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Polymer modeling has been playing an increasingly important role in complementing 3D genome experiments, both to aid their interpretation and to reveal the underlying molecular mechanisms. This chapter illustrates an application of Hi-C metainference, a Bayesian approach to explore the 3D organization of a target genomic region by integrating experimental contact frequencies into a prior model of chromatin. The method reconstructs the conformational ensemble of the target locus by combining molecular dynamics simulation and Monte Carlo sampling from the posterior probability distribution given the data. Using prior chromatin models at both 1 kb and nucleosome resolution, we apply this approach to a 30 kb locus of mouse embryonic stem cells consisting of two well-defined domains linking several gene promoters together. Retaining the advantages of both physics-based and data-driven strategies, Hi-C metainference can provide an experimentally consistent representation of the system while at the same time retaining molecular details necessary to derive physical insights.

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The rapid industrial progress in today's world has led to an alarming increase in water pollution caused by various contaminants such as synthetic dyes. To address this issue, a new hydrogel sorbent, BC-r-Na-Alg-g-p(NIPAm-co-AAc), was developed by combining bentonite clay, sodium alginate, and poly(N-isopropyl acrylamide-co-acrylic acid) through one-pot free radical polymerization at 60 °C. The developed sorbent was characterized using several analytical techniques including SEM, FTIR, TGA, UTM, and swelling studies. The swelling capacity of the sorbent was observed to increase remarkably with an increase in pH, reaching a maximum of 9664 % at pH 11. In batch mode sorption experiments, the sorbent's performance toward methylene green (MG) was investigated by analysing the effects of contact time, pH, temperature, and concentration. The experimental data were fitted to pseudo-second-order kinetic and Langmuir isotherm models, indicating chemisorption as the dominant interaction mode between the anionic sorbent and cationic MG. However, physisorption may also occur to a lesser extent, indicated by the significant R2 of the pseudo-first-order kinetic and Freundlich isotherm models. Additionally, the sorbent exhibited very little decrease (approximately 5 %) in sorptive performance for six sorption-desorption cycles. Overall, the facile fabrication, excellent swelling (9664 %), promising sorption performance (2573 mg.g-1), and good recyclability (6 cycles) make the developed sorbent a potential candidate for various industrial applications.

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Our study delved into the intricate dynamics of antifungal susceptibility testing for Candida spp., employing a Design of Experiments approach. We systematically investigated the influence of pH, temperature, inoculum size, and glucose concentration on both growth patterns and inhibitory concentrations of Candida spp. Our findings underscore the nuanced interplay between these factors, revealing significant impacts on susceptibility outcomes. Notably, even minor adjustments in these parameters yielded substantial variations in growth and inhibitory concentrations, underscoring the critical importance of meticulous control over growth conditions in antifungal susceptibility testing protocols. Each Candida isolates exhibited unique susceptibility profiles, necessitating tailored culture conditions for accurate testing. Our study sheds light on the variability inherent in Candida spp. growth patterns and emphasizes the need for standardized protocols to ensure consistency across laboratories. By leveraging the design of experiments, our research provides a systematic framework for unraveling the complexities of antifungal susceptibility testing, offering valuable insights for optimizing testing protocols and informing clinical decision-making in antifungal treatment. These findings represent a significant step towards enhancing the efficacy and reliability of antifungal susceptibility testing in clinical practice.

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Research on the improvement of national park recreation policies has attracted much attention to discrete choice experiments to obtain tourists' preferences and willingness to pay. However, individual choice behavior is extremely complex, and the single Random Utility Maximization (RUM) model ignores anticipated regret and is insufficient to explain individuals' actual choice behavior. To investigate whether regret influences tourists' choices regarding the improvement of national park recreation attributes, this study introduces the Random Regret Minimization (RRM) model and explores the performance of polynomial logit models and hybrid latent class models in analyzing discrete choice models based on utility and regret. By constructing a hybrid utility-regret model, we examine how tourists trade off between attributes such as vegetation coverage, water clarity, amount of litter, and level of crowding in national park recreation. Results indicate that the RRM model has better goodness-of-fit and predictive ability than the RUM model, indicating that regret is a significant choice paradigm, and the hybrid model better explains respondents' choices. Specifically, 62.5% of tourists' choices are driven by regret, and regret-driven respondents are more inclined to increase vegetation coverage and improve water clarity, while utility-driven respondents are more inclined to reduce litter and crowding. This study not only provides a reference for managers to develop more optimal recreation improvement strategies but also offers theoretical insights for national park recreation improvement policies.

