An integrated and rapid evaluation of Curcumae Radix from different botanical origins based on chemical components, antiplatelet aggregation effect and Fourier transform near-infrared spectroscopy.

Curcumae Radix (CR) is a widely used traditional Chinese medicine with significant pharmaceutical importance, including enhancing blood circulation and addressing blood stasis. This study aims to establish an integrated and rapid quality assessment method for CR from various botanical origins, based on chemical components, antiplatelet aggregation effects, and Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate algorithms. Firstly, ultra-performance liquid chromatography-photodiode array (UPLC-PDA) combined with chemometric analyses was used to examine variations in the chemical profiles of CR. Secondly, the activation effect on blood circulation of CR was assessed using an in vitro antiplatelet aggregation assay. The studies revealed significant variations in chemical profiles and antiplatelet aggregation effects among CR samples from different botanical origins, with constituents such as germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin, and curcumin showing a positive correlation with antiplatelet aggregation biopotency. Thirdly, FT-NIR spectroscopy was integrated with various machine learning algorithms, including Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Subspace K-Nearest Neighbors (Subspace KNN), to classify CR samples from four distinct sources. The result showed that FT-NIR combined with KNN and SVM classification algorithms after SNV and MSC preprocessing successfully distinguished CR samples from four plant sources with an accuracy of 100%. Finally, Quantitative models for active constituents and antiplatelet aggregation bioactivity were developed by optimizing the partial least squares (PLS) model with interval combination optimization (ICO) and competitive adaptive reweighted sampling (CARS) techniques. The CARS-PLS model achieved the best predictive performance across all five components. The coefficient of determination (R2p) and root mean square error (RMSEP) in the independent test sets were 0.9708 and 0.2098, 0.8744 and 0.2065, 0.9511 and 0.0034, 0.9803 and 0.0066, 0.9567 and 0.0172 for germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively. The ICO-PLS model demonstrated superior predictive capabilities for antiplatelet aggregation biotency, achieving an R2p of 0.9010, and an RMSEP of 0.5370. This study provides a valuable reference for the quality evaluation of CR in a more rapid and comprehensive manner.

Rapid detection of fertilizer information based on Raman spectroscopy and machine learning.

The rapid detection of fertilizer nutrient information is a crucial element in enabling intelligent and precise variable fertilizer application. However, traditional detection methods possess limitations, such as the difficulty in quantifying multiple components and cross-contamination. In this study, a rapid detection method was proposed, leveraging Raman spectroscopy combined with machine learning, to identify five types of fertilizers: K2SO4, (CO(NH2)2, KH2PO4, KNO3, and N:P:K (15-15-15), along with their concentrations. Qualitative and quantitative models of fertilizers were constructed using three machine learning algorithms combined with five spectral preprocessing methods. Two variable selection methods were used to optimize the quantitative model. The results showed that the classification accuracy of the five fertilizer solutions obtained by random forest (RF) was 100 %. Moreover, in terms of regression, partial least squares regression (PLSR) outperformed extreme learning machine (ELM) and least squares support vector machine (LSSVM), yielding prediction Rp2 within the range of 0.9843-0.9990 and a root mean square error in the range of 0.0486-0.1691. In addition, this study evaluated the impact of different water types (deionized water, well water, and industrial transition water) on the detection of fertilizer information via Raman spectroscopy. The results showed that while different water types did not notably affect the identification of fertilizer nutrients, they did exert a pronounced effect on the quantification of concentrations. This study highlights the efficacy of combining Raman spectroscopy with machine learning in detecting fertilizer nutrients and their concentration information effectively.

Highly Sensitive Detection of Sulfur Ion in Water by Four-Color Fluorescence Based on Cu-Containing Metal-Organic Framework.

