Hepatocellular cancer (HCC) is one of the main reasons for liver transplantation (LT). Biomarkers, such as alpha-foetoprotein (AFP) and Des-gamma-carboxy-prothrombin (DCP), can be helpful in defining the recurrence risk post LT. This study aims to evaluate the association between the intensity of DCP immunohistochemical labelling and serum DCP levels in patients undergoing LT for HCC. We carried out a prospective monocentric study including patients who all underwent LT for cirrhosis between 2016 and 2018 and all fell under the Milan criteria. The accepted diagnostic criteria for HCC were contrast-enhanced imaging and histology. Thirty-nine patients were followed for a median of 21 months, with HCC lesions categorized into negative, focally positive, and diffusely positive groups based on DCP immunohistochemistry. The serum DCP levels were significantly higher in the positive groups (258 mAU/mL for the focally and 257 mAU/mL for the diffusely positive) than in the negative group (48 mAU/mL) (p = 0.005) at diagnosis and at the time of liver transplantation (220 mAU/mL for the diffuse positive group). Microvascular invasion (58.8% vs. 19.0% for the diffusely positive and negative groups, respectively, p < 0.001) and lesion size (20 mm in the diffusely labelled group versus 12 mm in the other groups, p = 0.002) were significantly correlated with DCP labelling. Late recurrence occurred only in the positive groups; in the negative group, it occurred within the first 3 months after transplantation. DCP labelling in liver lesions correlates with serum levels and a more aggressive tumour profile. Further investigation is needed to determine if highly DCP-labelled tumours allow for the better selection of high-risk patients before LT. Full article

The ceramic pastes of ca. 31 samples recovered from the Almaraz archaeological site, located in the south bench of Tagus River, were studied in detail using XRF, micro-Raman and GSDR spectroscopies, as well as the XRD technique. The ceramic sherds could be grouped into six categories, red slip tableware, decorated tableware, yellow slip tableware, grey tableware, common tableware, and handmade pottery. Our studies of the mineralogic composition of the sherds’ body indicate all ceramics were produced locally, using siliceous clays in most cases and calcareous clays in a few ones. Micro-Raman and ground state diffuse reflectance absorption spectroscopy provided useful information regarding the materials used to produce the coloured ceramics: hematite and brookite for the red slip and decorated ceramics, jacobsite or carbon black for the black decoration or grey ceramics. For the yellow slip tableware, a simple engobe rich in yellow clay was used. XRF spectroscopic studies provided the elemental composition of all samples, and biplots of the potassium (K) versus calcium (Ca) contents, normalized to the silicon content of each ceramic paste, clearly show Pliocene and Miocene local clays sources were used to produce most ceramics. Only one sherd can be considered a Lisbon production. Full article

The article analyses the impact of two different types of dispersive glass on cement hydration and compressive strength at 7 and 28 days. The study employed dispersive glass from various LCDs (TV sets, computer monitors, smart phones), characterised by a composition of approximately 8% SrO, and dispersive glass from washing machines, which consists mainly of SiO₂, Na₂O, and CaO. The chemical composition and particle-size distribution of different types of dispersive glass were analysed. The study compares the effect of electronic waste glass on cement hydration by evaluating the amount and rate of heat released during the process. In addition, the results of X-ray diffraction (XRD), thermogravimetric analysis (TG), and scanning electron microscopy (SEM) are provided. Different types of glass were determined to have a similar effect on the physical and mechanical properties as well as the mineral composition of cementitious samples: density and UPV decrease up to 6% and compressive strength decreases by about 30%, when 5–20% of cement was replaced by glass waste. However, more prominent differences were observed in the workability of the mixtures: the waste glass from home appliances increased the spread by up to 25%, while the waste glass from electronic devices decreased the spread compared to the reference sample by approximately 20%. The mixtures modified with the waste glass of electronic devices had a higher degree of early hydration (96%) due to the higher water absorption of the mixtures compared to the waste glass of home appliances (88%). Full article

In developing nations, outdated technologies and sulfur-rich heavy fossil fuel usage are major contributors to air pollution, affecting urban air quality and public health. In addition, the limited resources hinder the adoption of advanced monitoring systems crucial for informed public health policies. This study addresses this challenge by introducing an affordable internet of things (IoT) monitoring system capable of tracking atmospheric pollutants and meteorological parameters. The IoT platform combines a Bresser 5-in-1 weather station with a previously developed air quality monitoring device equipped with Alphasense gas sensors. Utilizing MQTT, Node-RED, InfluxDB, and Grafana, a Raspberry Pi collects, processes, and visualizes the data it receives from the measuring device by LoRa. To validate system performance, a 15-day field campaign was conducted in Santa Clara, Cuba, using a Libelium Smart Environment Pro as a reference. The system, with a development cost several times lower than Libelium and measuring a greater number of variables, provided reliable data to address air quality issues and support health-related decision making, overcoming resource and budget constraints. The results showed that the IoT architecture has the capacity to process measurements in tropical conditions. The meteorological data provide deeper insights into events of poorer air quality. Full article