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Dry eye syndrome (DES) is a multifactorial ocular surface disease and represents one of the most prevalent ophthalmic disorders. Insulin is an important metabolism-regulating hormone and a potential antioxidant with critical biological roles as anti-inflammatory and anti-apoptotic. However, its mechanism of action remains unknown. In this study, we used network pharmacology techniques and conducted cell experiments to investigate the protective effect of insulin on human corneal epithelial cells (HCECs). Eighty-seven common targets of insulin and DES were identified from the database. KEGG pathway enrichment analysis suggested that insulin may be crucial in regulating the toll-like receptor (TLR) signaling pathway by targeting key targets such as IL-6 and TNF. In cell experiments, insulin promoted HCECs proliferation, improved their ability to migrate, and inhibited apoptosis. Western blot and enzyme-linked immunosorbent assay (ELISA) also confirmed the upregulation of the expression of inflammatory factors such as IL-1ß, IL-6, and proteins related to the TLR4/NF-κB signaling pathway. However, the expression of these proteins was inhibited by insulin administration. Our results preliminarily verified insulin may exert a protective role on HCECs under hyperosmotic condition, which offered a novel perspective for the clinical management of this condition.

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The timely and accurate acquisition of crop-growth information is a prerequisite for implementing intelligent crop-growth management, and portable multispectral imaging devices offer reliable tools for monitoring field-scale crop growth. To meet the demand for obtaining crop spectra information over a wide band range and to achieve the real-time interpretation of multiple growth characteristics, we developed a novel portable snapshot multispectral imaging crop-growth sensor (PSMICGS) based on the spectral sensing of crop growth. A wide-band co-optical path imaging system utilizing mosaic filter spectroscopy combined with dichroic mirror beam separation is designed to acquire crop spectra information over a wide band range and enhance the device's portability and integration. Additionally, a sensor information and crop growth monitoring model, coupled with a processor system based on an embedded control module, is developed to enable the real-time interpretation of the aboveground biomass (AGB) and leaf area index (LAI) of rice and wheat. Field experiments showed that the prediction models for rice AGB and LAI, constructed using the PSMICGS, had determination coefficients (R²) of 0.7 and root mean square error (RMSE) values of 1.611 t/ha and 1.051, respectively. For wheat, the AGB and LAI prediction models had R² values of 0.72 and 0.76, respectively, and RMSE values of 1.711 t/ha and 0.773, respectively. In summary, this research provides a foundational tool for monitoring field-scale crop growth, which is important for promoting high-quality and high-yield crops.

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Venous thromboembolism (VTE) has been occurring frequently in human society. There is an urgent need to study the influence of several factors on thrombolytic therapy, such as the effects of vascular pressure levels (VPL) and the drug injection time (DIT). Considering blood as a non-Newtonian fluid, valve as a hyperelastic material, and thrombus as a porous medium, a new numerical simulation model of biofluid mechanics incorporating fluid-solid coupling phenomena and biochemical substance reactions is established based on the N-S equations and the convection-diffusion reaction equations. Then, a unique in vitro experimental platform is established to verify the correctness of the constructed mathematical model. The results showed that vascular compression resulted in significant differences in blood flow status localized within the vessel. Vascular compression causes the blood boosting index to fluctuate and the valve displacement values are 135% and 158% greater than the lower VPL, respectively. At the same time, vascular compression weakened vortex intensity, accelerated material transport and response, and improved the treatment. Compared with low VPL, the therapeutic efficacy increased by 7% and 15%, respectively. In addition, when the dose of the drug is high, different injection times can increase the therapeutic effect to different degrees, with a maximum difference of 12%. Our in vitro experiments are similar to the results obtained by numerical simulation, which can verify the reliability of numerical simulation. The computational model proposed and the experimental platform designed in this study have the potential to assist in clinical medication prediction in different venous thromboembolism patients.