In this paper, a highly sensitive method for sulfur ion (S2-) detection was developed based on a four-color fluorescence probe constructed from copper-containing metal-organic framework (CuBDC) and four dye-labeled single-strand DNA (ssDNA). In the absence of S2-, dye-labeled ssDNA can be adsorbed on the surface of CuBDC, and the dyes are close to copper ion on the CuBDC surface, their fluorescence is quenched by copper ion, and their fluorescence signals are weak. In the presence of S2- in the system, S2- reacts with copper ion in CuBDC to form CuS, which has a more stable structure than complex CuBDC, resulting in the decomposition of CuBDC. In this case, dye-labeled ssDNA are detached from the CuBDC surface and dissolved in the solution, and the fluorescence of the dyes is restored. Under the optimized conditions, there is a good linear relationship between the total fluorescence intensity of four dyes and the concentration of S2- in the range of 2 × 10-9 to 5 × 10-8 mol/L; the detection limit is 2.2 × 10-10 mol/L. The method has a good selectivity and accuracy, and it can be applied to the analysis and detection of S2- in actual water samples.

The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0).

The Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT) has been expanded to include more patients and CT attenuation correction imaging. We present the design and initial results from the updated registry. Methods: The updated REFINE SPECT is a multicenter, international registry with clinical data and image files. SPECT images were processed by quantitative software and CT images by deep learning software detecting coronary artery calcium (CAC). Patients were followed for major adverse cardiovascular events (MACEs) (death, myocardial infarction, unstable angina, late revascularization). Results: The registry included scans from 45,252 patients from 13 centers (55.9% male, 64.7 ± 11.8 y). Correlating invasive coronary angiography was available for 3,786 (8.4%) patients. CT attenuation correction imaging was available for 13,405 patients. MACEs occurred in 6,514 (14.4%) patients during a median follow-up of 3.6 y (interquartile range, 2.5-4.8 y). Patients with a stress total perfusion deficit of 5% to less than 10% (unadjusted hazard ratio [HR], 2.42; 95% CI, 2.23-2.62) and a stress total perfusion deficit of at least 10% (unadjusted HR, 3.85; 95% CI, 3.56-4.16) were more likely to experience MACEs. Patients with a deep learning CAC score of 101-400 (unadjusted HR, 3.09; 95% CI, 2.57-3.72) and a CAC of more than 400 (unadjusted HR, 5.17; 95% CI, 4.41-6.05) were at increased risk of MACEs. Conclusion: The REFINE SPECT registry contains a comprehensive set of imaging and clinical variables. It will aid in understanding the value of SPECT myocardial perfusion imaging, leverage hybrid imaging, and facilitate validation of new artificial intelligence tools for improving prediction of adverse outcomes incorporating multimodality imaging.

Pharmacophylogenetic insights into Scutellaria strigillosa Hemsl.: chloroplast genome and untargeted metabolomics, quantitative analysis and antibacterial analysis.

Scutellaria strigillosa Hemsl., known for its traditional use in Chinese herbal medicine, is valued for heat-clearing and detoxifying, promoting diuresis, reducing swelling, alleviating pain, and preventing miscarriage. Despite its historical use, comprehensive studies on pharmacophylogenetic analysis, including genetic and chemical profiles and the antimicrobial activity of S. strigillosa are still lacking. Understanding these aspects is crucial for fully realizing its therapeutic potential and ensuring sustainable use. This study aims to elucidate these aspects through comparative genomics, metabolomics, and antimicrobial assays with Scutellaria baicalensis Georgi and Scutellaria barbata D. Don. The chloroplast genome of S. strigillosa was assembled, measuring 152,533 bp, and revealing a high degree of conservation, especially in the protein-coding regions, and identified four regions trnK(UUU)-rps16, trnN(GUU)-trnR(ACG), accD-psaI, psbE-petL) of variability that could serve as phylogenetic markers. The phylogenetic analysis revealed a closer genetic relationship of S. strigillosa with S. tuberifera and S. scordifolia than traditionally classified, suggesting a need for taxonomic reevaluation within the genus. UPLC-Q-TOF-MS analysis in negative ion mode was used to explore the chemical diversity among these species, revealing distinct variations in their chemical compositions. S. strigillosa shared a closer chemical profile with S. barbata, aligning with phylogenetic findings. Metabolomic identification through Progenesis QI software resulted in the tentative identification of 112 metabolites, including a substantial number of flavonoids, diterpenoids, iridoid glycosides, phenylethanoid glycosides, and others. HPLC analysis further detailed the concentrations of 12 actives across the species, highlighting the variation in compound content. S. strigillosa shows antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa, similar to S. baicalensis root extracts. This research enhances the understanding of the phylogenetic and phytochemical profiles and the antibacterial activity of S. strigillosa, offering new insights into its medicinal properties. The findings suggest a need for taxonomic reevaluation within the genus and underscore the potential antibacterial activity of S. strigillosa for therapeutic applications. Further studies are encouraged to explore its full medicinal potential and contribute to the sustainable development of Scutellaria species.