The Shack–Hartmann wavefront sensor (SHWFS) is widely utilized for ocular aberration measurement. However, large ocular aberrations caused by individual differences can easily make the spot move out of the range of the corresponding sub-aperture in SHWFS, rendering the traditional centroiding method ineffective. This study applied a novel convolutional neural network (CNN) model to wavefront sensing for large dynamic ocular aberration measurement. The simulation results demonstrate that, compared to the modal method, the dynamic range of our method for main low-order aberrations in ocular system is increased by 1.86 to 43.88 times in variety. Meanwhile, the proposed method also has the best measurement accuracy, and the statistical root mean square (RMS) of the residual wavefronts is 0.0082 ± 0.0185 $\lambda$ (mean ± standard deviation). The proposed method generally has a higher accuracy while having a similar or even better dynamic range as compared to traditional large-dynamic schemes. On the other hand, compared with recently developed deep learning methods, the proposed method has a much larger dynamic range and better measurement accuracy. Full article

Background: Sarcopenia is defined as a loss of muscle mass, strength, and physical function associated with aging. It is due to a combination of genetic, environmental, and physiological factors. It is also associated with an increased risk of health problems. Since there are many different researchers in the field, with their own algorithms and cut-off points, there is no single criterion for diagnosis. This review aims to compare the prevalence of sarcopenia according to these different diagnostic criteria in older adult populations by age group and sex. Methods: Different databases were searched: Web of Science, Pubmed, Dialnet, Scopus, and Cochrane. The keywords used were “sarcopenia”, “diagnosis”, “prevalence”, “assessment”, “aged”, “aging” and “older”. Studies conducted in a population aged ≥65 assessing the prevalence of sarcopenia were selected. Results: Nineteen articles met the inclusion criteria, with a total of 33,515 subjects, 38.08% female and 61.42% male, at a mean age of 74.52. The diagnostic algorithms used were 52.63% AWGS2, 21.05% EWGSOP2, 10.53% AWGS1 and EWGS1, and 5.26% FNIH. Prevalence ranged from 1.7% to 37.47%, but was higher in males and increased with age. Conclusions: The prevalence of sarcopenia varies depending on the diagnostic algorithm used, but it increases with age and is higher in men. The EWGSOP2 and AWGS2 are the most used diagnostic criteria and measure the same variables but have different cut-off points. Of these two diagnostic algorithms, the one with the highest prevalence of sarcopenia and severe sarcopenia is the AWGS2. These differences may be due to the use of different tools and cut-off points. Therefore, a universal diagnostic criterion should be developed to allow early diagnosis of sarcopenia. Full article

The rough morphology at the growth surface results in the non-uniform distribution of indium composition, intentionally or unintentionally doped impurity, and thus impacts the performance of GaN-based optoelectronic and vertical power electronic devices. We observed the morphologies of unintentionally doped GaN homo-epitaxially grown via MOCVD and identified the relations between rough surfaces and the miscut angle and direction of the substrate. The growth kinetics under the effect of the Ehrlich–Schwoebel barrier were studied, and it was found that asymmetric step motions in samples with a large miscut angle or those grown at high temperature were the causes of step-bunching. Meandering steps were believed to be caused by surface free energy minimization for steps with wide terraces or deviating from the $[1\overline{1}00]$ m-direction. Full article

Thermoelectric power can convert heat and electricity directly and reversibly. Low-dimensional thermoelectric materials, particularly thin films, have been considered a breakthrough for separating electronic and thermal transport relationships. In this study, a series of Bi_0.5Sb_1.5Te₃ thin films with thicknesses of 0.125, 0.25, 0.5, and 1 μm have been fabricated by RF sputtering for the study of thickness effects on thermoelectric properties. We demonstrated that microstructure (texture) changes highly correlate with the growth thickness in the films, and equilibrium annealing significantly improves the thermoelectric performance, resulting in a remarkable enhancement in the thermoelectric performance. Consequently, the 0.5 μm thin films achieve an exceptional power factor of 18.1 μWcm⁻¹K⁻² at 400 K. Furthermore, we utilize a novel method that involves exfoliating a nanosized film and cutting with a focused ion beam, enabling precise in-plane thermal conductivity measurements through the 3ω method. We obtain the in-plane thermal conductivity as low as 0.3 Wm⁻¹K⁻¹, leading to a maximum ZT of 1.86, nearing room temperature. Our results provide significant insights into advanced thin-film thermoelectric design and fabrication, boosting high-performance systems. Full article

