PURPOSE: To judge the injury mode and injury severity of the real human body through the measured values of anthropomorphic test devices (ATD) injury indices, the mapping relationship of lumbar injury between ATD and human body model (HBM) was explored. METHODS: Through the ATD model and HBM simulation, the mapping relationship of lumbar injury between the 2 subjects was explored. The sled environment consisted of a semi-rigid seat with an adjustable seatback angle and a 3-point seat belt system with a seatback-mounted D-ring. Three seatback recline states of 25°, 45°, and 65° were designed, and the seat pan angle was maintained at 15°. A 23 g, 47 km/h pulse was used. The validity of the finite element model of the sled was verified by the comparison of ATD simulation and test results. ATD model was the test device for human occupant restraint for autonomous vehicles (THOR-AV) dummy model and HBM was the total human model for safety (THUMS) v6.1. The posture of the 2 models was adjusted to adapt to the 3 seat states. The lumbar response of THOR-AV and the mechanical and biomechanical data on L1 - L5 vertebrae of THUMS were output, and the response relationship between THOR-AV and THUMS was descriptive statistically analyzed. RESULTS: Both THOR-AV and THUMS were submarined in the 65° seatback angle case. With the change of seatback angle, the lumbar spine axial compression force (F_z) of THOR-AV and THUMS changed in the similar trend. The maximum F_z ratio of THOR-AV to THUMS at 25° and 45° seatback angle cases were 1.6 and 1.7. The flexion moment (M_y) and the time when the maximum M_y occurred in the 2 subjects were very different. In particular, the form of moment experienced by the L1 - L5 vertebrae of THUMS also changed. The changing trend of M_y measured by THOR-AV over time can reflect the changing trend of maximum stress of L1 and L2 of THUMS. CONCLUSION The F_z of ATD and HBM presents a certain proportional relationship, and there is a mapping relationship between the 2 subjects on F_z. The mapping function can be further clarified by applying more pulses and adopting more seatback angles. It is difficult to map M_y directly because they are very different in ATD and HBM. The M_y of ATD and stress of HBM lumbar showed a similar change trend over time, and there may be a hidden mapping relationship.
Humans ; Lumbar Vertebrae/injuries* ; Finite Element Analysis ; Biomechanical Phenomena ; Manikins ; Spinal Injuries/physiopathology*

The blood-brain barrier (BBB) plays a crucial role in maintaining the homeostasis of the brain's internal environment, which poses challenges to the treatment of central nervous system diseases. Drug carriers can aid in the delivery of therapeutic agents across the BBB to exert their pharmacological effects. The article reviewed the pathways for drug delivery across the BBB, the intracerebral fate and the classification of drug carriers and focuses on the functions and characteristics of liposomes, exosomes, apoptotic bodies, cell-penetrating peptides, and cell-targeting peptides. The review will provide an outlook on the future and challenge of research in the field of drug delivery across the BBB.

In recent years, with the increasing societal focus on drug quality and safety, quality issues have become a major challenge faced by the pharmaceutical industry, directly impacting consumer health and market trust. By combining multispectral imaging technology with machine learning, it is possible to achieve rapid, non-destructive, and precise detection of traditional Chinese medicine(TCM) preparations, thereby revolutionizing traditional detection methods and developing more convenient and automated solutions. This paper provides a comprehensive review of the current applications of rapid, non-destructive detection techniques based on machine learning algorithms in the field of TCM preparations. It analyzed the principles and advantages of commonly used rapid, non-destructive detection techniques, offering a reference for the application and promotion of these technologies in TCM preparation detection. Additionally, this paper explored various data preprocessing techniques, operational processes, and machine learning algorithms to enhance data utilization efficiency. Finally, it focused on the challenges of applying machine learning in TCM preparation detection and offered corresponding recommendations, providing guidance for the future integration of machine learning with rapid, non-destructive detection techniques in practical production.
Machine Learning ; Drugs, Chinese Herbal/analysis* ; Medicine, Chinese Traditional/methods* ; Humans ; Quality Control

At present, China's traditional Chinese medicine(TCM) industry is developing rapidly with the support of modern science and technology. While promoting economic development and improving national health, it has brought multiple environmental problems. Under the "dual carbon" goals, the ecological fine manufacturing of TCM may become one of the breakthroughs for the TCM industry to practice low-carbon economy. From the perspective of low-carbon economy and considering the current situation of TCM pharmaceutical manufacturing, this paper analyzes the problems and shortcomings of the TCM pharmaceutical industry. In view of the key factors influencing the quality of TCM preparations under the ecological fine manufacturing mode, this paper proposes a practical and feasible selection plan for the ecological fine manufacturing mode of TCM, aiming to provide research ideas and a theoretical basis for the TCM industry in helping to achieve the goals of carbon peaking and carbon neutrality.
Drugs, Chinese Herbal/economics* ; Medicine, Chinese Traditional ; Carbon/analysis* ; China ; Drug Industry/economics*