Chiral Inorganic Nanomaterials Characterized by Advanced TEM: A Qualitative and Quantitative Study.

Chiral inorganic nanomaterials (CINMs) have garnered significant interest due to their exceptional optical, electronic, and catalytic properties, offering promising advancements in energy conversion, data storage, catalysis, and biomedicine. While traditional optical spectrophotometers reveal the chiroptical performance of CINMs on an ensemble level, the direct structural visualization for the qualitative and quantitative discernment of their chiral features has become increasingly distinct with the advancements of transmission electron microscopy (TEM) techniques. The need for reasonable and high-standard discrimination requirements of CINMs has driven the progress of chirality-based TEM technologies. Therefore, this review in the good season takes the initiative to summarize the current advancements in TEM technologies for CINMs characterization, emphasizing a qualitative analysis of chiral atomic-level features, 0D, 1D, and 2D nanocrystals, and assembled nanomaterials. Then, the quantitative methods for determining chirality is also highlighted, such as 3D electron tomography, and further address the evolution of chiral structures monitored by the Ex-situ and In-situ TEM technologies. By providing a roadmap for the current challenges and proposing future advancements in TEM technologies for the qualitative, quantitative, and real-time analysis of CINMs, it can drive innovations in the field of chiral nanomaterials as well as the development of TEM technologies.

Assessing the stability of daptomycin in icodextrin-based peritoneal dialysis solution.

BACKGROUND: The stability of antimicrobials in peritonitis during peritoneal dialysis (PD) solutions is a critical factor influencing treatment success. This study investigated the stability of daptomycin (DAP) when combined with icodextrin-based PD solution, by measuring DAP concentrations and observing any structural changes. METHODS: A dose of DAP (350 mg) was dissolved in 7 mL of saline in a clean bench. The solution was then injected into the large compartment (1,260 mL) of NICOPELIQ® Peritoneal Dialysis Solution and thoroughly mixed. Samples were collected at intervals ranging from 0 to 336 h (7 points in total). The concentration of DAP was quantified using high-performance liquid chromatography (HPLC). The structure of any unidentified peaks was determined using HPLC coupled with electrospray ionization tandem mass spectrometry. RESULTS: DAP maintained 90% of the initial concentration in NICOPELIC® for 72 h at room temperature and 12 h at 37 °C. Unidentified peaks, distinct from DAP, were detected during analysis. Further investigation indicated that these peaks corresponded to anhydrated DAP. CONCLUSIONS: The findings from this stability study are expected to enhance the effectiveness of outpatient management and preparation for treating peritonitis using DAP.

Quantification of relevant metabolites in apoptotic bodies from HK-2 cells by targeted metabolomics based on liquid chromatography-tandem mass spectrometry.