This research investigates the influence of synthesis kinetics on the structural and photocatalytic properties of chitosan–clay nanocomposites (Cs/MMT) and chitosan–hectorite nanocomposites (Cs/HET), employing an optimized initial stoichiometry of 1:3. Utilizing a variety of analytical techniques, including X-ray diffraction (XRD), transmission electron microscopy (TEM), and Fourier-transform infrared spectroscopy (FTIR), the study explores the structural evolution of the nanocomposites and their photocatalytic performance using semiconductor catalysts TiO₂ and ZnO. The findings emphasize the significant impact of reaction kinetics, particularly after 3 h of reaction time, on the structural features of the nanocomposites. Notably, Cs/MMT demonstrates greater crystalline stability compared to Cs/HET due to variations in octahedral cavity occupancy in the initial clays. FTIR and TEM analyses depict the progressive evolution of the nanocomposites during the reaction, shedding light on how reaction kinetics drive the formation of specific bonds within the nanocomposites. In terms of photocatalytic activity, this study provides insights into the complex dynamics of photocatalytic degradation, with a specific focus on the performance of TiO₂ and ZnO under diverse experimental conditions. The superior efficacy of TiO₂ as a catalyst, particularly when integrated with Cs/MMT nanocomposites, is unequivocally demonstrated, with degradation rates exceeding 80%. This preference stems from TiO₂ consistently exhibiting higher degradation rates compared to ZnO, attributed to structural disparities between montmorillonite and hectorite, influencing catalyst–support interactions. The findings underscore the critical importance of selecting suitable catalyst and support matrix combinations for optimizing performance in specific applications. Full article

This study assessed the prevalence of myopia, cataracts, glaucoma, and macular degeneration among Koreans over 40, utilizing data from the 7th Korea National Health and Nutrition Examination Survey (KNHANES VII, 2018). We analyzed 204,973 adults (44% men, 56% women; mean age 58.70 ± 10.75 years), exploring the association between myopia and these eye diseases through multivariate logistic regression, adjusting for confounders and calculating adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Results showed a myopia prevalence of 44.6%, cataracts at 19.4%, macular degeneration at 16.2%, and glaucoma at 2.3%, with significant differences across ages and genders. A potential link was found between myopia and an increased risk of cataracts and macular degeneration, but not with glaucoma. Additionally, a higher dietary intake of carbohydrates, polyunsaturated and n-6 fatty acids, vitamins, and minerals correlated with lower risks of these diseases, underscoring the importance of the diet in managing and preventing age-related eye conditions. These findings highlight the need for dietary considerations in public health strategies and confirm myopia as a significant risk factor for specific eye diseases in the aging Korean population. Full article

In cholinergic urticaria (CholU), small, itchy wheals are induced by exercise or passive warming and reduced sweating has been reported. Despite the described reduced muscarinic receptor expression, sweat duct obstruction, or sweat allergy, the underlying pathomechanisms are not well understood. To gain further insights, we collected skin biopsies before and after pulse-controlled ergometry and sweat after sauna provocation from CholU patients as well as healthy controls. CholU patients displayed partially severely reduced local sweating, yet total sweat volume was unaltered. However, sweat electrolyte composition was altered, with increased K⁺ concentration in CholU patients. Formalin-fixed, paraffin-embedded biopsies were stained to explore sweat leakage and tight junction protein expression. Dermcidin staining was not found outside the sweat glands. In the secretory coils of sweat glands, the distribution of claudin-3 and -10b as well as occludin was altered, but the zonula occludens-1 location was unchanged. In all, dermcidin and tight junction protein staining suggests an intact barrier with reduced sweat production capability in CholU patients. For future studies, an ex vivo skin model for quantification of sweat secretion was established, in which sweat secretion could be pharmacologically stimulated or blocked. This ex vivo model will be used to further investigate sweat gland function in CholU patients and decipher the underlying pathomechanism(s). Full article

