Multiple Aspects Research Articles

Integrated DNA barcoding methods to identify species in the processed fish products from Chinese market

DNA-based methods are reliable for a precise identification of species in processed products. In this study, we assessed five typical DNA extraction methods from multiple aspects. Full-length and mini-length DNA barcoding were performed to detect the species substitution and mislabeling of 305 processed fish products from the Chinese market covering six processed fish products. The salt extraction method that exhibited the best overall performance was applied. All samples were successfully extracted; however, only 19.3 % of samples could be amplified using the full-DNA barcode primer set, and 90.2 % of samples could be amplified using the newly designed mini-DNA barcode primer sets (401 and 320 bp). Overall, the molecular identification results revealed that 36.4 % (111/305) of the samples were inconsistent with the labels, with commercial fraud observed in all six types of processed fish products. The survey findings provide technical references for effective fish authentication monitoring, offering insights into the seafood safety in markets.

Mother–child similarity during observed interactions: Links with mother and child effortful control

AbstractObjectiveWe examined whether mothers' and child's regulatory capacity, measured by effortful control (EC) and its facets, is associated with variance in mother–child within‐dyad similarity in multiple aspects of positive emotions and behaviors during their interaction.BackgroundBoth parents' and children's self‐regulation capacities may help them to modulate their behaviors and emotions to be mutually responsive to and harmonious with their interaction partner.MethodsParticipants were children of 3‐ to‐7‐year‐olds and their mothers (n = 147). Mothers completed a set of questionnaires regarding themselves, their child, and demographics, and mother–child interactions were observed during three cooperative tasks. We estimated mother–child within‐dyad similarity during their brief interaction using the Q‐correlation method.ResultsMothers' general EC was statistically associated with greater mother–child similarity, but children's EC was not. When testing the subscales of EC, greater mother–child similarity was associated with mother's higher attentional control, child's better attention focusing, child's lower levels of low intensity pleasure, and older child age.ConclusionMother's higher attentional control and child's better attention focusing are associated with greater mother and child within‐dyad similarity during their interactions.ImplicationsThis study highlights the importance of considering child and mother self‐regulation for intervention efforts to better understand how dyads match and co‐modulate their behaviors and emotions during their interactions.

A Sparse Self-Attention Enhanced Model for Aspect-Level Sentiment Classification

Aspect based sentiment analysis (ABSA) manifests the well refined work as Aspect-level sentiment classification (ASC) due to recent high attention and profound outcomes. This paper reveals the exorbitant relation of concerned aspect in determining the sentiment polarity of a sentence in addition to their content. Considering an instance, “The food is tasty but restaurant is untidy”, aspect food reveals the polarity as positive, while in case of restaurant, the polarity seems negative. Hence to scout relation between an aspect\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$aspect$$\\end{document} and context\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$context$$\\end{document} words present in sentence is much vital. In spite of the exceptional progress, the ASC experiences certain pitfalls as (1) The current attention based methods makes the given aspect to falsely relate syntactically unrelated words as related ones. (2) Single context-independent representation is only achieved by traditional Word2Vec or GloVe based embedding vectors. (3) Sentiments for multiple words that are inconsecutive remain insufficient for CNN based models. A Sparse-Self-Attention-based Gated Recurrent Unit with Aspect Embedding (SSA-GRU-AE) implementing BERT for ASC is proposed to solve these issues. The proposed SSA-GRU-AE mechanism is centralized on various portions of sentence as multiple aspects are taken as input. The experimental analysis on ASC datasets has proved that proposed model enhanced performance on ASC.