BACKGROUND: Apoptotic bodies play an important role in the cellular communication as a consequence of the great variety of biomolecules they harbor. There is evidence that 1st generation apoptotic bodies from HK-2 cells induced by cisplatin or UV light trigger apoptosis in naïve HK-2 cells whereas 2nd generation apoptotic bodies activate cell proliferation showing an opposite effect. Thus, the development of new analytical strategies to quantify the changes in the involved metabolites is imperative to shed light on the biological mechanisms which trigger apoptosis and cell proliferation. RESULTS: A LC-(Q-Orbitrap)MS method has been developed to quantify the metabolites unequivocally identified in the apoptotic body fluid from HK-2 cells in our previous works based on untargeted metabolomics. Thus, two different columns and gradients were tested and the HILIC column was selected taking into account the retention times and chromatographic separation. Also, different normal collision energies were tested for each metabolite and the parallel reaction monitoring was chosen to carry out the quantitative analysis. Once the method was optimized, it was evaluated in terms of linearity, limits of detection and quantification, matrix effects, accuracy, and precision, for each metabolite. Limits of detection ranged from 0.02 to 1.4 ng mL-1. A total of 9 relevant metabolites proposed as potential biomarkers to reveal metabolic differences among apoptotic bodies from HK-2 cells were quantified and some insights about the biological relevance were discussed. SIGNIFICANCE: The first targeted metabolomics methodology enabling the quantification of relevant metabolites in apoptotic bodies from HK-2 cells was developed using LC-(Q-Orbitrap)MS. Pyridoxine, kynurenine, and creatine concentrations were determined in apoptotic bodies from HK-2 cells treated with cisplatin and UV light. Phenylacetylglycine, hippuric acid, butyrylcarnitine, acetylcarnitine, carnitine, and phenylalanine were determined in 1st and 2nd generation apoptotic bodies from HK-2 cells treated with cisplatin. Concentrations determined were useful to establish their biological role in the metabolism.

Evaluation of analytical uncertainty in quantitative determination of elements - The case of boron.

BACKGROUND: The uncertainty including accuracy and precision is the most vital factor that determines the overall quality of quantitative analysis. The uncertainty has been, however, evaluated relatively within the same analytical technique. Given this background, the present study evaluates the uncertainty on quantitative elemental analysis with a quasi-absolute approach. The objectives of this study are (1) to investigate the analytical uncertainty of prompt gamma-ray analysis (PGA), a chemical interference-free method in principle, on the quantitative analysis of boron and (2) to evaluate the applicability of inductively coupled plasma optical emission spectrometry (ICP-OES), a common technique for quantitative elemental analysis including boron. RESULTS: PGA provided analytical quantity that is equivalent to the true quantity. The quantity values determined for a series of boron-containing samples are all well above the detection limit of the PGA system, the quantity resolution of which is also much smaller than the minimum difference in quantity among the samples. These facts confirm that the evaluation of analytical uncertainty with the present PGA system is statistically meaningful. The analytical uncertainty in both methods was adequately evaluated by comparing the results from PGA and ICP-OES for a series of boron-containing materials with different physical/chemical properties (i.e. CrB2, B4C, and solidified products of stainless steel-B4C melt) and the major sources of uncertainty in both methods are specified. The conditions for sample preparation/pretreatment were optimized to lower the uncertainty. SIGNIFICANCE AND NOVELTY: This study proposes a new concept to perform the quasi-absolute evaluation of analytical uncertainty by employing a chemical interference-free technique. The proposed concept is not limited to the combination of PGA and ICP-OES as demonstrated in this study, but it is applicable to any combination of any analytical methods for any element. Hence, the concept demonstrated in this study could be beneficial to a wide range of analytical chemistry.

Spectral reconstruction from RGB image to hyperspectral image: Take the detection of glutamic acid index in beef as an example.