The construction method and simulation parameter settings for the discrete element model of Jianwei Xiaoshi Granules, as the primary material of Jianwei Xiaoshi Tablets, are not yet clear. The accuracy of the simulation model significantly influences the dynamic response characteristics between granules. Therefore, it is necessary to calibrate the parameters to improve the accuracy of the simulation parameters. Using the repose angle of Jianwei Xiaoshi Granules as the response value, the response surface methodology was employed to optimize and calibrate the discrete element parameters. Physical experiments were conducted to determine the physical properties of Jianwei Xiaoshi Granules. Based on the Hertz-Mindlin with Johnson-Kendall-Roberts(JKR) V2 model and virtual simulation methods, a repose angle determination model was constructed in EDEM software. The repose angle was measured using image analysis and numerical fitting methods. The Plackett-Burman experiment was used to screen the initial parameters for significance in the discrete element simulation. The significant parameters were then subjected to a steepest ascent experiment to determine the optimal parameter range. Furthermore, based on the Box-Behnken experiment, a second-order regression equation between significant parameters and repose angle was established, with the repose angle of 37.64° in the physical experiment as the target value. The regression equation was optimized and solved. The significance screening experiment revealed that the granule-granule static friction coefficient, granule-granule rolling friction, and granule-steel plate rolling friction of Jianwei Xiaoshi Granules significantly influenced the simulated repose angle. The optimal parameter combination was found to be 0.330, 0.222, and 0.229. The simulation results with this optimal parameter combination showed that there was no significant difference between the simulated repose angle and the repose angle obtained in the physical experiment, with a relative error of 0.05%, which further validated the reliability of the calibrated discrete element parameters for Jianwei Xiaoshi Granules.
Drugs, Chinese Herbal/chemistry* ; Calibration ; Computer Simulation

Identification of critical material attributes(CMAs) is a key issue in the quality control of large-scale TCM products like Jianwei Xiaoshi Tablets. This study focuses on the granules of Jianwei Xiaoshi Tablets, using tablet tensile strength as the primary quality attribute. A method for identifying the CMAs and a design space for the granules were established, along with a predictive model for the granule CMAs based on Fourier transform near-infrared spectroscopy(FT-NIR). First, granules of Jianwei Xiaoshi Tablets with different properties were prepared using a partial factorial design method from the design of experiments(DOE). The powder properties of the granules were measured. An orthogonal partial least squares(OPLS) model was established to correlate the powder properties with tensile strength. Based on the characteristics of the comprehensive variables extracted by OPLS, the independent variables with the greatest explanatory power for tensile strength were identified. FT-NIR technology was then employed to establish a predictive model for the granule CMAs. The final CMAs identified were hygroscopicity, moisture content, D_(50), collapse angle, mass flow rate, and tapped density. The coefficients of determination of the prediction set(R■) and relative percentage deviation(RPD) of the prediction set for flowability, D_(50), and moisture content were 0.891, 0.994, and 0.998; and 2.97, 12.4, and 20.7, respectively. The established OPLS model clearly identified the impact of various factors on tensile strength, demonstrating good fit results. The model exhibited high prediction accuracy and can be used for the rapid and accurate determination of CMAs in granules of Jianwei Xiaoshi Tablets.
Drugs, Chinese Herbal/chemistry* ; Tablets/chemistry* ; Tensile Strength ; Quality Control ; Spectroscopy, Fourier Transform Infrared ; Spectroscopy, Near-Infrared

The application of new-generation information technologies such as big data, the internet of things(IoT), and cloud computing in the traditional Chinese medicine(TCM)manufacturing industry is gradually deepening, driving the intelligent transformation and upgrading of the TCM industry. At the current stage, there are challenges in understanding the extraction process and its mechanisms in TCM. Online detection technology faces difficulties in making breakthroughs, and data throughout the entire production process is scattered, lacking valuable mining and utilization, which significantly hinders the intelligent upgrading of the TCM industry. Applying data-driven technologies in the process of TCM extraction can enhance the understanding of the extraction process, achieve precise control, and effectively improve the quality of TCM products. This article analyzed the technological bottlenecks in the production process of TCM extraction, summarized commonly used data-driven algorithms in the research and production control of extraction processes, and reviewed the progress in the application of data-driven technologies in the following five aspects: mechanism analysis of the extraction process, process development and optimization, online detection, process control, and production management. This article is expected to provide references for optimizing the extraction process and intelligent production of TCM.
Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Quality Control ; Big Data ; Algorithms