A metabolically controlled contact site between vacuoles and lipid droplets in yeast

The lipid droplet (LD) organization proteins Ldo16 and Ldo45 affect multiple aspects of LD biology in yeast. They are linked to the LD biogenesis machinery seipin, and their loss causes defects in LD positioning, protein targeting, and breakdown. However, their molecular roles remained enigmatic. Here, we report that Ldo16/45 form a tether complex with Vac8 to create vacuole lipid droplet (vCLIP) contact sites, which can form in the absence of seipin. The phosphatidylinositol transfer protein (PITP) Pdr16 is a further vCLIP-resident recruited specifically by Ldo45. While only an LD subpopulation is engaged in vCLIPs at glucose-replete conditions, nutrient deprivation results in vCLIP expansion, and vCLIP defects impair lipophagy upon prolonged starvation. In summary, Ldo16/45 are multifunctional proteins that control the formation of a metabolically regulated contact site. Our studies suggest a link between LD biogenesis and breakdown and contribute to a deeper understanding of how lipid homeostasis is maintained during metabolic challenges.

Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon.

Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in environmental monitoring provides an opportunity to improve monitoring practices. Approaches that directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing and the site-specific community composition from environmental DNA (eDNA) can provide timely, relevant results for parties interested in the success of sustainable agricultural practices. To ensure that the measured impacts are due to the environmental projects and not exogenous factors, sites where projects have been implemented should be benchmarked against counterfactuals (no project) and control (natural habitat) sites. Results can then be used to calculate diverse sets of indicators customized to monitor different projects. Here, we report on our experience developing and applying one such approach to assess the impact of shaded cocoa projects implemented by the Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA) near São Félix do Xingu, in Pará, Brazil. We used the Continuous Degradation Detection (CODED) and LandTrendr algorithms to create a remote sensing-based assessment of forest disturbance and regeneration, estimate carbon sequestration, and changes in essential habitats. We coupled these remote sensing methods with eDNA analyses using arthropod-targeted primers by collecting soil samples from intervention and counterfactual pasture field sites and a control secondary forest. We used a custom set of indicators from the pilot application of a coupled monitoring framework called TerraBio. Our results suggest that, due to IMAFLORA's shaded cocoa projects, over 400 acres were restored in the intervention area and the community composition of arthropods in shaded cocoa is closer to second-growth forests than that of pastures. In reviewing the coupled approach, we found multiple aspects worked well, and we conclude by presenting multiple lessons learned.

Irradiance driven trophic plasticity in the coral Madracis pharensis from the Eastern Mediterranean

The distribution of symbiotic scleractinian corals is driven, in part, by light availability, as host energy demands are partially met through translocation of photosynthate. Physiological plasticity in response to environmental conditions, such as light, enables the expansion of resilient phenotypes in the face of changing environmental conditions. Here we compared the physiology, morphology, and taxonomy of the host and endosymbionts of individual Madracis pharensis corals exposed to dramatically different light conditions based on colony orientation on the surface of a shipwreck at 30 m depth in the Bay of Haifa, Israel. We found significant differences in symbiont species consortia, photophysiology, and stable isotopes, suggesting that these corals can adjust multiple aspects of host and symbiont physiology in response to light availability. These results highlight the potential of corals to switch to a predominantly heterotrophic diet when light availability and/or symbiont densities are too low to sustain sufficient photosynthesis, which may provide resilience for corals in the face of climate change.

Advances in paleoclimatology

ABSTRACT There is an urgent need for information on the Earth’s climate beyond the limited history provided in the instrumental record. Paleoclimate information provides a baseline for understanding natural climate variability and how human activities have altered the climate. Paleoclimate reconstructions also allow us to estimate the potential impacts of climate change on multiple aspects of the climate system. Over the past three decades, paleoclimatologists have made great advances in using climate proxies, natural archives of climate conditions, to better understand climates of the past. Here, we categorize the main types of advancements made over recent decades, which include the discovery of new proxies and new measurements from existing proxies, the reconstruction of novel components of the climate system, the geographical expansion of paleoclimate records, and the integration of multiple proxies and models. We provide examples of published research in each category from across the field of paleoclimatology, and we end with a summary of remaining knowledge gaps and emerging questions that will require continued paleoclimate research progress in the future.

A Versatile Intestine-on-Chip System for Deciphering the Immunopathogenesis of Inflammatory Bowel Disease.