The use of spectral reconstruction (SR) to recovery RGB images to full-scene hyperspectral image (HSI) is an important measure to achieve real-time and low-cost HSI applications. Taking the detection of glutamic acid index for 360 beef samples as an example, the feasibility of using 11 state-of-the-art reconstruction algorithms to achieve RGB to HSI in complex food systems was investigated. The multivariate correlation analysis was used to prove that RGB is a projection of three-channel comprehensive coverage wide-band information. The comprehensive quality attributes (PSNR-Params-FLOPS) was proposed to determine the optimal reconstruction model (MST++, MST, MIRNet, and MPRNet). Moreover, SSIM values and t-SNE were introduced to evaluate the consistency of the reconstruction results. Finally, Lightweight Transformer was used to establish the detection models of Raw-HSI, RGB and SR-HSI for the prediction of glutamic acid index for beef. The results showed that the MST++ model exhibited the best performance in SR, with RMSE, PSNR, and SSIM values of 0.015, 36.70, and 0.9253, respectively. Meanwhile, the prediction effect of MST++ (R2P = 0.8422 and RPD = 2.46) reconstructed was close to the Raw-HSI (R2P = 0.8526 and RPD = 2.69). The results provide practical application scenarios and detailed analysis ideas for RGB-to-HSI.

Quantitative Analysis on Vessel Stiffness and Vector Flow Imaging in the Assessment of Carotid Artery Structural and Functional Changes in Patients With Type 2 Diabetes.

OBJECTIVE: To explore the value of RF-data-based quantitative analysis on vessel stiffness (R-QVS) combined with dynamic vector flow imaging (VFI) in evaluating structural and functional changes in the carotid arteries of patients with type 2 diabetes mellitus (T2DM). METHODS: A prospective study was conducted between October 2022 and April 2024, including 275 consecutive subjects (50 volunteers as controls, 108 patients with T2DM and normal carotid intima-media thickness (CIMT), and 117 patients with T2DM and thickened CIMT). Carotid intima-media thickness (IMT) was measured using real-time intima-media thickness (RIMT) technology, while R-QVS was employed to measure the systolic diameter (Diam), displacement (Dist), hardness coefficient (HC), and pulse wave velocity (PWV) of the distal segment of the carotid artery. VFI was used to measure the maximum wall shear stress (WSSmax), mean wall shear stress (WSSmean), and maximum instantaneous velocity (Vmax) of the vessel wall. Differences in ultrasound parameters among the three groups were compared, and receiver operating characteristic (ROC) curves were plotted to calculate the area under the curve (AUC), evaluating the efficacy of these parameters in assessing structural and functional changes in the carotid arteries of patients with T2DM. RESULTS: There were statistically significant differences in carotid IMT, Diam, Dist, HC, PWV, WSSmax, and Vmax among the three groups (all p < 0.01). The AUCs for evaluating structural and functional changes in the carotid arteries of patients with T2DM using carotid ultrasound parameters Diam, Dist, HC, PWV, WSSmax, and Vmax were 0.64, 0.68, 0.83, 0.88, 0.86, and 0.82, respectively. Multiple linear regression analysis identified Dist., HC, PWV, WSSmax, and WSSmean as influencing factors for CIMT in T2DM patients (with ß values of -0.406, 0.515, 0.564, -0.472, and -0.438, respectively; all p < 0.05). CONCLUSION: R-QVS and VFI techniques contribute to the early assessment of structural and functional changes in the carotid arteries of patients with type 2 diabetes mellitus. Compared with controls, T2DM patients exhibit more advanced functional changes than morphological changes despite normal CIMT. The enhanced sensitivity, reproducibility, and detailed assessment capabilities of these methods make them valuable tools in the early detection and intervention of cardiovascular risk in T2DM.

Single Cell mass spectrometry: Towards quantification of small molecules in individual cells.