Tumor brings great threat to human public health. In recent years, incidence rate and mortality of tumor were rapidly increased in the world. Anti-tumor therapies have undergone the development of cytotoxic therapy, targeted therapy, and immunotherapy. Among them, tumor immunotherapy is rapidly developed and becomes an important anti-tumor therapy in recent years, although it also brings some related side effects. Tumor microenvironment (TME) is composed of immune cells, vascular vessels, fibroblasts, the extracellular matrix, etc. TME significantly affects the efficacy of immunotherapy. Macrophages in the TME are named as tumor associated macrophages (TAMs). Recently, increasing studies have shown that TAMs play an important role in the regulation of tumor immunity, especially in tumor immune surveillance and immune escape. Currently, more and more anti-tumor immunotherapy strategies targeting TAMs are at the development stage. Based on the important role of TAMs in the TME and their potential as therapeutic targets in tumor immunotherapy, we first reviewed the subtypes and functions of TAMs, as well as the roles of TAMs in tumors. Furthermore, we summarized the research progress on anti-tumor strategies targeting TAMs and the current status of drug targeting TAMs. The current review will provide new ideas and novel insights for tumor immunotherapy.

Chronic psychological stress can promote vascular diseases, such as hypertension and atherosclerosis. This study aims to explore the effects and mechanism of chronic psychological stress on aortic medial calcification (AMC). Rat arterial calcification model was established by nicotine gavage in combination with vitamin D₃ (VitD₃) intramuscular injection, and rat model of chronic psychological stress was induced by humid environment. Aortic calcification in rats was evaluated by using Alizarin red staining, aortic calcium content detection, and alkaline phosphatase (ALP) activity assay. The expression levels of the related proteins, including vascular smooth muscle cells (VSMCs) contractile phenotype marker SM22α, osteoblast-like phenotype marker RUNX2, and endoplasmic reticulum stress (ERS) markers (GRP78 and CHOP), were determined by Western blot. The results showed that chronic psychological stress alone induced AMC in rats, further aggravated AMC induced by nicotine in combination with VitD₃, promoted the osteoblast-like phenotype transformation of VSMCs and aortic ERS activation, and significantly increased the plasma cortisol levels. The 11β-hydroxylase inhibitor metyrapone effectively reduced chronic psychological stress-induced plasma cortisol levels and ameliorated AMC and aortic ERS in chronic psychological stress model rats. Conversely, the glucocorticoid receptor agonist dexamethasone induced AMC, promoted AMC induced by nicotine combined with VitD₃, and further activated aortic ERS. The above effects of dexamethasone could be inhibited by ERS inhibitor 4-phenylbutyrate. These results suggest that chronic psychological stress can lead to the occurrence and development of AMC by promoting glucocorticoid synthesis, which may provide new strategies and targets for the prevention and control of AMC.
Rats ; Animals ; Glucocorticoids/metabolism* ; Rats, Sprague-Dawley ; Nicotine/metabolism* ; Hydrocortisone/metabolism* ; Muscle, Smooth, Vascular ; Dexamethasone/metabolism* ; Vascular Calcification/metabolism* ; Myocytes, Smooth Muscle/metabolism* ; Cells, Cultured

Objective:To study the genetic profile of neonatal hyperbilirubinemia with unknown etiology in Guangdong Province and the clinical significance of jaundice-related genetic screening.Methods:From July to September, 2021, neonates with hyperbilirubinemia of unknown etiology born in different hospitals in Guangdong Province were studied. 24 neonatal jaundice-related exons were sequenced using targeted capture and high-throughput sequencing technology. The pathogenic variants were analyzed.Results:A total of 331 cases, 139 (42.0%) cases showed positive screening results with five diseases, including 65 (19.6%) cases of Gilbert syndrome, 48 (14.5%) cases of glucose-6-phosphate dehydrogenase (G6PD) deficiency,18 (5.4%) cases of sodium taurocholate cotransporting polypeptide deficiency, 4 (1.2%) cases of Citrin deficiency and 4 (1.2%) cases of Dubin-Johnson syndrome. 149 (45.0%) cases carried one or more genetic variants and 43 (13.0%) cases showed no clinically significant variants. The 8 high-frequency mutation loci (carrier rate >1%) are UGT1A1 gene c.211G>A and c.1091C>T, G6PD gene c.1466G>T and c.1478G>A, SLC10A1 gene c.800C>T, SLC25A13 gene c.852_855del TATG, HBB gene c.126_129delCTTT and c.316-197C>T.Conclusions:Genetic factors are important for neonatal hyperbilirubinemia with unknown etiology in Guangdong. The common pathogenic genes are UGT1A1, G6PD, SLC10A1, and SLC25A13 and the population carries high-frequency mutation loci. Therefore, genetic screening in neonates with hyperbilirubinemia of unknown etiology has important clinical significance.