The multifactorial nature of inflammatory bowel disease (IBD) necessitates reliable and practical experimental models to elucidate its etiology and pathogenesis. To model the intestinal microenvironment at the onset of IBD in vitro, it is important to incorporate relevant cellular and noncellular components before inducing stepwise pathogenic developments. A novel intestine-on-chip system for investigating multiple aspects of IBD's immunopathogenesis is presented. The system includes an array of tight and polarized barrier models formed from intestinal epithelial cells on an in-vivo-like subepithelial matrix within one week. The dynamic remodeling of the subepithelial matrix by cells or their secretome demonstrates the physiological relevance of the on-chip barrier models. The system design enables introduction of various immune cell types and inflammatory stimuli at specific locations in the same barrier model, which facilitates investigations of the distinct roles of each cell type in intestinal inflammation development. It is showed that inflammatory behavior manifests in an upregulated expression of inflammatory markers and cytokines (TNF-α). The neutralizing effect of the anti-inflammatory antibody Infliximab on levels of TNF-α and its inducible cytokines could be explicitly shown. Overall, an innovative approach to systematically developing a microphysiological system to comprehend immune-system-mediated disorders of IBD and to identify new therapeutic strategies is presented.

Including the perspective of stakeholders in landscape planning through the Ecosystem Services co-production framework: an empirical exploration in Le Marche, Italy

Research on Ecosystem Services (ES) has become dominant in landscape planning to frame the relationship between people and nature. Increasingly, studies are stressing that most ES do not flow from nature alone but require a significant human contribution, known as ES co-production. However, there is a lack of understanding on how different stakeholders contribute to ES co-production. Here, we integrated stakeholders’ perspectives in landscape planning using questionnaires and focus groups in a case study in Le Marche, Italy. We found that respondents acknowledge co-production in a wide range of ES with a major share of cultural ES. Mostly self-perceived as users and managers, local stakeholders invest in their activities mainly human and social capitals, while physical and financial capitals gain importance in the case of provisioning services. Our findings embraced the multiple aspects of human-nature interactions, offering the opportunity to bridge different sectors, such as agriculture, eco-tourism, and resilience against extreme events, toward a multifunctional vision of landscapes. The integration of the ES co-production framework proved useful in fostering the access of stakeholders to decision-making.

Prediction and analysis of breast cancer based on transfer learning from DDSM mammography images

Breast cancer is a cancer mostly found in women, causing a high morality rate. It appears as a lump in the breast initially, and as cancer cells spread, the other organs are endangered. Research shows that the earlier the breast cancer is detected, the higher rate of recovering will be. The main methods of breast cancer detection are mainly using various physical methods to probe the internal condition of the patients breast. Breast X-ray imaging, also known as mammography, is the most widely used. It uses low-dose X-ray technology to observe the breast tissue and help doctors figure out the exact condition of the patient. With the advancements in deep learning and image recognition, the analysis of mammograms can be previously done by the computer, easing the pressure on doctors. Digital Database for Screening Mammography (DDSM) dataset is a mammography dataset specifically designed for the development of mammography detection models. It contains huge amounts of mammograms and provides the labels corresponding to them. In this study, the performances of normal deep learning model and transfer learning model on the DDSM dataset are compared. Pretrained neural network models are employed and fine-tuned on the DDSM dataset to adapt to the features of mammographic images. Experimental results demonstrate significant improvements through transfer learning, outperforming traditional methods with Convolutional Neural Network (CNN). Finally, the models are evaluated in multiple aspects, conclusions and prospects are analysed based on the results.

An Individual Music Intervention for Adults With Intellectual Disabilities and Challenging Behavior: Protocol for a Randomized Controlled Trial.