An optimization model that may be applied to analyze building retrofit strategies is presented in this research. The aim of this research paper is to identify the optimal thermal envelope configuration that will assure the minimum energy requirement for heating in the case of a residential building, while also considering price restrictions obtained through a specific market survey. To achieve this, several values for the following parameters are considered: thermal insulation materials’ conductivities and thicknesses, windows’ overall heat transfer coefficients and total solar energy transmittance and doors’ thermal proprieties. Additionally, this paper presents a method used to find the best option from among the available heat pumps that could cover most of the energy requirements for heating and domestic hot water systems, also considering the products’ prices. The proposed method is based on a Non-dominated Sorting Genetic Algorithm II (NSGA-II) model developed in the Pymoo (Multi-Objective Optimization in Python) library. The result shows that the energy requirement for heating can be reduced by up to approximately 75% compared to that obtained in the case of a non-insulated building by using suitable insulation materials and doors and windows with superior thermal proprieties chosen by the NSGA-II. Full article

This study explores the nexus between digital financial inclusion and household participation in commercial insurance, utilizing data from the Peking University Digital Financial Inclusion Index and the 2018 CFPS database. Using Probit and Logit models, our research uncovers significant regional and risk -preference variations, emphasizing the influence of governance mechanisms. The study underscores the pivotal role of digital participation in a sustainable governance mechanism in shaping financial behavior, as well as the importance of advocating for regulatory interventions, enhanced financial literacy, and infrastructure development to foster equitable insurance access. Moreover, positive determinants, such as education level and social insurance participation, are identified, while discretionary spending emerges as a barrier. This study advocates for expedited digital financial inclusion initiatives to increase financial literacy with strengthened regulatory oversight and governance mechanisms which would ensure sustainable regional development and insurance market resilience. Full article

It is crucial to speed up the training process of multivariate deep learning models for forecasting time series data in a real-time adaptive computing service with automated feature engineering. Multivariate time series decomposition and recombining (MTS-DR) is proposed for this purpose with better accuracy. A proposed MTS-DR model was built to prove that not only the training time is shortened but also the error loss is slightly reduced. A case study is for demonstrating air quality forecasting in sub-tropical urban cities. Since MTS decomposition reduces complexity and makes the features to be explored easier, the speed of deep learning models as well as their accuracy are improved. The experiments show it is easier to train the trend component, and there is no need to train the seasonal component with zero MSE. All forecast results are visualized to show that the total training time has been shortened greatly and that the forecast is ideal for changing trends. The proposed method is also suitable for other time series MTS with seasonal oscillations since it was applied to the datasets of six different kinds of air pollutants individually. Thus, this proposed method has some commonality and could be applied to other datasets with obvious seasonality. Full article

Water pipe failures result in real water losses in the form of water outflowing into the porous medium, such as the surrounding soil. Such an outflow may result in the creation of suffosion holes. The appropriate management of the water supply network may contribute to reducing the number of failures, but due to their random nature, it is not possible to completely eliminate them. Therefore, alternative solutions are being sought to reduce the effects of the failures. This article presents a fragment of the results from a broader scope of the research, which attempted to determine the outflow zone in relation to the fractal characteristics of water outflows. The research included the analysis of the actual geometric structures created by the water outflows, which were simplified into linear structures using isometric transformations. The structures were analyzed in terms of the parameters characterizing them, including their fractal dimensions. As a result, it was found that there was no relationship between the analyzed fractal parameters and the leakage area or hydraulic pressure in the water pipe. However, the influence of the number of points forming each linear structure on the analyzed parameters was shown. This allowed for the determination of further research aimed at estimating the size of the water outflow zone after the unsealing of an underground water supply pipe. Full article

