal anodes receive significant attention due to their high theoretical specific energy and cost-effectiveness. However, the high reactivity of Na foil anodes and the irregular surfaces have posed challenges to the operability and reliability of Na metals in battery applications. In the absence of inert environmental protection conditions, constructing a uniform, dense, and sodiophilic Na metal anode surface is crucial for homogenizing Na deposition, but remains less-explored. Herein, we fabricated a Tin (Sn) nanoparticle-assembled film conforming to separator pores, which provided ample space for accommodating volumetric expansion during the Na alloying process. Subsequently, a seamless Na-Sn alloy overlayer was formed and transferred onto the Na foil during Na plating through a separator-assisted technique, thereby overcoming conventional operational limitations of metallic Na. As compared to traditional volumetrically expanded cracked ones, the present autotransferable, highly sodiophilic, ion-conductive, and seamless Na-Sn alloy overlayer serves as uniform nucleation sites, thereby reducing nucleation and diffusion barriers and facilitating the compact deposition of metallic Na. Consequently, the autotransferable alloy layer enables a high average Coulombic efficiency of 99.9 % at 3.0 mA cm−2 and 3.0 mAh cm−2 in the half cells as well as minimal polarization overpotentials in symmetric cells, both during prolonged cycling 1200 h. Furthermore, the assembled Na||Sn-1.0h-PP||Na3V2(PO4)3@C@CNTs full cell delivers high capacity retention of 97.5 % after 200 cycles at a high cathodic mass loading.

Breaking piezoelectric limits of molecules for biodegradable implants

AbstractIn the quest for optimizing biodegradable implants, the exploration of piezoelectric materials stands at the forefront of biomedical engineering research. Traditional piezoelectric materials often suffer from limitations in biocompatibility and biodegradability, significantly impeding their in vivo study and further biomedical application. By leveraging molecular engineering and structural design, a recent innovative approach transcends the conventional piezoelectric limits of the molecules designed for biodegradable implants. The biodegradable molecular piezoelectric implants may open new avenues for their applications in bioenergy harvesting/sensing, implanted electronics, transient medical devices and tissue regeneration.

Ultra-sensitive measurement of small optical rotation angles using quantum entanglement based on a quasi-Wollaston prism beam splitter

The measurement of optical rotation is fundamental to optical atomic magnetometry. Ultra-high sensitivity has been achieved by employing a quasi-Wollaston prism as the beam splitter within a quantum entanglement state, complemented by synchronous detection. Initially, we designed a quasi-Wollaston prism and intentionally rotated the crystal axis of the exit prism element by a specific bias angle. A linearly polarized light beam, incident upon this prism, is divided into three beams, with the intensity of each beam correlated through quantum entanglement. Subsequently, we formulated the equations for optical rotation angles by synchronously detecting the intensities of these beams, distinguishing between differential and reference signals. Theoretical analysis indicates that the measurement uncertainty for optical rotation angles, when using quantum entanglement, exceeds the conventional photon shot noise limit. Moreover, we have experimentally validated the effectiveness of our method. In DC mode, the experimental results reveal that the measurement uncertainty for optical rotation angles is 4.7 × 10−9 rad, implying a sensitivity of 4.7 × 10−10 rad/Hz1/2 for each 0.01 s measurement duration. In light intensity modulation mode, the uncertainty is 48.9 × 10−9 rad, indicating a sensitivity of 4.89 × 10−9 rad/Hz1/2 per 0.01 s measurement duration. This study presents a novel approach for measuring small optical rotation angles with unprecedentedly low uncertainty and high sensitivity, potentially playing a pivotal role in advancing all-optical atomic magnetometers and magneto-optical effect research.

Quantum Mechanical Versus Polarizable Embedding Schemes: A Study of the Xray Absorption Spectra of Aqueous Ammonia and Ammonium.

The X-ray absorption spectra of aqueous ammonia and ammonium are computed using a combination of coupled cluster singles and doubles (CCSD) with different quantum mechanical and molecular mechanical embedding schemes. Specifically, we compare frozen Hartree-Fock (HF) density embedding, polarizable embedding (PE), and polarizable density embedding (PDE). Integrating CCSD with frozen HF density embedding is possible within the CC-in-HF framework, which circumvents the conventional system-size limitations of standard coupled cluster methods. We reveal similarities between PDE and frozen HF density descriptions, while PE spectra differ significantly. By including approximate triple excitations, we also investigate the effect of improving the electronic structure theory. The spectra computed using this approach show an improved intensity ratio compared to CCSD-in-HF. Charge transfer analysis of the excitations shows the local character of the pre-edge and main-edge, while the post-edge is formed by excitations delocalized over the first solvation shell and beyond.