Individuals with intellectual disabilities (ID) are more likely to have problems with executive functioning (EF) and challenging behavior (CB), which are negatively linked to well-being. Among clinical populations, music interventions have been shown to improve various outcome measures, such as CB and EF. Until now, no randomized controlled trials (RCTs) have been conducted to examine the effectiveness of an individual music intervention for adults with ID and CB. The study aims to identify the effect and feasibility of an individual music intervention compared with care-as-usual for people with ID and CB. In this study, a 2-group RCT with a pretest, posttest, and follow-up assessment after 8 weeks is presented. Participants of the music intervention condition will receive 16 individual music sessions within 8 to 10 weeks. The music intervention will be guided by a manual for music workers, in which every session will have a different focus (introduction, emotions, different EF, and end performance). Participants receiving care as usual will function as a control group. After the research is finished, they will be offered a budget, which they can spend on musical activities or musical instruments as they wish. Assessments will include caregiver rating scales and self-report questionnaires and tests, which will assess outcome measures of CB, well-being, depression, anxiety, self-esteem, and 4 domains of EF. A process evaluation will be conducted after the completion of the study, which entails the analysis of data on multiple aspects of the intervention and the study overall. Enrollment commenced in July 2021, and data collection ended in May 2023. A total of 97 participants were recruited, with 44 participants allocated to the intervention group and 53 allocated to the control group. Data will be analyzed after this protocol has been accepted for publication. Because there are currently no published RCTs of an individual music intervention for adults with ID and CB, this study will provide insight into the effectiveness and experiences of an individual music intervention for this target group. International Clinical Trials Registry Platform NL8482; http://tinyurl.com/4565s5pd. DERR1-10.2196/52497.

The emotional impact of uncomplicated urinary tract infections in women in China and Japan: a qualitative study

BackgroundUncomplicated urinary tract infections (uUTIs) are one of the most common community-acquired infections, particularly among women. Common symptoms of UTI include dysuria, urinary urgency and increased frequency, and lower abdominal pain. With appropriate treatment, symptoms may resolve in a few days. However, there is a lack of research on the emotional impact of this disease. We conducted a qualitative, interview-based study to gain a greater understanding of the emotional impact of uUTIs in women in China and Japan.MethodsA qualitative, exploratory, in-depth, interview-based study was conducted between 19 November 2020 and 25 February 2021. Women aged ≥ 18 years who experienced ≥ 1 uUTI and received antibiotic treatment in the past year were eligible for inclusion. Participants must have experienced ≥ 1 of the following symptoms during a uUTI episode: urinary urgency, frequency, dysuria, or lower abdominal/suprapubic pain. Participants who reported back pain or fever (indicative of complicated UTI) were excluded. Participants with recurrent or sporadic UTIs were included, with specific screening criteria used to ensure capture of both groups. Following a screening call, a structured, in-depth telephone interview (~ 30 min in duration) was conducted by three female external moderators trained in qualitative interviewing, assisted by an interview guide. Interviews were analysed individually and thematically, with the results presented within the identified themes.ResultsA total of 65 women with uUTI completed the in-depth telephone interview: 40 (62%) from China and 25 (38%) from Japan. Participants reported that the symptoms of uUTI affected multiple aspects of their lives, and described feelings of embarrassment, frustration, guilt, dread, and loneliness associated with symptoms that interfered with relationships, work and daily activities, and sleep. Participants reported seeking healthcare from several different points of contact, from local pharmacies to hospitals.ConclusionsOur analysis highlights the profound emotional impact of uUTIs in women in China and Japan, and the journey these participants take before their initial interaction with a healthcare professional. These insights emphasise the need to better understand the full impact of uUTI, and the role of healthcare professionals in improved patient education and support.

A holistic approach to environmentally sustainable computing

AbstractPlacing sustainability at the core of computing practices, the industry is poised to pioneer positive changes and create a cleaner and more sustainable world for future generations. The environmentally sustainable computing (ESC) framework is introduced in this paper as an innovative solution to revolutionize sustainability practices across various computing domains and cover multiple aspects of sustainable information technology (IT). The ESC framework includes the entire lifecycle of computing systems, including critical stages such as design, development, monitoring, refactoring, and regulatory compliance. Through the adoption of the ESC framework, academia and industry stakeholders can gain a powerful tool to evaluate and measure sustainability factors across different computing domains and can integrate eco-friendly computing principles and patterns throughout their products and services. This can significantly reduce their carbon footprint while complying with environmental regulations. In addition to presenting the ESC framework, the paper showcases real-world use cases. The first involves a leading Italian bank, emphasizing the significance of monitoring and compliance in achieving sustainable solutions within carbon-aware computing. The second use case explores resource efficiency optimization in Kubernetes clusters, illustrating how the ESC framework aligns with cloud infrastructure management trends.