Attention plays an important role in not only the awareness and perception of tinnitus but also its interactions with external sounds. Recent evidence suggests that attention is heightened in the tinnitus brain, likely as a result of relatively local cortical changes specific to deafferentation sites or global changes that help maintain normal cognitive capabilities in individuals with hearing loss. However, most electrophysiological studies have used passive listening paradigms to probe the tinnitus brain and produced mixed results in terms of finding a distinctive biomarker for tinnitus. Here, we designed a selective attention task, in which human adults attended to one of two interleaved tonal (500 Hz and 5 kHz) sequences. In total, 16 tinnitus (5 females) and 13 age- and hearing-matched control (8 females) subjects participated in the study, with the tinnitus subjects matching the tinnitus pitch to 5.4 kHz (range = 1.9–10.8 kHz). Cortical responses were recorded in both passive and attentive listening conditions, producing no differences in P1, N1, and P2 between the tinnitus and control subjects under any conditions. However, a different pattern of results emerged when the difference was examined between the attended and unattended responses. This attention-modulated cortical response was significantly greater in the tinnitus than control subjects: 3.9-times greater for N1 at 5 kHz (95% CI: 2.9 to 5.0, p = 0.007, η_p² = 0.24) and 3.0 for P2 at 500 Hz (95% CI: 1.9 to 4.5, p = 0.026, η_p² = 0.17). We interpreted the greater N1 modulation as local neural changes specific to the tinnitus frequency and the greater P2 as global changes to hearing loss. These two cortical measures were used to differentiate between the tinnitus and control subjects, producing 83.3% sensitivity and 76.9% specificity (AUC = 0.81, p = 0.006). These results suggest that the tinnitus brain is more plastic than that of the matched non-tinnitus controls and that the attention-modulated cortical response can be developed as a clinically meaningful biomarker for tinnitus. Full article

Agricultural green development represents an environmentally friendly and resource-efficient agricultural model, and it is a key way to achieve sustainable agricultural development. With the rapid rise of the digital economy, its influence is gradually spreading from urban to rural areas, and it has played a significant and far-reaching role in promoting the green transformation of agriculture. This paper employs the entropy weight method to measure the level of digital economy and agricultural green development in rural areas in 30 provincial administrative regions in China from 2012 to 2021 and analyzes the relationship between the two and the mechanisms behind it. The research results show that (1) the rural digital economy significantly promotes agricultural green development. (2) With the enhancement of agricultural green development, the impact of the rural digital economy on it initially increases and then declines. (3) The rural digital economy fosters agricultural green development by advancing agricultural technology, easing credit constraints, and promoting agricultural industry agglomeration. (4) Environmental regulation intensifies the positive influence of the rural digital economy on agricultural green development. This research significantly enhances our understanding of the mechanism by which the rural digital economy facilitates agricultural green development. It offers empirical evidence and recommendations for the government to formulate and implement effective policies to advance agricultural green transformation in the context of digital economy trends. Full article

Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be caused by extracellular matrix collagen and non-collagen components heterogeneously. This study compares the angiogenic potential of collagen type I-based scaffolds and collagen type I/glycosaminoglycans scaffolds by using the chick embryo chorioallantoic membrane (CAM) model and IKOSA digital image analysis. Two clinically used biomaterials, Xenoderm (containing type I collagen derived from decellularized porcine extracellular matrix) and a dual-layer collagen sponge (DLC, with a biphasic composition of type I collagen combined with glycosaminoglycans) were tested for their ability to induce new vascular network formation. The AI-based IKOSA app enhanced the research by calculating from stereomicroscopic images angiogenic parameters such as total vascular area, branching sites, vessel length, and vascular thickness. The study confirmed that Xenoderm caused a fast angiogenic response and substantial vascular growth, but was unable to mature the vascular network. DLC scaffold, in turn, produced a slower angiogenic response, but a more steady and organic vascular maturation and stabilization. This research can improve collagen-based knowledge by better assessing angiogenesis processes. DLC may be preferable to Xenoderm or other materials for functional neovascularization, according to the findings. Full article

Intraductal carcinoma of the prostate (IDC-P) has emerged as a distinct entity with significant clinical implications in prostate cancer (PCa) management. Despite historically being considered an extension of invasive PCa, IDC-P shows unique biological characteristics that challenge traditional diagnostic and therapeutic settings. This review explores the clinical management of IDC-P. While the diagnosis of IDC-P relies on specific morphological criteria, its detection remains challenging due to inter-observer variability. Emerging evidence underscores the association of IDC-P with aggressive disease and poor clinical outcomes across various PCa stages. However, standardized management guidelines for IDC-P are lacking. Recent studies suggest considering adjuvant and neoadjuvant therapies in specific patient cohorts to improve outcomes and tailor treatment strategies based on the IDC-P status. However, the current level of evidence regarding this is low. Moving forward, a deeper understanding of the pathogenesis of IDC-P and its interaction with conventional PCa subtypes is crucial for refining risk stratification and therapeutic interventions. Full article