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Over the last three decades, the technology that makes it possible to follow chemical processes in the solid state in real time has grown enormously. These studies have important implications for the design of new functional materials for applications in optoelectronics and sensors. Light-matter interactions are of particular importance, and photocrystallography has proved to be an important tool for studying these interactions. In this technique, the three-dimensional structures of light-activated molecules, in their excited states, are determined using single-crystal X-ray crystallography. With advances in the design of high-power lasers, pulsed LEDs and time-gated X-ray detectors, the increased availability of synchrotron facilities, and most recently, the development of XFELs, it is now possible to determine the structures of molecules with lifetimes ranging from minutes down to picoseconds, within a single crystal, using the photocrystallographic technique. This review discusses the procedures for conducting successful photocrystallographic studies and outlines the different methodologies that have been developed to study structures with specific lifetime ranges. The complexity of the methods required increases considerably as the lifetime of the excited state shortens. The discussion is supported by examples of successful photocrystallographic studies across a range of timescales and emphasises the importance of the use of complementary analytical techniques in order to understand the solid-state processes fully.

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The present study describes a set of methodological procedures (seldom applied together), including (i) development of an alternative adsorbent derived from abundant low-cost plant biomass; (ii) use of simple low-cost biomass modification techniques based on physical processing and chemical activation; (iii) design of experiments (DoE) applied to optimize the removal of a pharmaceutical contaminant from water; (iv) at environmentally relevant concentrations, (v) that due to initial low concentrations required determination by ultra-performance liquid phase chromatography coupled to mass spectrometry (UPLC-MS/MS). A central composite rotational design (CCRD) was employed to investigate the performance of vegetable sponge biomass (Luffa cylindrica), physically processed (crushing and sieving) and chemically activated with phosphoric acid, in the adsorption of the antibiotic trimethoprim (TMP) from water. The optimized model identified pH as the most significant variable, with maximum drug removal (91.1 ± 5.7%) achieved at pH 7.5, a temperature of 22.5 °C, and an adsorbent/adsorbate ratio of 18.6 mg µg-1. The adsorption mechanisms and surface properties of the adsorbent were examined through characterization techniques such as scanning electron microscopy (SEM), point of zero charge (pHpzc) measurement, thermogravimetric analysis (TGA), specific surface area, and Fourier-transform infrared spectroscopy (FTIR). The best kinetic fit was obtained by the Avrami fractional-order model. The hypothesis of a hybrid behavior of the adsorbent was suggested by the equilibrium results presented by the Langmuir and Freundlich models and reinforced by the Redlich-Peterson model, which achieved the best fit (R2 = 0.982). The thermodynamic study indicated an exothermic, spontaneous, and favorable process. The maximum adsorption capacity of the material was 2.32 × 102 µg g-1 at an equilibrium time of 120 min. Finally, a sustainable and promising adsorbent for the polishing of aqueous matrices contaminated by contaminants of emerging concern (CECs) at environmentally relevant concentrations is available for future investigations.

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Land subsidence caused by excessive groundwater withdrawal has become a global hazard, which demands further researches and the potential measures to control. Using the FlowTrac Ⅱ consolidation test system, six compression tests were designed to investigate the stress state and stress paths of sand within confined aquifers under conditions of withdrawal and recharging. The deformation characteristics of aquifer sand were studied under different withdrawal-recharging patterns. During pumping and recharge processes, sand deformation responses were observed to lag behind changes in applied stress. The characteristics of this hysteresis effect on deformation were summarized. The alternating phenomenon of rebound and compression of sand deformation under the recharging process is analyzed. When the recharging effect was relatively small than withdrawing effect under the stable withdrawal-recharging pattern, the compression deformation was observed in the recharging process. The research results provide a rational explanation for the continuous compression deformation of the aquifer during groundwater level recovery and offer experimental evidence for the rational design of artificial groundwater recharge in engineering construction.