Musculoskeletal Pain Characteristics and Objectively Measured Physical Activity in Older Adults.

Pain is associated with reports of restricted physical activity (PA), yet the association between musculoskeletal pain characteristics and objectively measured PA quantities and patterns in late life is not well understood. A total of 553 adults (mean age 75.8 ± 8.4 years, 54.4% women) in the Baltimore Longitudinal Study of Aging (BLSA) completed a health interview and subsequent 7-day wrist-worn ActiGraph assessment in the free-living environment between 2015 and 2020. Pain characteristics, including pain presence in 6x sites (ie, shoulders, hands/wrists, low back, hip, knees, and feet), pain laterality in each site, and pain distribution were assessed. PA metrics were summarized into total daily activity counts (TAC), activity fragmentation, active minutes/day, and diurnal patterns of activity. Linear regression models and mixed-effects models examined the association between pain characteristics and PA outcomes, adjusted for demographics and comorbidities. Unilateral knee pain was associated with 184 070 fewer TAC (p = .039) and 36.2 fewer active minutes/day (p = .032) compared to those without knee pain. Older adults with shoulder pain or hand/wrist pain had more active minutes compared to those without pain (p < .05 for all). For diurnal patterns of activity, participants with knee pain had fewer activity counts during the afternoon (12:00 pm to 5:59 pm). Analyses stratified by sex showed that these associations were only significant among women. Our study highlights the importance of assessing pain laterality in addition to pain presence and suggests that pain interferes with multiple aspects of daily activity. Longitudinal studies are needed to assess the temporality of these findings.

Aggregating knowledge and collaborative information for sequential recommendation

Sequential recommendation aims to predict users’ future activities based on their historical interaction sequences. Various neural network architectures, such as Recurrent Neural Networks (RNN), Graph Neural Networks (GNN), and self-attention mechanisms, have been employed in the tasks, exploring multiple aspects of user preferences, including general interests, short-term interests, long-term interests, and item co-occurrence patterns. Despite achieving good performance, there are still limitations in capturing complex user preferences. Specifically, the current structures of RNN, GNN, etc., only capture item-level transition relations while neglecting attribute-level transition relations. Additionally, the explicit item relations are studied using item co-occurrence modules, but they cannot capture the implicit item-item relations. To address these issues, we propose a knowledge-augmented Gated Recurrent Unit (GRU) to improve the short-term user interest module and adopt a collaborative item aggregation method to enhance the item co-occurrence module. Additionally, our long-term interest module utilizes a bitwise gating mechanism to select historical item features significant to users’ current preferences. We extensively evaluate our model on three real-world datasets alongside competitive methods, demonstrating its effectiveness in top K sequential recommendation.

Patients’ perspectives on systemic sclerosis-related Raynaud's phenomenon in the feet: A qualitative study from the OMERACT Foot and Ankle Working Group