With the rapid advancements in computer vision, using deep learning for strawberry disease recognition has emerged as a new trend. However, traditional identification methods heavily rely on manual discernment, consuming valuable time and imposing significant financial losses on growers. To address these challenges, this paper presents BerryNet-Lite, a lightweight network designed for precise strawberry disease identification. First, a comprehensive dataset, encompassing various strawberry diseases at different maturity levels, is curated. Second, BerryNet-Lite is proposed, utilizing transfer learning to expedite convergence through pre-training on extensive datasets. Subsequently, we introduce expansion convolution into the receptive field expansion, promoting more robust feature extraction and ensuring accurate recognition. Furthermore, we adopt the efficient channel attention (ECA) as the attention mechanism module. Additionally, we incorporate a multilayer perceptron (MLP) module to enhance the generalization capability and better capture the abstract features. Finally, we present a novel classification head design approach which effectively combines the ECA and MLP modules. Experimental results demonstrate that BerryNet-Lite achieves an impressive accuracy of 99.45%. Compared to classic networks like ResNet34, VGG16, and AlexNet, BerryNet-Lite showcases superiority across metrics, including loss value, accuracy, precision, F1-score, and parameters. It holds significant promise for applications in strawberry disease identification. Full article

Sesame seeds are important resources for relieving oxidation stress-related diseases. Although a significant variation in seeds’ antioxidant capability is observed, the underlying biochemical and molecular basis remains elusive. Thus, this study aimed to reveal major seed components and key molecular mechanisms that drive the variability of seeds’ antioxidant activity (AOA) using a panel of 400 sesame accessions. The seeds’ AOA, total flavonoid, and phenolic contents varied from 2.03 to 78.5%, 0.072 to 3.104 mg CAE/g, and 2.717 to 21.98 mg GAE/g, respectively. Analyses revealed that flavonoids and phenolic acids are the main contributors to seeds’ AOA variation, irrespective of seed coat color. LC-MS-based polyphenol profiling of high (HA) and low (LA) antioxidant seeds uncovered 320 differentially accumulated phenolic compounds (DAPs), including 311 up-regulated in HA seeds. Tricin, persicoside, 5,7,4′,5′-tetrahydro-3′,6-dimethoxyflavone, 8-methoxyapigenin, and 6,7,8-tetrahydroxy-5-methoxyflavone were the top five up-regulated in HA. Comparative transcriptome analysis at three seed developmental stages identified 627~2357 DEGs and unveiled that differential regulation of flavonoid biosynthesis, phenylpropanoid biosynthesis, and stilbene biosynthesis were the key underlying mechanisms of seed antioxidant capacity variation. Major differentially regulated phenylpropanoid structural genes and transcription factors were identified. SINPZ0000571 (MYB), SINPZ0401118 (NAC), and SINPZ0500871 (C3H) were the most highly induced TFs in HA. Our findings may enhance quality breeding. Full article

This study presents a comprehensive examination of Pinus kesiya var. langbianensis (Pinus kesiya var. langbianensis), the primary resin-extraction tree species in Yunnan Province, China. In this study, we formulated different concentration gradients of 0.25%, 0.5%, 1%, and 2% of diquat solution as tapping stimulant to test the effect of different concentrations on the resin gain rate of Pinus kesiya, and analyzed the relationship between anatomical structure, major chemical composition of turpentine and resin yield by methods such as wood anatomy and chemical composition analysis of turpentine. The primary focus of the investigation was on exploring the interrelationships among resin-tapping stimulants, anatomical structures, turpentine components, and resin yield. Research findings demonstrate a significant enhancement in resin production due to the application of stimulants, with the highest increase rate reaching 55% in a specific group, while others achieved approximately 30% increments. Moreover, measurement data about resin duct dimensions indicate a noteworthy increase in resin duct area for the stimulant-treated group compared to the control group. However, it should be noted that the impact on resin duct area by varying stimulant concentrations was relatively minor. Furthermore, continuous observation of resin extraction from different resin-yield classes of P. kesiya revealed insignificant variation in resin yield over time for the low and moderate resin-yield groups. In contrast, the high resin-yield group exhibited a gradual increase in resin production. Interestingly, the high resin-yield group exhibited the smallest resin duct area, but the highest resin duct density, indicating an interconnectedness of resin duct-related data that influences resin yield. Additionally, correlative investigations between anatomical structures and resin yield demonstrate a positive correlation between resin duct area and resin yield, total resin production, and average resin yield. This underscores the importance of resin duct area as a significant factor in resin production. On the other hand, the influence of stimulant concentrations on the turpentine components was found to be negligible. Overall, the correlation results suggest that turpentine components cannot reliably predict or differentiate between high and low resin-yield trees. This study provides a comprehensive analysis of the interrelationships among stimulants, anatomical structures, and turpentine components, offering a theoretical foundation for the resin extraction and resin processing industries in Yunnan Province. Full article