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In recent years, the field of analytical chemistry has witnessed a notable shift towards the adoption of greener chromatographic methods, aiming to minimize the environmental impact. An effective strategy involves substituting conventional harmful organic solvents with environmentally friendly alternatives, reducing the use of hazardous chemicals that contribute to environmental concerns. However, separating drug substances without the use of buffers and organic solvents presence is a big challenge. To overcome this challenge, a combination of quality-by-design (QbD) and green analytical chemistry (GAC) was employed in this study for method development. A high-performance liquid chromatography (HPLC) method was successfully developed and validated for the simultaneous determination of Nebivolol hydrochloride, Telmisartan, Valsartan, and Amlodipine besylate. The method utilized a mobile phase composed of a mixture of 0.1 % formic acid in water (pH: 2.5) and ethanol. A regular octadecyl silica (ODS) column was employed, and UV detection at 220 nm was utilized. The method exhibited linearity within the concentration range of 25-75 µg/mL for Telmisartan and 150-450 µg/mL for Nebivolol Hydrochloride, Valsartan, and Amlodipine besylate and the correlation coefficient was greater than 0.999 for all the analytes. Limits of detection (LOD) and quantification (LOQ) were determined as 0.01 and 0.04 µg/mL for Telmisartan, 0.06 and 0.20 µg/mL for Nebivolol Hydrochloride, 0.08 and 0.25 µg/mL for Amlodipine besylate, and 0.14 and 0.46 µg/mL for Valsartan, respectively. The developed method underwent thorough validation, encompassing various parameters such as linearity, accuracy, precision, LOD, LOQ, robustness, and ruggedness. The mean recovery values were observed to range between 98.86 % and 99.89 %. The accuracy demonstrated was consistently above 98.98 % for both intra-day and inter-day precisions were with the relative standard deviations less than 2 %. To establish its robustness, a quality-by-design-based experimental design (DoE) approach was implemented. Additionally, the method's environmental friendliness was evaluated using the Analytical Greenness metric (AGREE) an analytical eco scale, both confirming its alignment with sustainable practices and reduced ecological impact. The sustainability of the solvent used in the current study was evaluated by Green Solvents Selecting Tool (GSST) Further, the developed method greenness was evaluated with the green analytical tools such as Analytical method greenness score (AMGS) and using the recently released White Analytical Chemistry (WAC) using RGB assessment tool. By employing this greener approach to chromatography method, this study contributes to the ongoing efforts in analytical chemistry to promote sustainable practices and minimize the environmental footprint of analytical methods.

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This study validates a stability-indicating LC method for detecting organic impurities in the chlorzoxazone dosage form. Using a Waters X-Select R HSS T3 analytical column, mobile phase of it was made by mixing of water, methanol, and glacial acetic acid in the ratio of 700:300:10 (v/v/v). The drug product and drug substance were subjected to the stress conditions such as acid, base, oxidation, heat, and photolysis as per the recommendations of the International Conference on Harmonization (Q2) methodology. The study revealed the susceptibility of 4-chloro-2-aminophenol to alkaline environments, emphasizing peak homogeneity and stability. The method verification, per ICH guidelines and USP<1225>, established precision, specificity, linearity, accuracy, and robustness for quality control. The mean impurity recovery ranged from 95.5% to 105.2%, the correlation coefficient (r) was greater than 1.000, and the RSD values (n = 6) ranged from 0.6% to 5.1% across the LOQ-150% ranges. Full-factorial design tested final method conditions, evaluating multiple parameters concurrently. Graphical optimization within the design space defined strong method requirements, ensuring consistent and reliable outcomes. The study develops and validates chlorzoxazone stability-indicating methods, employing advanced statistical approaches like design of experiments and factorial design, with resilient conditions established through graphical optimization of the design space.

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Understanding material failure on a fundamental level is a key aspect in the design of robust structural materials, especially for metals and alloys capable to undergo plastic deformation. In the last decade, significant progress is made in quantifying the stresses associated with failure in both experiments and simulations. Nonetheless, the processes occurring on the most essential level of individual dislocations that govern semi-brittle and ductile fracture are still experimentally not accessible, limiting the failure prediction capabilities. Therefore, in the present work, a one-of-a-kind nanoscale fracture experiment is conducted on a single crystalline Cr bending beam in situ in the transmission electron microscope and for the first time quantify the transient strains around individual dislocations, as well as of the whole dislocation network during crack opening. The results reveal the importance of both pre-existing and newly emitted dislocations for crack-tip shielding via their intrinsic strain field and provide guidelines to design more damage tolerant materials.