ObjectiveTo explore, from patients’ perspectives, the symptoms and impact of Raynaud's phenomenon (RP) on the feet of patients with systemic sclerosis (SSc-RP), and to identify which foot-related domains are important to patients. MethodsForty participants (34 women) with SSc-RP took part in one of six focus groups held in the United Kingdom or United States. Participants were purposively sampled to ensure diversity in disease type, duration, and ethnicity. The topic guide included questions on RP impact, self-management, and treatment expectations. Qualitative content analysis was employed to identify key concepts in the data relating to foot-specific symptoms and their impact. Themes were organized by corresponding domains of potential importance. ResultsTwenty-eight participants (70 %) reported experiencing RP in their feet. Five themes were identified corresponding to domains of potential importance: temperature changes, pain, cramping and stiffness, numbness, and color changes. These issues negatively affected participants’ lives, impairing walking, driving, and socializing, and causing issues with footwear and hosiery. ConclusionsThis large qualitative study exploring the experiences of patients with SSc-RP in the feet identified several key domains of high importance to patients. SSc-RP is common in the feet, presents in several patterns, and impacts multiple aspects of patients’ lives. These findings indicate where future foot-specific interventions for RP could be targeted. Findings from this study improve understanding of what domains are important to patients with SSc-RP affecting the feet and will contribute to the development of a core outcome set for foot and ankle disorders in rheumatic and musculoskeletal diseases.

Large eddy simulation of end effects on a cylinder rotor

Due to the limited length of cylinders, their use in practical engineering inevitably involves end effects, which results in three-dimensional flows at the ends of cylinders. These flow fields are the main factor influencing the aerodynamic and flow field characteristics of cylinders. Regarding a finite-length cylinder rotor, a specific pattern of tip vortices will form under the action of rotation, resulting in notable differences in the aerodynamic characteristics between an ideal two-dimensional cylinder and a finite-length cylindrical rotor. In the present study, the large eddy simulation method is used to systematically investigate cylinder rotors with various aspect ratios. By analyzing the sectional aerodynamic and flow field characteristics, the variation laws of the aerodynamic force, wind pressure, and flow field characteristics of cylinder rotors under the influence of end effects were summarized. The results show that the influence range and intensity of the tip vortices on the rotor flow field and sectional aerodynamic characteristics are dominated by the dimensionless rotating speed, which in turn affects the range of the end effects. The development trend of the tip vortices is analyzed and discussed from multiple aspects, including sectional aerodynamics, the pressure coefficient, and the flow correlation, and an attempt is made to explain changes in the phenomenon.

Evaluation of citric acid-treated natural fibres as sustainable additives for improving expansive soil performance in highway construction

This study addresses the evaluation of citric acid-treated natural fibres as sustainable additives for improving soil performance in highway construction. A series of tests were conducted on the soil to assess its baseline properties. The natural soil exhibited a Plasticity Index (PI) of 30 and Linear Shrinkage of 12%, along with a Liquid Limit (LL) of 65 and Plastic Limit (PL) of 35. Additionally, the fines content (<0.075 mm) and sand content (0.075–4.7 mm) were determined to be 79.6% and 20.4%, respectively. The soil's mineral composition included Quartz (5%), Orthoclase (3–5%), Montmorillonite (2.6%), and Illite (18.2%), with key components identified through chemical analysis: SiO2 (52.721 wt%), Fe2O3 (16.132 wt%), and Al2O3 (15.202 wt%). Subsequently, a range of tests were performed with varying additives to assess their impact on the soil's engineering properties. The sample containing 6% Sawdust (SD) additive exhibited notable improvements in multiple aspects. This sample achieved a maximum dry density (MDD) of 1856 kg/m³, surpassing the control (1900 kg/m³) and the 10% Rice Husk Ash (RHF) sample (1698 kg/m³). Furthermore, the 6% SD sample demonstrated enhanced Unconfined Compressive Strength (UCS) of 320 kPa, as opposed to the control's 121 kPa. Triaxial shear strength followed a similar pattern, peaking at 41 kPa for the 6% SD sample. The California Bearing Ratio (CBR), the 6% SD sample showcased significant improvements, achieving 41% for Unsoaked CBR and 36% for Soaked CBR. These results outperformed the control (25%) and the 4% RHF sample (37%). Additionally, the hydraulic conductivity of the 6% SD sample was notably lower at 4.98 ×10–8 cm/s compared to the control (3.35 ×10–8 cm/s) and the 4% RHF sample (4.58 ×10–8 cm/s). The Coefficient of Volume Change (Mv) further supported the superior performance of the 6% SD sample with a value of 0.6, indicating reduced settlement potential compared to the 4% RHF sample (Mv: 0.7). Based on the results, the 6% Sawdust (SD) additive consistently demonstrated the most favourable engineering properties for the expansive clay soil. hence, it is recommended that the 6% SD sample be considered as an optimal choice for enhancing subgrade material, leading to improved performance and sustainability in highway construction.