Studying cell heterogeneity can provide a deeper understanding of biological activities, but appropriate studies cannot be performed using traditional bulk analysis methods. The development of diverse single cell bioanalysis methods is in urgent need and of great significance. Mass spectrometry (MS) has been recognized as a powerful technique for bioanalysis for its high sensitivity, wide applicability, label-free detection, and capability for quantitative analysis. In this review, the general development of single cell mass spectrometry (SCMS) field is covered. First, multiple existing SCMS techniques are described and compared. Next, the development of SCMS field is discussed in a chronological order. Last, the latest quantification studies on small molecules using SCMS have been described in detail.

Development of a Quality Evaluation Method for Allii Macrostemonis Bulbus Based on Solid-Phase Extraction-High-Performance Liquid Chromatography-Evaporative Light Scattering Detection Chromatographic Fingerprinting, Chemometrics, and Quantitative Analysis of Multi-Components via a Single-Marker Method.

As a traditional Chinese medicine (TCM), Allii Macrostemonis Bulbus (AMB) is a key herb for the treatment of thoracic paralytic cardiac pain, but its quality evaluation method has not yet been fully clarified. In this study, chromatographic fingerprints of AMB were developed using solid-phase extraction-high-performance liquid chromatography-evaporative light scattering detection (SPE-HPLC-ELSD) to evaluate the quality of AMB from various origins and processing methods. This was achieved by employing chemical pattern recognition techniques and verifying the feasibility and applicability of the quality evaluation of AMB through the quantitative analysis of multi-components via a single-marker (QAMS) method. Through the analysis of the fingerprints of 18 batches of AMB, 30 common peaks were screened, and 6 components (adenosine, syringin, macrostemonoside T, macrostemonoside A, macrostemonoside U, and macrostemonoside V) were identified. Moreover, three differential markers (macrostemonoside A, macrostemonoside T, and macrostemonoside U) were screened out using chemometrics techniques, including principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Subsequently, a QAMS method was established for macrostemonoside T and macrostemonoside U using macrostemonoside A as an internal reference. The results demonstrate the method's accuracy, reproducibility, and stability, rendering it suitable for the quality evaluation of AMB. This study provides a theoretical basis for drug quality control and the discovery of quality markers for AMB.

Quantitative assessment of the oral microvasculature using optical coherence tomography angiography.

Introduction: Early diagnosis of oral squamous cell carcinoma can greatly improve treatment success rate and patient survival. Although Optical Coherence Tomography (OCT) based Angiography (OCTA) is a promising in vivo technique in oral imaging, there is a need for objective assessment of oral microvasculature. Methods: This study aimed to demonstrate a comprehensive methodology of quantitative assessing OCTA intraoral scanning results to provide measurable, reproducible data and to avoid subjective visual interpretations. Data were collected from 37 healthy subjects in total across four intraoral sites-buccal mucosa (n = 32), labial mucosa (n = 24), floor of the mouth (n = 13), and hard palate (n = 8)-using a non-invasive swept-source OCT system. Four quantitative metrics-vessel area density, vessel skeleton density, vessel diameter index, and a newly proposed weighted Tortuosity Index-were used to assess OCTA images in oral applications. Results: The quadruple quantitative assessment's repeatability was evaluated to be reliable. Analysis of a benign ulcer case revealed differences in these metrics compared to healthy cases. Discussion/Conclusion: In conclusion, we demonstrated a comprehensive method to quantify microvasculature in the oral cavity, showing considerable promise for early diagnosis and clinical management of oral diseases.

3D hot spot construction on the hydrophobic interface with SERS tags for quantitative detection of pesticide residues on food surface.

The overuse of pesticides results in excessive pesticide residues, posing a potential threat to human health. Herein, this work proposes a SERS substrate for the quantitative analysis of pesticide residues on food surfaces. Au cores are assembled on PS microspheres, followed by the modification of Raman internal standards (1,4-BDT) on the gold core surface and the growth of the Au shell. After incubating the analytes with PS@Au@1,4-BDT@Au particles, the mixture is dropped on the hydrophobic gold film for drying before detection. The SERS substrates exhibited high sensitivity and stability, with a detection limit of 10-12 M and an RSD of less than 7 %. Combined with a portable Raman spectrometer, the SERS detection of pesticide residues on three kinds of food surfaces is carried out, with a sensitivity of 10-11 M, meeting the US MRLs regulations. Therefore, this strategy may possess significant potential for future food safety.