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Introduction: The study aimed to systematically enhance the fabrication process of flurbiprofen-loaded bilosomes (FSB) using Quality by Design (QbD) principles and Design of Experiments (DOE). The objective was to develop an optimized formulation with improved entrapment efficiency and targeted drug delivery capabilities. Methods: The optimization process involved applying QbD principles and DOE to achieve the desired formulation characteristics. Superparamagnetic iron oxide nanoparticles (SPIONs) were incorporated to impart magnetic responsiveness. The size, entrapment efficiency, morphology, and in vitro release patterns of the FSB formulation were evaluated. Additionally, an in situ forming hydrogel incorporating FSB was developed, with its gelation time and drug release kinetics assessed. In vivo studies were conducted on osteoarthritic rats to evaluate the efficacy of the FSB-loaded hydrogel. Results: The optimized FSB formulation yielded particles with a size of 453.60 nm and an entrapment efficiency of 91.57%. The incorporation of SPIONs enhanced magnetic responsiveness. Morphological evaluations and in vitro release studies confirmed the structural integrity and sustained release characteristics of the FSB formulation. The in situ forming hydrogel exhibited a rapid gelation time of approximately 40 ± 1.8 s and controlled drug release kinetics. In vivo studies demonstrated a 27.83% reduction in joint inflammation and an 85% improvement in locomotor activity in osteoarthritic rats treated with FSB-loaded hydrogel. Discussion: This comprehensive investigation highlights the potential of FSB as a promising targeted drug delivery system for the effective management of osteoarthritis. The use of QbD and DOE in the formulation process, along with the integration of SPIONs, resulted in an optimized FSB formulation with enhanced entrapment efficiency and targeted delivery capabilities. The in situ forming hydrogel further supported the formulation's applicability for injectable applications, providing rapid gelation and sustained drug release. The in vivo results corroborate the formulation's efficacy, underscoring its potential for improving the treatment of osteoarthritis.

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Ingestion of perfluoroalkyl acids (PFAAs) via contaminated food contact materials (FCMs) is an important human exposure source. This study adopts a toxicity equivalent approach to evaluate the collective health risk of multiple PFAAs in FCMs. A comprehensive extraction and analysis of 21 PFAAs in FCMs was performed. Among the analyzed substances, 15 PFAAs were detected. Migration experiment using three food simulants revealed the migration range of seven PFAAs from FCMs into the simulant to be 0.47-46.7 ng/cm2. The hazard quotient results suggest minimal health risk, except for 9% of packaged samples where perfluorooctanoic acid (PFOA) poses a higher risk. Utilizing PFOA toxic equivalent concentrations, comprehensive risk calculations showed ∼77% of samples potentially posing elevated health risks due to PFAA exposure. This emphasizes the substantial contribution of PFAAs beyond PFOA and underscores the importance of considering them in related assessments. The aggregated risk assessment reflects actual exposure circumstances more accurately.

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Plant phenology, the timing of recurrent biological events, shows key and complex response to climate warming, with consequences for ecosystem functions and services. A key challenge for predicting plant phenology under future climates is to determine whether the phenological changes will persist with more intensive and long-term warming. Here, we conducted a meta-analysis of 103 experimental warming studies around the globe to investigate the responses of four phenophases - leaf-out, first flowering, last flowering, and leaf coloring. We showed that warming advanced leaf-out and flowering but delayed leaf coloring across herbaceous and woody plants. As the magnitude of warming increased, the response of most plant phenophases gradually leveled off for herbaceous plants, while phenology responded in proportion to warming in woody plants. We also found that the experimental effects of warming on plant phenology diminished over time across all phenophases. Specifically, the rate of changes in first flowering for herbaceous species, as well as leaf-out and leaf coloring for woody species, decreased as the experimental duration extended. Together, these results suggest that the real-world impact of global warming on plant phenology will diminish over time as temperatures continue to increase.

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Mixture experimentation is commonly seen in pharmaceutical formulation studies, where the relative proportions of the individual components are modeled for effects on product attributes. The requirement that the sum of the component proportions equals 1 has given rise to the class of designs, known as mixture designs. The first mixture designs were published by Quenouille in 1953 but it took nearly 40 years for the earliest mixture design applications to be published in the pharmaceutical sciences literature by Kettaneh-Wold in 1991 and Waaler in 1992. Since then, the advent of efficient computer algorithms to generate designs has made this class of designs easily accessible to pharmaceutical statisticians, although the use of these designs appears to be an underutilized experimental strategy even today. One goal of this tutorial is to draw the attention of experimental statisticians to this class of designs and their advantages in pursuing formulation studies such as excipient compatibility studies. We present sufficient materials to introduce the novice practitioner to this class of design, associated models, and analysis strategies. An example of a mixture-process variable design is given as a case study.