Constituents, pharmacological activities, pharmacokinetic studies, clinical applications, and safety profile on the classical prescription Kaixinsan.

Kaixinsan (KXS) is a noteworthy classical prescription, which consists of four Chinese medicinal herbs, namely Polygalae Radix, Ginseng Radix et Rhizoma, Poria, and Acori Tatarinowii Rhizoma. KXS was initially documented in the Chinese ancient book Beiji Qianjin Yaofang written by Sun Simiao of the Tang Dynasty in 652 A.D. As a traditional Chinese medicine (TCM) prescription, it functions to nourish the heart and replenish Qi, calm the heart tranquilize the mind, and excrete dampness. Originally used to treat amnesia, it is now also effective in memory decline and applied to depression. Although there remains an abundance of literature investigating KXS from multiple aspects, few reviews summarize the features and research, which impedes better exploration and exploitation of KXS. This article intends to comprehensively analyze and summarize up-to-date information concerning the chemical constituents, pharmacology, pharmacokinetics, clinical applications, and safety of KXS based on the scientific literature, as well as to examine possible scientific gaps in current research and tackle issues in the next step. The chemical constituents of KXS primarily consist of saponins, xanthones, oligosaccharide esters, triterpenoids, volatile oils, and flavonoids. Of these, saponins are the predominant active ingredients, and increasing evidence has indicated that they exert therapeutic properties against mental disease. Pharmacokinetic research has illustrated that the crucial exposed substances in rat plasma after KXS administration are ginsenoside Re (GRe), ginsenoside Rb1 (GRb1), and polygalaxanthone III (POL). This article provides additional descriptions of the safety. In this review, current issues are highlighted to guide further comprehensive research of KXS and other classical prescriptions.

Abstract IA019: Multiscale systems approach to target tumor ecosystem responses for therapeutic benefit

Abstract Breast tumors arise and progress via processes that involve intrinsic deregulation of epithelial cells and that also alter the composition and function of associated stromal and immune cells. Together, these tumor-intrinsic and microenvironmental changes enable malignant epithelial cells in the tumor to acquire key cancer hallmarks, including proliferation, migration, immune evasion and further evolution. The resulting collection of cancer and stromal cells comprise a complex, adaptive tumor ecosystem. Long-term therapeutic success will require that drugs attack malignant cells, favorably activate the immune system, and create a tumor microenvironment that does not support tumor (re)growth. Creating a process for treatment selection will require an integrated systems biology approach to develop, test and refine a robust computational framework that takes into account the states, signaling relationships, and spatial organization that determine the emergent properties inherent in complex interacting systems. Toward this goal, we have developed a coordinated experimental-computational approach designed to enable identification of effective treatment strategies. To examine therapeutic responses of diverse aspects of the tumor ecosystem, we have deployed a novel drug delivery microdevice that enables rapid, high-throughput assessment of the effects of multiple therapies on tumor cells and the surrounding microenvironment. When coupled with multiplex tissue imaging, this platform provides a comprehensive assessment of the state and spatial organization of the tumor ecosystem as it adapts to therapy. Initial studies demonstrated that many drugs designed to target malignant epithelial cells strongly impact stromal and immune cells, providing new insights into the importance of considering multiple aspects of the tumor ecosystem when designing effective therapeutic strategies. The resultant data are being used to guide development of a multiscale computational model that considers the functional relationships between different tumor components and can be used to predict the effects of therapies on diverse aspects of tumor ecosystems. In total, our approach has the potential to transform cancer treatments through rational identification of effective therapeutic strategies that lead to long-term durable control of tumors. Citation Format: Laura M. Heiser. Multiscale systems approach to target tumor ecosystem responses for therapeutic benefit [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA019.