Is Microporous Carbon Confined Nano Si Composite the Best Anode Choice for High-Energy-Density Lithium-Ion Batteries?

Microporous carbon confined nano silicon composites (Si/m-C) are considered to be the best anode materials for high-energy-density lithium-ion batteries compared with the other Si-based materials such as SiO, due to high initial Coulombic efficiency (ICE) and capacity, as well as good cycling stability. However, there is a lack of multilevel comprehensive evaluation of Si/m-C, which poses potential risks to the commercial application. Herein, combined with quantitative titration, mechanical characterization, and bulk/interface evolution analysis, a systematic evolution of commercialized Si/m-C from the particle level to the cylindrical cell level is conducted, revealing the decay mechanism and proposing corresponding solutions. Among them, it is well demonstrated that the Si/m-C still withstands huge volume expansion of over 200% with poor mechanical strength, causing the electrical contact loss of active LixSi and severe interfacial side reactions. Moreover, even blending more than 90% graphite cannot completely suppress its volumetric strain, and the combination of highly flexible single-walled carbon nanotubes (SWCNT) is necessary. In response to this, the 32700-type cylindrical cell with a designed capacity of 9.5 Ah is assembled by mixing Si/m-C with 90% graphite and SWCNT as anode, achieving a long-term cycling stability over 300 cycles at 0.5 C with a capacity retention of 94.8%.

Exploring psychological help-seeking behaviors and stigma perception among cancer patients: a study on their impact on psychosocial adjustment.

OBJECTIVE: The study investigates the relationships between psychological help-seeking behaviors, stigma perception, and psychosocial adjustment among cancer patients. Understanding these dynamics is crucial for enhancing the mental health and overall well-being of individuals battling cancer. METHODS: This descriptive cross-sectional study involved 387 cancer patients, with data collected through structured questionnaires assessing attitudes toward seeking psychological help (ATSPPH-SF), stigma perception (SSRPH), and psychosocial adjustment (PAIS-SR). Statistical analyses, including correlation and hierarchical regression models, were conducted to explore the associations between these variables. RESULTS: The findings revealed a significant inverse relationship between perceived stigma and help-seeking behaviors, indicating that higher stigma is associated with reduced likelihood of seeking psychological support. Additionally, patients who were more reluctant to seek help demonstrated poorer psychosocial adjustment. Factors such as age, education level, marital status, and treatment status also played significant roles in influencing these outcomes. CONCLUSION: The study underscores the need for targeted interventions to reduce stigma and encourage help-seeking among cancer patients to improve their psychosocial adjustment and quality of life. Integrating mental health services into oncology care and addressing the stigma associated with psychological support are essential steps in enhancing patient outcomes.

Depositional Environment and Ecological Response of Bioconstructions: A Case Study of Southern China (Guizhou Province) in Moscovian-Gzhelian.