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Ferroelectric materials promise exceptional attributes including low power dissipation, fast operational speeds, enhanced endurance, and superior retention to revolutionize information technology. However, the practical application of ferroelectric-semiconductor memory devices has been significantly challenged by the incompatibility of traditional perovskite oxide ferroelectrics with metal-oxide-semiconductor technology. Recent discoveries of ferroelectricity in binary oxides such as Zn1-xMgxO and Hf1-xZrxO have been a focal point of research in ferroelectric information technology. This work investigates the ferroelectric properties of Zn1-xMgxO utilizing automated band excitation piezoresponse force microscopy. This findings reveal the coexistence of two ferroelectric subsystems within Zn1-xMgxO. A "fringing-ridge mechanism" of polarization switching is proposed that is characterized by initial lateral expansion of nucleation without significant propagation in depth, contradicting the conventional domain growth process observed in ferroelectrics. This unique polarization dynamics in Zn1-xMgxO suggests a new understanding of ferroelectric behavior, contributing to both the fundamental science of ferroelectrics and their application in information technology.

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Objective: This research aims to explore how Puerariae Lobatae Radix regulates sebaceous gland secretion using network pharmacology, and validate its effects on important targets through animal studies. Methods: This study utilized UPLC-EQ-MS to analyze Puerariae Lobatae Radix extract and identify potential bioactive compounds. Predicted targets of these compounds were obtained from the Swiss Target Prediction database, while targets associated with sebaceous gland secretion were obtained from the GeneCards database. Common targets between the databases were identified and a protein-protein interaction (PPI) network was established using the STRING platform. The PPI network was further analyzed using Cytoscape software. Pathway enrichment analysis was performed using Reactome, and molecular docking experiments targeted pivotal pathway proteins. Animal experiments were then conducted to validate the regulatory effects of the primary active compounds of Puerariae Lobatae Radix on key pathway proteins. Results: This research identified 17 active compounds in Puerariae Lobatae Radix and 163 potential targets associated with the regulation of sebum secretion. Pathway enrichment analysis indicates that these targets may modulate lipid metabolism pathways through involvement in peroxisome proliferator-activated receptor α, SREB, steroid metabolism, and arachidonic acid metabolism pathways. Molecular docking analysis demonstrates that puerarin and daidzein show favorable binding interactions with key targets in these pathways. Animal experiments demonstrated that the administration of Puerariae Lobatae Radix resulted in a significant reduction in the area of sebaceous gland patches compared to the control group. Histological analysis revealed notable alterations in the structure of sebaceous glands, including reductions in size, thickness, and density. Furthermore, the expression levels of TG, DHT, and IL-6 were significantly decreased in the Puerariae Lobatae Radix group (p < 0.05), and immunoblotting indicated a significant decrease in the expression of PPARG and ACC1 (p < 0.05). Conclusion: This study demonstrates that Puerariae Lobatae Radix can regulate skin lipid metabolism by targeting multiple pathways. The primary mechanism involves inhibiting sebaceous gland growth and reducing TG secretion by modulating the expression of PPARG and ACC1. Puerarin and Daidzein are identified as key bioactive compounds responsible for this regulatory effect. These findings highlight the therapeutic potential of Puerariae Lobatae Radix in addressing sebaceous gland-related conditions.

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CONTEXT: Most of the 11 million undocumented immigrants living in the United States are excluded from government healthcare programs. Yet, healthcare inequities pose significant dangers to all members of society during a pandemic. This project explores to what extent undocumented immigrants, in the context of a pandemic, can be seen as deserving of access to government healthcare programs. METHODS: The first survey experiment explores whether work ethic can affect perceptions of undocumented immigrants as deserving of government healthcare programs. The second survey experiment tests to what extent appeals to fairness and self-interest, during a pandemic, shape healthcare deservingness attitudes. FINDINGS: The results show that respondents view undocumented immigrants as less deserving of healthcare than citizens, even when undocumented immigrants have a solid work history. The second survey experiment, however, shows that appeals to fairness and self-interest trigger substantial increases in support for undocumented immigrants, both among Republicans and Democrats. CONCLUSIONS: The results suggest that while undocumented immigrants are seen as less deserving of access, appeals to fairness and self-interest can trigger increased support.