From the late Carboniferous to the early Permian, multiple pulses of glaciation and deglaciation have been caused by the LPIA. The Pennsylvanian period experienced phases of recovery, proliferation, and decline, ultimately forming a reef system distinctly different from that of the Mississippian period. During the late Bashkirian to Moscovian, the metazoan reef experienced a limited resurgence, with reef predominantly formed by chaetetid developing in the United States, northern China, and Japan. During the Kasimovian to Gzhelian, the phylloid algal reef dominated the global reef systems. In the late Pennsylvanian, bioconstruction cases and paleoenvironmental proxies in southern Guizhou Province were studied to investigate the composition, recovery, and evolutionary processes of the bioconstructions as well as their response to environmental variations during this period. Several bioconstructions have been reported in the Lumazhai section of Houchang Town, Guizhou Province, southern China, from the Moscovian to the Gzhelian. The upper Carboniferous strata are well-preserved and continuously exposed. The continuous strata, abundant fossils, and diverse bioconstructions provide excellent research materials for exploring the mutual constraints between organisms and their environment. This study identified ten microfacies, whose vertical evolution indicated significant changes in the depositional environment related to relative sea-level fluctuations. Skeletal grains are widely present in these facies. Among them, foraminifera, algae, bryozoans, crinoids, and Tubiphytes are the most common and exhibit distinct distribution characteristics in various environments. Quantitative statistics, CCA and theoretical ecospace have been utilized to examine and interpret environmental impact factors. Quantitative analysis of their relative abundance and distribution patterns provides insights into the complex interactions between organisms and environmental factors. The relative abundances of different organisms and factors controlling their bioconstructions are influenced by relative sea-level changes. CCA analysis reveal that hydrodynamic conditions are the primary influencing factor. Variation trends in average tiering and motility reveal the characteristics of biological communities during environmental changes in phylloid algae and microbial bioconstructions. These bioconstructions are not directly correlated with changes in environmental factors, and the biological communities in phylloid algae mounds and biostromes exhibit similar organism compositions and ecological niches across different environments.

Dynamic Fault Tree Generation and Quantitative Analysis of System Reliability for Embedded Systems Based on SysML Models.

As embedded systems become increasingly complex, traditional reliability analysis methods based on text alone are no longer adequate for meeting the requirements of rapid and accurate quantitative analysis of system reliability. This article proposes a method for automatically generating and quantitatively analyzing dynamic fault trees based on an improved system model with consideration for temporal characteristics and redundancy. Firstly, an "anti-semantic" approach is employed to automatically explore the generation of fault modes and effects analysis (FMEA) from SysML models. The evaluation results are used to promptly modify the system design to meet requirements. Secondly, the Profile extension mechanism is used to expand the SysML block definition diagram, enabling it to describe fault semantics. This is combined with SysML activity diagrams to generate dynamic fault trees using traversal algorithms. Subsequently, parametric diagrams are employed to represent the operational rules of logic gates in the fault tree. The quantitative analysis of dynamic fault trees based on probabilistic models is conducted within the internal block diagram of SysML. Finally, through the design and simulation of the power battery management system, the failure probability of the top event was obtained to be 0.11981. This verifies that the design of the battery management system meets safety requirements and demonstrates the feasibility of the method.

Quantification of osilodrostat in horse urine using LC/ESI-HRMS to establish an elimination profile for doping control.

Aim: The use of osilodrostat, developed as a medication for Cushing's disease but categorized as an anabolic agent, is banned in horses by both the International Federation of Horseracing Authorities and the Fédération Equestre Internationale. For doping control purposes, elimination profiles of hydrolyzed osilodrostat in horse urine were established and the detectability of free forms of osilodrostat and its major metabolite, mono-hydroxylated osilodrostat (M1c), was investigated.Materials & methods: Post-administration urine samples obtained from a gelding and three mares were analyzed to establish the elimination profiles of osilodrostat using a validated method involving efficient enzymatic hydrolysis followed by LC/ESI-HRMS analysis.Results: Applying the validated quantification method with an LLOQ of 0.05 ng/ml, hydrolyzed osilodrostat could be quantified in post-administration urine samples from 48 to 72 h post-administration; by contrast, both hydrolyzed osilodrostat and M1c were detected up to 2 weeks. In addition, confirmatory analysis identified the presence of hydrolyzed osilodrostat for up to 72 h post-administration.Conclusion: For doping control purposes, we recommend monitoring both hydrolyzed M1c and osilodrostat because of the greater detectability of M1c and the availability of a reference material of osilodrostat, which is essential for confirmatory analysis.

[Box: see text].